cc: Life Science Podcast: Recent Episodes

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Kris Barnette is a creative powerhouse—the President of All Good Marketing and an adjunct professor at Kent State—who brings a level of “swagger” to life science branding.

Kris is focused on turning Ontario, Canada, into a global commercial powerhouse in the life sciences.

Ontario has everything a biotech hub needs: world-class infrastructure, elite academic institutions, and incredible talent. However, Kris points out a “commercialization chokehold” that prevents the region from reaching global dominance. The science is often buried under layers of academic jargon and conservative positioning.

Kris is tackling this head-on with his upcoming project, The Ontario Life Science Founder Marketing Glow Up. It’s a guide designed to help PhD founders shift their mindset from “poster presentation” to “brand beast”.

One of the biggest hurdles for scientist-founders is the “curse of knowledge”. In academia, you’re taught to be conservative with data and open to endless debate. But as Kris explained, once you move from research to a venture, you are no longer just doing science—you are running a business.

Marketing isn’t just “mascara” or “bedazzle” you sprinkle on a product once it’s ready for the spotlight. It’s a muscle. It’s about charting a commercial path, building partnerships, and communicating value to three key audiences: investors, partners, and clinicians.

We talked about “Demand Gen Without Desperation,” a chapter in his book inspired by his work with Lee Jay Lowenstein at Stellar Scientific. Kris and Lee decided to inject some levity into the brand by creating the “Lab Llamas”—a family of characters like Lana Llama (Customer Service) and Leon Llama (Shipping).

While it might seem risky to use comic-book-style flyers in a conservative field, the data backed it up. Market research showed that 90% of customer sentiment was positive because people appreciated the friendliness and approachability. It proves that having a sense of humor doesn’t make you unprofessional; it makes you human.

Even for a veteran like Kris, with 30 years of marketing experience, putting yourself out there is hard. He admitted to a “reverse curse of knowledge”—feeling like if he knows something, everyone else must know it too, so why bother posting it on LinkedIn?.

But “invisible innovation” is a danger to any business. If your website is a “coming soon” page or your LinkedIn is silent, you’ve already lost. Kris had to overcome his own shyness to launch All Good Marketing in Canada, even navigating the hurdles of finding local talent to get his new site, allgoodmarketing.ca, live.

For U.S. companies looking to move north, Kris warns against simply “importing loud marketing”. The Canadian market is more risk-averse and relationship-driven. In Canada, trust is the primary currency; it’s earned slower, but it lasts much longer. His approach combines “Substance, Savvy, and Swagger” to help these companies get noticed without losing that essential human connection.

As a final surprise, Kris introduced his “aluminum shepherd,” Gizmo—a robot dog that will serve as his co-host for his upcoming 14-episode audio book podcast.

It was a fittingly creative end to the show. While this is the last episode of Life Science Marketing Radio, I am so grateful to the 200+ guests and the thousands of listeners who have joined me on this journey over the last 11 years.

Wishing you all the best.

Chris

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At the Advanced Lateral Flow Conference, I spoke with Jeremy Elser, Head of Science Operations at Palantir and founder of Ship of Theseus, a biotech company tackling longevity and regenerative medicine. The name refers to the Greek thought experiment about replacing every plank on a ship over time, similar to Jeremy’s vision to keep rebuilding the human body, replacing the cellular “planks” so it stays functional indefinitely.

He’s focusing on restoring the body’s natural ability to regenerate using resident stem cells. Damage accumulates linearly throughout life, but aging accelerates when our capacity to replace that damage falters. His company aims to “re-up” that regenerative capacity, thus the metaphor of the Ship of Theseus .

Jeremy also spoke at the conference about using AI and large language models (LLMs) to break down complex scientific questions into smaller, solvable ones. This conversation was fascinating to me in regards to both the biology and the LLMs, discovering what’s possible with both.

Jeremy compared an LLM to an eager intern—smart, well-informed, but needing structure and direction. You can’t just hand it a huge problem like “design a new drug protocol” and expect perfection. But if you break that into smaller, ordered tasks like “find existing injury models,” “suggest positive controls,” “compare published protocols”, the system can produce remarkably intelligent, end-to-end workflows.

That approach mirrors how good scientists think. Start with clear purpose, choose the right model for the goal, and use well-established methods when you need confidence or novel ones when you want to show something better. It’s part strategy, part rigor, driven by intention. Using an LLM to see where your FDA submission meets (or doesn’t) guidelines seems a relevant example.

With respect to biology, Jeremy’s team applies that rigor to wound-healing research involving Hox genes, a class of master regulators that pattern the body during development. He explained how HoxA3, in particular, seems tailor-made for wound repair. It repolarizes macrophages from their inflammatory “angry” state to a regenerative one, promotes vascular growth, and helps skin cells migrate to close the wound. In his words, it “hits wounds in three different ways.” The same gene that once told your embryo where to put your head or feet can later tell adult cells how to heal. I find this phenomenon somewhat magical and hope to someday learn how that works at a molecular level.

On the AI front, Jeremy’s biggest insight was about preserving scientific context. He’s using AI to capture and structure what scientists actually do in the lab so knowledge doesn’t walk out the door when people leave. Instead of asking scientists to fill endless forms, the AI reads what they write, asks clarifying questions, and turns messy notes into structured data. The AI will generate every possible graph or chart based on the data, something most scientists would rather avoid. They can then find the ones that are interesting and discard the rest. Jeremy says,

Yeah, that’s my bribe to the scientists ‘cause we enforce a little bit of structure. They have to obey the LLM when it asks for more information. So we try to compensate for that time by doing some of the grunt work that they don’t enjoy doing, like producing a bunch of charts.

Fair enough.

Jeremy wants AI not just to help scientists think faster but to help us see how it thinks so we can decide what to trust. His view is that LLMs already resemble a kind of brain: opaque, pattern-driven, capable of reasoning, but not always able to explain why. It turns out humans are no different. Jeremy shared an interesting example. You’ll have to listen to the episode for that.

Beyond the fascinating biology for me the takeaway (and in line with my own experience so far) is that the usefulness of LLMs goes way beyond answering questions or producing content. As I learned from Jeremy Utley of Stanford, using them as a teammate or collaborator is where the value lies.

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This episode is a double from my visit to the Advanced Lateral Flow Conference.

Usability is Innovation: Atomo Diagnostics

Atomo Diagnostics set out more than a decade ago to solve a surprisingly human problem in diagnostics: complexity. Founder John Kelly describes how even the best rapid tests—validated in pristine lab environments—often fail when they reach the real world, where people have no training, and shaky instructions. That gap between laboratory precision and real-world usability has huge implications for reliability, trust, and ultimately regulatory approval.

Atomo’s core insight is simple: most errors in point-of-care testing aren’t biological—they’re behavioral. The accessories people use in the field (cheap pipettes, dropper bottles, uncalibrated parts) invite mistakes, and the more steps required, the higher the failure rate. Kelly and his team approached the problem the way a designer might: observe how real users behave, then engineer around human nature instead of fighting it.

To validate their approach, they went straight to the source—literally to the community—conducting studies in Africa with low-literacy users who received only picture-based instructions. “If it needs a lot of explanation, it’s probably not obvious,” Kelly notes. The goal: build a device that is self-explanatory and self-correcting.

Their solution, the Pascal platform, integrates every accessory needed to run a test—lancet, blood collection, and buffer reagent—directly into one cartridge. Instead of multiple steps and parts, users simply collect, press, and go. Each step is interlocked to prevent mistakes; for instance, the reagent button won’t activate until blood is correctly loaded. It’s engineering that enforces proper sequence, eliminating user doubt and waste.

Kelly describes how this design delivers the right volume, in the right order, every time—removing the “what if I did it wrong?” anxiety that undermines confidence in results. It’s the difference between a reliable diagnostic and a false sense of security.

Atomo’s HIV self-test—registered with the World Health Organization and distributed across Australia, Europe, and the UK—has demonstrated greater than 99% concordance between trained and untrained users. The company also supports a blood-based pregnancy test (approved in Europe and Brazil) that detects earlier than urine tests, and they’re now developing the world’s first active syphilis test, capable of distinguishing between current and previously treated infections.

What’s equally smart is their business model flexibility. Recognizing that many manufacturers already have validated lateral flow cassettes on the market, Atomo developed a “clip-on” usability upgrade that integrates their collection and buffer technology without requiring full retooling or revalidation—a bridge between old workflows and modern design.

Beyond infectious disease, Kelly sees growth in at-home wellness and chronic condition monitoring—everything from testosterone and thyroid tests to celiac screening. The platform’s adaptability makes it attractive for home use and clinical trials alike. One example: a pharmaceutical partner using Atomo’s device to monitor liver toxicity in patients remotely, reducing clinic visits from three times a week to “only when needed.” It’s better for patients, cheaper for healthcare systems, and faster for research.

The bigger story here is that usability is innovation. Kelly’s approach turns workflow design into a driver of impact. Instead of chasing exotic chemistry, Atomo focused on reliability and trust—two things that ultimately decide whether a test makes it into people’s hands.

As diagnostics and healthcare move increasingly into the home, Atomo’s design philosophy feels ahead of its time. If the pandemic taught us anything, it’s that people can and will take responsibility for their health—if we give them tools that make sense.

Pitch Competition Finalist: EAZEBIO

I also sat down with Ying Chen, founder of EAZEBIO, one of the Innovation Award finalists. Her company’s portable strip-based diagnostic platform combines CRISPR and AI to bring precision health to everyone, especially in low-resource settings.

The Problem: Reactive Healthcare

Ying opens by explaining the fundamental flaw she sees in today’s healthcare system—it’s reactive. We wait for symptoms to become severe before acting. EAZEBIO’s mission is to shift the paradigm toward proactive, precision healthcare, emphasizing early detection and personalized intervention. Her team focuses on diseases often overlooked at the root-cause level—metabolic, autoimmune, and cardiovascular conditions.

Their aim is to bridge the gap between scientific breakthroughs and universal access, translating biomarker data into actionable health insights. As Ying puts it, “We hope proactive, personalized care can provide health equity for everyone, no matter where they live.”

Ying’s background is a blend of pediatrics, research science, and business—she holds both a PhD and an MBA. Her experience inspired her to adapt the power of CRISPR from the lab to the home.

In their prototype for sepsis detection, EAZYBIO’s system uses CRISPR to identify antimicrobial resistance genes—the genetic clues that reveal which pathogen is causing an infection. The test also detects human protein biomarkers, providing a two-layered view of infection and host response.

Here’s how it works:

• The CRISPR complex acts like a molecular “scissor,” recognizing and cutting specific DNA or RNA sequences associated with infection.

• These sequences are tagged with a cortisol-based reporter. When the CRISPR cut happens, cortisol is released.

• The released cortisol binds to split reporter proteins, generating a visible signal on a lateral flow strip.

• An AI-powered app then reads and interprets the signal into a semi-quantitative result.

This approach achieves roughly 300x signal amplification compared to conventional lateral flow assays—crucial for fast, reliable results.

Sepsis is notoriously time-sensitive; treatment delays of more than three hours can dramatically increase mortality. Ying emphasizes that EAZEBIO’s platform could enable clinicians to identify pathogens and select the correct antibiotic within one hour—a potentially life-saving improvement.

While sepsis is their initial target, the underlying platform is modular and scalable, enabling future multiplexing for 3–5 pathogens per test. Beyond acute disease, the same technology could support early cancer detection and wellness testing, making high-quality diagnostics as easy as a home pregnancy test.

Ying speaks with humility about being a finalist at ALFC, but it’s clear the recognition validates EAZEBIO’s bold vision. The conference gave her valuable exposure to peers across R&D and manufacturing, as well as insights into where diagnostics are heading over the next decade.

Her takeaway? Collaboration and accessibility matter just as much as innovation. “It’s not just technology—it’s about bringing care to everyone, whether they live in a big city or a rural village.”

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The Future of Science Marketing: AI, Upskilling, and Human Connection

I recently had a conversation with Isabel Verniers, partner at the Marketing Technology and Innovation Institute (MTI2) in Belgium, about how life science companies are adapting to rapid technological change while maintaining their scientific rigor.

One of the interesting threads we explored was the tension between scientific and commercial mindsets. Scientists are trained to seek certainty and perfection before moving forward but in a fast-moving market, that perfectionist approach can become a liability.

Isabel explained that the key is helping R&D teams become comfortable with a different kind of rigor that embraces uncertainty through assumption testing and rapid iteration. It’s about applying scientific principles differently in a commercial context.

“The innovation story is that the R&D part and the commercial part need to nicely blend and avoid that it becomes this valley of death for innovations,” Isabelle noted. The goal isn’t to turn scientists into salespeople, but to help them expand their considerable expertise into market-facing activities.

This is where the concept of “minimum viable products” often creates friction. For engineers and scientists, anything “minimal” can feel uncomfortably imperfect. The solution is to focus on assumptions and validation. By mapping out which assumptions are truly critical (requiring extensive testing) versus those that can be validated quickly, R&D teams can maintain their rigor while operating at market speed.

We also explored how AI is reshaping market research through “synthetic personas” - AI-generated archetypes built from vast datasets that can help validate ideas earlier in the development process. While some companies eagerly embrace these tools, others remain skeptical. The divide often comes down to that same comfort level with uncertainty.

What fascinates me is how AI is becoming less a replacement for human insight and more an amplifier of it. As Isabel pointed out, tasks can be automated, but human skills like critical thinking, empathy, and pattern recognition are becoming more valuable, not less. She reframes these as “power skills” rather than soft skills.

The tools get more sophisticated, but the core challenge remains: How do we help brilliant technical minds connect with the market in ways that feel authentic to their training and values?

A few key takeaways for science marketers:

1. Build “commercial acumen” through small steps that respect scientific rigor while expanding comfort with market-facing activities

2. Use structured assumption mapping to help R&D teams engage earlier without feeling they’re compromising standards

3. Think of AI as augmentation rather than automation - it’s most powerful when amplifying human insight and creativity

4. Focus on developing “power skills” that machines can’t replicate - deep listening, empathy, critical thinking, and pattern recognition

5. Create regular “drumbeat” rhythms for market engagement rather than one-off initiatives

The conversation reminded me that while tools and technologies evolve rapidly, the fundamentals of human connection remain surprisingly constant. Our job as science marketers isn’t to strip away scientific rigor - it’s to help translate it into market impact through better storytelling and engagement.

As Isabel put it, “ It’s about smart validation. It’s not about quick and dirty.” That’s something I think all of us in life science marketing can rally around.

Let’s keep exploring how we can blend scientific precision with commercial adaptability. The companies that figure this out will be the ones that not only survive but thrive in bringing breakthrough innovations to market.

And check out Isabel’s book (along with Nuno Camacho): https://thetalentadvantage.org/

What’s your experience with this balance between scientific rigor and commercial agility? How are you using new tools like AI while maintaining the human element? I’d love to hear your thoughts in the comments.

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Carter Mitchell, Chief Scientific Officer at Kemp Proteins, brings scientific rigor and an artist’s imagination to the world of protein design and production. In this episode, recorded at the Advanced Lateral Flow Conference, we explore how his company is pushing the boundaries of protein expression, quality, and analysis using tools that merge machine learning, automation, and human creativity.

A company reborn through precision and innovationKemp Proteins has deep roots in recombinant protein production, tracing back over 30 years to a company that began with insect-cell expression systems. After a rocky acquisition phase, the company was revived with renewed focus under CEO Mike Keefe, this time with a modern quality management system and new emphasis on antibodies and engineering solutions for diagnostics, therapeutics, and vaccines.

Carter, a self described protein nerd, joined around that time, bringing expertise in structural biology, protein engineering, and quantitative analytics and a mission to integrate AI into the company’s core processes.

Why insect cells still matterI knew that people used insect cells but I didn’t know why. Mitchell explains how insect cells, long used in protein production, still offer unique advantages. Unlike E. coli, insect cells can perform post-translational modifications, such as glycosylation—key for producing proteins that resemble their natural human counterparts. While mammalian systems like HEK293 have since made expression “paint-by-numbers” simple, Carter notes that insect systems still excel when complexity and authenticity matter. “It’s about having multiple expression capabilities,” he says, “so you can choose the right one for the problem at hand.”

Four questions that guide every projectCarter’s approach to solving client challenges starts with four questions:

• What is the protein?

• What information is available?

• What’s the intended use?

• What’s the scale?

From there, the team tailors both the process and the system to ensure reproducibility and regulatory readiness, whether the goal is a diagnostic reagent or a therapeutic protein. As an aside, manufacturing kilograms of protein still blows my mind.

As Carter puts it: “Regulators don’t want to see a smear on an SDS page. We think like regulators, anticipate their questions, and design out variability before it becomes a problem.”

From data lake to digital expert: ProtIQThe centerpiece of Carter’s innovation is ProtIQ, an internal expert system that combines structured data, AI models, and domain expertise into a 200–300-page report for every target protein. Initially, these reports were for experts, but Carter’s team is now transforming them into an interactive chatbot interface so anyone on the team can query the data conversationally.

“If a technician can ask, ‘What’s the isoelectric point?’ or ‘Does it have a secretory tag?’ and get an immediate answer, they’re empowered,” he says.It’s part of a broader effort to turn technicians into scientists, helping them engage more deeply with data, notice anomalies early, and contribute to process improvement.

Predicting protein liabilities before they happenUsing sequence analysis and AI-assisted visualization, Kemp Proteins can predict potential degradation sites or stability issues before production even begins. Carter’s team also models how viral variants like influenza strains might evolve over time, identifying changes in glycosylation patterns that could impact diagnostic binding. “We’re actually collaborating with the FDA on this,” he adds.

When science meets artCarter looks at protein structure like art. A lifelong painter and flamenco guitarist, he traces his fascination with structure to his mother’s art studio and his childhood encounters with crystals in Texas soil. That visual mindset drives how he thinks about molecules: “Art flattens multi-dimensional space to describe motion. That’s what we do in AI and machine learning, flattening complexity into something interpretable.”

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When it comes to biotech innovation, data and logic should drive decision-making, but sometimes stories take the wheel.

This week, I spoke to Julien Willard, a board advisor and strategist for biopharma leaders. He had written a post on LinkedIn about how biologics may be favored over small molecules when logic suggests otherwise.

Despite perceptions, small molecules still make up 73% of all FDA approvals from 2009 to 2023. They’re faster and cheaper to develop with median costs around $2.1 billion vs. $3 billion for biologics and easier to manufacture and scale. Yet, they’re increasingly overlooked.

Why? Three systemic distortions drive this imbalance:

• Regulatory bias. The Inflation Reduction Act grants 13 years of market exclusivity for biologics but only 9 years for small molecules — the so-called “pill penalty.”

• Narrative premium. Investors are captivated by stories that sound futuristic. Saying “we’re reprogramming immune cells to fight cancer” sounds far more thrilling than “we designed a molecule that blocks a kinase.”

• Flawed valuation models. Risk-adjusted NPV calculations rely heavily on peak sales assumptions and exclusivity duration, favoring high-priced biologics even when they serve smaller populations.

The result is a market that systemically favors expensive therapies and leaves affordable innovation underfunded.

Julien’s critique is a call for narrative accountability. He’s seen investor rooms go silent not when presented with data, but when shown the story of an 8-year-old patient whose tumor vanished. Emotion drives attention. “We’ve created an industry where the best storytellers get funded, not necessarily the best science.”

This bias ties to a deeper cognitive flaw, biotech’s “narcissism of outliers.” Every founder believes they’ll beat the odds. Despite historical data showing 60% of Phase I drugs fail, CEOs say, “Ours is different.” Investors, too, often prefer that hero narrative because it promises 100× returns.

So how do we rebalance the equation?

Julien points to portfolio biotechs, including firms like BridgeBio that apply modern portfolio theory to drug development. Instead of betting on a single compound, they fund multiple related programs. Ten projects with 20% success odds each yield a 90% chance of at least one success, diversifying to reduce risk. This requires different incentives: rewarding teams for portfolio success instead of single-asset hype. “Right now,” Julien says, “we’re training biotech CEOs to optimize for the biggest headline, not the best outcome.”

I feel like this shift also runs against America’s “blockbuster mindset.”As Julien notes from his European perspective, U.S. business culture celebrates the lone hero, not the collective success. That mentality seeps into funding, regulation, and storytelling alike.

We shifted gears to antibiotics, a perfect example of market failure that will require cooperation for success. Developing them makes no financial sense: they’re used sparingly to avoid resistance, and priced cheaply against generics. Yet antibiotic resistance is a national security threat. Programs like BARDA and CARB-X aim to fix this through “decoupled incentives”: guaranteed government purchases and funding for early-stage platforms. Julien sees this as a template for fixing other market failures, from rare diseases to mental health.

Could AI restore the balance? Julien argues that the best use of AI in drug development is reducing bias and noise in decision-making.Today’s biotech investing, he says, is “embarrassingly primitive”. Billion-dollar bets are made off 30-page decks and gut instinct. AI could process far more variables- molecular data, patient subsets, regulatory shifts to make more rational decisions.But we’re using it wrong: optimizing existing systems instead of reimagining them. Real innovation will come when AI enables adaptive trials that learn and evolve in real time to detect human bias rather than amplify it.I have some thoughts on how storytelling can still win: Let’s amplify the narrative that there is a better way to do things that could actually deliver better results for everyone:

• Lower risk for investors through diversified portfolios

• More accessible treatments for patients

• Better alignment between scientific progress and public health needs

Next week (Oct 13-15), I’ll be moderating a panel at the Advanced Lateral Flow Conference in La Jolla, CA. Use code LSMR25 to save 25% on your registration.

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Anis Fahandej-Sadi is building two businesses. He is the founder of TLDR Biotech, a daily newsletter that condenses life science news into a quick, skimmable format, and creator of Science 2 Sales, a service designed to help biotech companies accelerate business development. In this conversation, Anis opens up about his career journey, the lessons he’s learned in building content-driven businesses, and his perspective on where life science marketing is heading.

The Birth of TLDR Biotech

Anis started TLDR Biotech with this idea: build the thing you wish existed. With his background in sales and BD, he saw how overwhelming it was to track 10+ news sources every day just to stay informed. So he created a newsletter that captures the good, the bad, and the ugly (those are literally the categories) in biotech news, sprinkled with memes and GIFs for personality.

The format drove strong reactions. Some folks loved the humor, but hated the GIFs. However, strong reactions mean you’re creating something memorable. Strive to make a product where you can say, “It’s not for everybody.” Nevertheless, growth stalled early on, leading Anis to pause the newsletter and retool his approach.

Anis shared his struggles around finding product-market fit, admitting he initially took the wrong approach by treating it as a full-time venture too early. He had to find the product that suited him. After a strategic pause in May, he restructured the backend to create content more efficiently while maintaining quality. Now he is focused on organic growth through LinkedIn and expanding into interview content to expand his reach.

From Chemistry to Business Development

After earning a master’s in chemistry, he taught English in Korea, then pivoted into sales roles for life science companies like Cytiva and OmniaBio. Business development roles are a great fit for scientists who crave variety and human interaction, but the transition isn’t easy. There’s often little formal training, so one has to learn prospecting, discovery calls, and pipeline management on the fly. His advice for scientists considering sales: leverage LinkedIn, embrace continuous learning, and be clear on why you want to leave the lab.

Science to Sales: A New Kind of BD Support

His current venture, Science to Sales, tackles the pain of BD reps spending too much time on cold outreach instead of moving real deals forward. His team takes on prospecting, cold emails, LinkedIn outreach, and calls, so client BD teams can focus on high-value work. The approach begins with deep research into the client’s ideal customer profile, growth goals, and messaging. But the most interesting angle is pairing outbound prospecting with executive-driven LinkedIn content. The platform is evolving beyond corporate messaging to more authentic, personal storytelling.

Why LinkedIn Needs Personality

The old model of corporate-only content is dead. The future is personality-driven, with executives and BD reps building authentic, active profiles. He points to examples like Steve Harvey of Camena Biosciences and Philippe Baaske at NanoTemper as models for how thought leadership and “building in public” can humanize companies and create inbound traction. As a clear signal of where the market is going, even companies like PayPal are hiring full-time staff to manage CEO content.

Short-form video and personality-driven LinkedIn posts are no longer optional. They’re becoming essential. And while it’s not easy (Anis admits to his own hesitations about video), the payoff is familiarity that turns cold calls into warm conversations.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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PCR has been a staple of molecular biology for over 30 years. But as Yann Jouvenot, Director of Product at N6 Tec, explains, no technology is ever too mature to be reinvented. In this walk and talk interview along the Martinez (CA) shoreline, we explore how N6 Tec’s ICON PCR technology is reshaping genomics workflows: reducing artifacts, unlocking discoveries at the margins, and giving postdocs their nights back.

The Problem with Overamplification

Next-generation sequencing (NGS) has revolutionized biology, but library preparation still relies heavily on PCR. While PCR is essential for generating enough DNA to sequence, too many cycles introduce errors and distortions in the results. Abundant samples may only need a handful of cycles, but low-quality or scarce DNA, such as from liquid biopsies, requires more amplification. If one demands more cycles for all samples, that increases the risk of duplicates and bias in some.

Overamplification can suppress the detection of rare or structurally complex sequences. This means that some species or genetic variants simply disappear from view if a sample is cycled too many times.

That forces scientists into a tough choice between two suboptimal scenarios:

• Overamplify samples and accept the consequences: duplicates, errors, distorted representation.

• Babysit reactions manually: pausing machines at just the right time, tube by tube, cycle by cycle.

The ICON PCR Breakthrough

Traditional PCR machines heat an entire metal block of wells at once, forcing all reactions to follow the same program. ICON PCR takes a different approach: instead of one block, it has 96 individually controlled heating elements with sensors—effectively 96 thermocyclers in the space of a standard plate. Each well can stop cycling the moment its target threshold is reached, while others continue until they are done.

I geeked out for a bit on the engineering aspect of this story. This design required immense effort to miniaturize components and coordinate heat, power and amplification detection for each well. The result is transformative: wells act independently without affecting their neighbors. One reaction can continue as normal, while the eight “cooler neighbors” around it have finished and are held at low temperature. Yann joked about “Cooler Neighbors” sounding like the name of a new sitcom.

Where and Why It Matters

• Metagenomics: ICON PCR preserves diversity by preventing dominant species from overwhelming rare ones. In studies of soil samples, ICON PCR identified 5–10 times more species than conventional workflows.

• Liquid Biopsies & Preventive Healthcare: As sequencing capacity grows, the bottleneck shifts to library prep. ICON PCR’s AutoNorm™ feature automatically normalizes libraries, reducing the need for individual purification and quantification. This saves time, consumables, and labor while improving downstream data quality.

• Reducing Hidden Costs: Overamplification generates duplicate reads and useless data, which labs still pay to store. By reducing noise at the source, ICON PCR helps avoid paying for “garbage in the cloud.”

Looking Ahead

Yann sees ICON PCR as a key enabler for the future of liquid biopsies and preventive healthcare, where cost-effective and accurate sequencing will become routine. He also points to the broader promise of tools that let us see biological systems holistically, rather than through narrow markers. Just as early discoveries like Taq polymerase unexpectedly transformed entire industries, advances like ICON PCR may open new scientific and diagnostic horizons.

The Human Impact

Beyond cost savings, Yann emphasizes something often overlooked: the scientist’s experience. Postdocs have long wasted hours hovering over reactions, pausing machines to remove individual tubes. With ICON PCR, they can simply set a fluorescence threshold, walk away, and trust the system. That reclaimed time could mean more science or more poetry, music, and life outside the lab.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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Tino Chow’s career spans three worlds—military operations in Singapore, industrial design at Rhode Island School of Design, and entrepreneurship. That mix has shaped his work at Giant Shoulders, where he helps challenger brands in medtech, venture capital, and startups bring innovations to market.

It takes more than a great product and strong marketing. Without a sustainable business model, impact fades. For startups, the challenge is bigger. You’re new, unproven, and likely challenging the status quo. Your first hurdle isn’t your tech, it’s earning trust.

Tino’s biggest lesson after coaching 350+ founders: in addition to selling your innovation, you’re selling yourself. Investors and partners must decide if they can trust you before they ever dig into the data. That’s where the “superhero origin story” comes in. Peter Parker didn’t become Spiderman when the spider bit him. He became a superhero only after he discovered how to use his new powers for good. He found his purpose. Founders who can share that moment connect on a human level and settle what Tino calls the “lizard brain”, the audience’s instinctive fight-or-flight filter. Purpose is what will convince an investor that you’ll stick with the business when things get tough. (And they will).

It reminded me of a famous psychology study where people asked to cut in line at a copy machine. When they gave a reason — even something obvious like “because I need to make copies” — people were far more likely to let them in. The reason didn’t have to be good, it just had to exist. Now imagine what your origin story can do when it’s actually rooted in purpose. It gives people a reason to believe in you before they’ve even looked at your numbers. Superhero tip: Always use your powers for good.

He draws on his military experience to explain why creativity and discipline aren’t opposites. In elite teams, strict process frees you to improvise under pressure—just like in music, where mastery of fundamentals enables jazz improvisation. For startups, that process-driven creativity is what builds lasting brands.

Many technical founders resist storytelling, assuming data will speak for itself. But as Tino points out, ten people can look at the same numbers and draw ten conclusions. Without a clear narrative, your audience may misinterpret the story your data tells. Once founders see this, they start to value narrative control—and they often see fundraising improve.

The episode is full of practical takeaways:

• Lead with why you care, not how your tech works.

• Control the narrative so your data supports your story.

• Challenge yourself to ask “naïve” questions—they can lead to surprising insights.

• Trust-building begins the moment you open your mouth. Make it count.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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Tiffany Payne recently attended the American Society of Mass Spectrometry meeting—just two weeks after being laid off—and received a badge with "NONE" printed in giant letters under “Company.”

She could only laugh to keep from crying. It’s sometimes hard to separate our job from our identity. Tiffany turned it into a conversation starter: “I’m the CEO of None Industries—offering nothing to no one, anywhere.” Humor not only helped her deal with the sting of unemployment but also opened doors to conversations with peers at the event who had faced the same experience. Her badge was now a symbol of honesty and resilience.

Here is Tiffany’s perspective: Layoffs are hard, but the fear of being laid off can be even worse. Once you’re on the other side of it, you have control again—you can decide what you value, what work means, and how you want to show up in the world. For Tiffany, this led to founding Veris Marketing, rooted in clarity about what marketing really is.

Defining Marketing

Tiffany’s definition of marketing is far from the “Mad Men” clichés of catchy slogans and glossy brochures.

“Marketing isn’t about convincing people to buy something they don’t need. It’s about understanding their real problems and matching them with the right solution.”

She shared a story about working with a lab that developed a faster drug test. Instead of focusing on technical specs, she framed the story around the human stakes: the child protective services administrator choosing between a lab that returns results in weeks versus one that can respond in days. If you are a child in a home with someone abusing drugs, that matters. Good marketing starts with empathy and storytelling.

On Being an Upstander

Tiffany is also vocal about values. She celebrates companies that stay committed to diversity, equity, and inclusion (DEI), even when it’s not mandated or trendy, calling them “upstanders.” Inspired by her daughter’s experience at San Francisco Pride, she encourages companies to lead with integrity, not fear.

“If you drop your DEI policy when the pressure is off, what does that say about what you really believe?”

I tend to agree. You can choose to have a policy or not, but the companies that dropped their initiatives as soon as it became convenient revealed something about themselves.

Advice for Job Seekers

Tiffany has heard some people advising some job seekers to “hide” their age, gender, or identity on resumes. While it’s certainly understandable in the current environment, she says:

“If you have to hide who you are to get the job, is that the place you really want to work?”

In addition, do we want to give more power to the companies that are doing that?

I appreciate Tiffany’s vision for the world. She is passionate about building alternative paths—small, connected businesses that can thrive without relying on corporate gatekeepers.

“Imagine creating a company where you get to pick all your coworkers. That’s the dream.”

If you or someone you know has been dealing with the struggles of unemployment, this episode is worth listening to and sharing.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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When you're selling something truly new, you're not just fighting for market share – you're fighting to create a market that doesn't exist yet. A big part of that battle is figuring out your sales process. Chris Morrison from ViaVerus and Brian Jamieson from Diagnostic Biochips shared their experience on this week’s episode.

Chris Morrison introduced the "innovation death spiral." It goes like this: A startup gets early validation from one big customer. They get excited (who wouldn’t?) and build their entire go-to-market strategy around that single success. Then... silence. The market doesn't respond as expected, so they double down on their approach, burning through resources until there's nothing left.

This pattern is particularly dangerous because that first success feels so validating. As Chris put it, finding one customer isn't a repeatable process, which is what is needed for long-term success.

Diagnostic Biochips provides an example of navigating these treacherous waters. They've developed technology that can read the "ones and zeros" of brain activity. If you want to learn more about the science, make sure you listen to the full recording. It's cool stuff that could revolutionize how we understand and treat conditions like Alzheimer's, schizophrenia, and epilepsy.

If you aren’t subscribed, now might be a good time…

But here's the catch: When you're that innovative, your biggest challenge isn't competition – it's teaching the market what's even possible.

The Discovery-Based Sales Process

Traditional sales processes are execution-based: You have historical data, known customer needs, and established patterns to follow. But what do you do when none of that exists?

Morrison and Jamieson's approach reveals a framework that any tech startup can learn from:

Instead of assuming they knew their market, they tested their initial assumption about big pharma being their primary customer. When that didn't pan out, they pivoted quickly rather than forcing a fit.

They discovered their sweet spot wasn't with big pharma or pure academic research, but with translational research organizations – the groups that bridge the gap between basic science and practical applications.

Rather than trying to educate the market about their technology's potential, they focused on identifying existing problems their technology could solve today.

One customer isn't validation – it's an anomaly. And two customers are just two different cases. According to Morrison, for complex B2B sales like Diagnostic Biochips, you need 10-20 customers before you can start seeing genuine patterns emerge in your sales process.

Developing a repeatable sales process isn't a single task – it's a series of staged discoveries:

• Market Entry Point: Identifying where your technology connects with immediate, funded problems

• Messaging: Finding the language that resonates with early adopters

• Lead Generation: Developing tactics that consistently bring qualified prospects

• Sales Process: Building the steps that convert interest into purchase

• Customer Success: Creating the bridge from purchase to satisfied customer

You can't skip steps. You need to complete each stage before moving to the next.

Perhaps the most interesting tension revealed in our conversation was what Brian Jamieson called "the funny combination between urgency and patience." Revolutionary technology creates natural urgency – you're sitting on something that could change the world. But rushing the process of finding your market fit can kill even the most promising innovation.

I actually thought there was an opportunity to educate the market on the gap between patch-clamp studies and animal behavior. Chris emphasized that startups don't have the luxury of educating markets. Instead, find where your innovation solves an existing, recognized problem.

The goal is to find messaging that makes customers pull you toward their problems rather than pushing your solution onto them.

As Chris noted, what typically takes three years can be compressed to 18 months with the right approach – but it can't be compressed to three months, no matter how hard you push.

Diagnostic Biochips' technology could fundamentally change how we understand and treat brain disorders. But that potential can only be realized if they successfully navigate the path to market. I often wonder how many amazing technologies end up on the scrap heap, not because of science but because of poor timing or strategy.

Launching truly disruptive technology is "probably one of, if not the hardest thing to do in business." But with a disciplined approach to discovering your repeatable sales process, it's not impossible. It's a matter of having the wisdom to be patient and the drive to stay urgent while you figure it out.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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When Joachim Eeckhout says he started small, he’s not kidding. He and a friend began curating biotech news from a Paris dorm room, eventually launching LaBiotech.eu, a media brand that became a trusted voice in European biotech. What caught my attention is how they learned the landscape: by biking across France with a camera, interviewing CEOs, and turning it into a documentary. That’s how they built credibility and a network from scratch. As a fan of cycling, science and documentary filmmaking, that sounds like a dream job to me. Or me 40 years ago…

That kind of storytelling, doing something unexpected and human, creates lasting connections. In our attention economy, Joachim’s approach stands out. He now runs The Science Marketer, helping life science companies do smarter marketing with a voice and personality.

Content doesn’t need to be flashy. But it does need to be authentic, consistent, and personal. Joachim suggests starting with what you would actually want to see yourself. That’s how you find your edge or your angle.

If you aren’t subscribed, now might be a good time…

We dug into the mechanics of content-led growth: how podcasts and newsletters aren’t just media channels—they’re trust-building engines. When someone hears your voice regularly or reads your thoughts in their inbox each week, you go from being a company name to a known entity. Familiarity builds comfort, and comfort builds trust. And unlike a sales call, this kind of content scales. It creates what Joachim calls “a simple funnel”. You share your perspective, your expertise, and a bit of your personality, and over time, people move closer to working with you.

Funnels have gotten a bad name lately. Nobody wants to feel like a lead. So how do you build one without turning people off? The goal is to show up with something valuable, consistently, and let the content do the work. This is especially important for founders and CEOs. The ones who are willing to show up, not just to talk about the science, but to let people see who they are, how they think, and what kind of culture they’re building, stand out. Customers don’t just pick a service; they pick a team. The value of good content is letting them get to know yours without pressure.

Joachim shares my love of repurposing. Too many companies make a great webinar, record a brilliant interview, or write a strong article and it’s one and done. They move on. But that single piece of content can become the seed for a dozen others. Joachim talked about how he helps clients turn webinars into PDFs, transcripts into blog posts, clips into LinkedIn videos, even media pitches that include actual footage of someone making their point, instead of a generic quote in a press release.

We both agree that posting content more than once on the same platform is a mental hurdle more than a real one. Most people won’t see your post the first time. And if they do, they probably won’t remember it. So why not reshare it? Especially if it was good. Posting the same content again weeks or months later isn’t lazy. It’s efficient and effective.

Joachim brought up Plasmidsaurus, a company that markets seriously essential biotech services by being obsessed with dinosaurs. It works because it’s memorable, and it doesn’t compromise the quality of the science.

The whole conversation was a reminder that in biotech, seriousness doesn’t have to mean boring. Passion, creativity, and a little risk-taking can go a long way in earning trust and growing your brand.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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Jin Kim is the founder and CEO of Miracle, a company helping biotech teams accelerate clinical trials by automating operational insights. Trials are a data problem and Miracle solves it by unifying siloed systems into one real-time dashboard. That has helped some clients finish trials 3–4 months ahead of schedule.

Many trial operations still rely heavily on Excel. It’s easy, familiar, and free. But once you enter Phase 2 or 3 with CROs, labs, and recruitment vendors in play, things break down fast. Different systems name fields inconsistently (think “data randomization” vs. “randomized data”), and humans can understand that but systems can’t. That’s where the manual labor comes in—pulling data from multiple platforms, cleaning it up, and trying to build reports.

Miracle automates all of that. The system integrates with common clinical tools via API or data exports, normalizes disparate formats, and delivers insights in real time. That means no more waiting for a report on Wednesday to catch an issue from last Friday. Users can respond as problems arise.

We talked about the hype around AI, especially at recent industry conferences like AWS Life Sciences. Jin’s take is that AI is only as good as the data it has access to. And in clinical trials, that data is usually siloed or messy. So before deploying AI, companies need a solid data infrastructure. That’s what Miracle provides: a clean, unified layer that can feed downstream AI use cases.

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Jin stressed that he doesn’t lead with AI in conversations—he starts with the problem. What do clinical operations teams need today? Miracle's customers are typically not engineers. They're researchers, clinicians, and trial managers. That’s why the platform is tailored to non-technical users, with role-specific dashboards and workflows for everyone from the CEO to a clinical operations lead checking in eight times a day. Jin has made sure the tool meets people where they are, surfacing the right metrics based on their goals—whether that’s daily site activity or long-term enrollment projections.

I think it's so important to get down into how is the director of clinical operations using it versus the actual people on the clinical operations team versus even, you know, calling it leadership, how the chief medical officer's using it might be different from how the CEO's using it.

If you’re running a biotech trial and wondering whether you have a data problem, Jin suggests starting with a simple question: “Are we going to finish our study on time?” If that answer isn’t crystal clear, you’ve got work to do. And for most teams, enrollment is the biggest risk factor. Miracle helps teams back-calculate from their timelines using data they already have: how many patients are being screened, how many pass, how many are randomized, and how many drop out.

While Miracle doesn’t handle patient recruitment directly, it can track the entire recruitment funnel from ad spend on Facebook or Google, through study website visits, to completed screenings. That makes it easier to assess the ROI of digital outreach and reallocate spend based on what’s actually converting.

Jin started Miracle while still in grad school, building on his experience in enterprise sales and his background in computer science from MIT. He saw firsthand how data bottlenecks crippled big pharma, and he realized that smaller, resource-strapped biotechs needed a better way.

It just occurred to me as I write this, weeks after I first met Jin, that some companies might run out of money in the middle of a trial, which seems a tragedy for the participants, regardless of whether a product was headed for approval or not. In any case, helping more trials get across the finish line is a worthy cause. Whatever any of us in life science can do to help that happen is a good thing.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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Nick Clare is a co-founder of Succession Bio and co-host of the SalesDNA podcast. I recently spoke to Harrison Wade, the other co-founder here. Nick's journey into sales wasn't a planned career move. It was the result of "fear and desperation," as he put it.

Nick was working as a scientist in the lab when his wife was 14 weeks pregnant with their third child. 20 days before Christmas, he was made redundant. Ouch. During his job search, he interviewed with a company where the CEO and CBO offered him two positions - field application scientist or lab manager. Nick, thinking about his growing family and financial needs, asked the most direct question possible: "Which one pays more?" The CBO immediately claimed him for the sales side, recognizing the money motivation that's so crucial in sales.

Nick was honest about his initial resistance. He spent the first six months looking for another job because he was a scientist, not a salesperson. But eventually he realized he wasn’t finding anything he wanted because he actually loved what he was doing. Now he runs a company that teaches sales, selling sales itself. Men make plans and the universe laughs…

I asked about the distinction between sales and business development, something it seems everyone describes differently. Nick's definition is pretty simple: sales is about selling something that already exists - a widget, service, or software - while BD is about selling partnerships to develop something new together. CROs are kind of a hybrid. He pointed out that BD professionals often lag behind in their processes compared to traditional salespeople. They rely heavily on networking but don't utilize the same systematic lead generation and pipeline management that sales teams do.

That brought us into a discussion of cold email (Yikes), but Nick and Harrison's LinkedIn posts have been helping me get over that fear. Nick's perspective is liberating (and reflects the truth): he challenged me to think of a single email from the past two weeks that annoyed me enough to actually do something about it. I couldn't. His point was we only remember emails that resonate positively with us. Everything else just gets deleted and forgotten. We're so worried about negative consequences that we miss the fact that most people won't even notice our outreach, and when they do, it's usually positive.

Nick has a "10 a day" rule from when he managed sales teams - spend five minutes researching each person and reach out to 10 people daily. That's less than an hour of work that results in 200 outreaches per month. That math should be sufficient when you think about pipeline impact.

We have to talk about how Nick uses Notebook LM for sales research. I'm a huge fan of this Google AI tool myself, and Nick's applications are brilliant. He uploads company websites and generates mind maps to visualize all their products and propositions, perfect for visual learners like him, preparing for discovery calls. Even better, he creates AI-generated podcasts from the research materials that he can listen to while driving or multitasking. The fact that you can now interrupt these AI podcasts to ask questions makes it even more powerful.

I shared how I've been using Notebook LM with 10 years of podcast transcripts, creating a searchable knowledge base where people can ask questions about life science marketing and get specific insights from past guests. Nick's using it to help his daughters with homework, having them listen to AI-generated podcasts about complex topics before tackling assignments.

If you are AI resistant, I think you have to recognize what’s coming, whether you like it or not. You can be part of your own plan or part of someone else’s. Quick aside: When I was a kid, my dad had a gag where he had a telephone handset (with a spiral cord pinned inside his jacket. He had a ringer in his pocket that sounded like a phone. He’d pull out the handset and say, “It’s for you.”

What used to be a laugh is now an indispensable reality. Fast forward and this morning I’m using advanced voice mode to have a conversation with ChatGPT about content creation while I’m on a walk. You get the picture.

Nick talks to ChatGPT while driving to customer calls, essentially having a conversation with an AI teammate about strategy and approach. He even created a custom GPT called "Pocket Nick Nick" loaded with his company's public data, so he could access specific information during customer calls in real-time.

What I appreciated most was his practical, no-nonsense approach to both sales and AI. He's not afraid to be direct about money (which served him well in that initial interview), he's systematic about prospecting, and he's embraced AI as a genuine productivity multiplier rather than viewing it as a threat. I’m not making or following predictions about AI making us dumber or smarter or taking our jobs. The only thing I’m sure of is that people will use it.

Nick's story also highlights something I see frequently in our industry - scientists who discover they love the business side of science. There's something powerful about being able to share science broadly rather than going deep into one narrow research area. Nick used a great analogy about being on a boat viewing the horizon versus investigating the Mariana Trench.

This conversation energized me around several things: being more systematic about outreach (those 10 people per day), using AI more creatively in my work, and thinking about BD versus sales more clearly. Nick's journey from reluctant scientist to sales leader shows that sometimes the best career moves come from necessity rather than planning, and that embracing change - even when it feels uncomfortable - can lead to unexpected fulfillment.

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I had a fantastic conversation with Abdul Rastagar, founder of Serona Marketing, about his mission to cut the b**t out of marketing. Abdul runs both a podcast and newsletter with that exact title. It’s pretty clear he feels strongly about this. I thought it would be fun to find out what’s been bugging him lately. I was not disappointed.

Abdul's beef is that we're stuck using outdated marketing processes from a decade ago that don't match how customers buy today. There’s too much friction. Customers want to see pricing, but we force them through multiple calls with SDRs and demos before revealing whether they're even in the right ballpark. Meanwhile, they're already sharing pricing information in peer communities and researching vendors thoroughly before ever contacting sales. I’ll write more about this soon, but it seems like a missed opportunity to build some trust.

While Amazon has systematically removed friction at every step, B2B companies have done the opposite - we've added barriers and complexity. I pushed back a bit about competitive concerns, but he made the case that if you're worried about competitors seeing your pricing, they'll find out anyway through those peer networks. More importantly, if you hide pricing while competitors don't, you're not even getting into the conversation. Better to reduce friction and actually engage with prospects than lose them before they ever reach out.

One of his most painful observations is that marketing is the only function where everyone else in the company tells you how to do your job. I laughed at his story about the CEO's spouse not liking the logo colors, but it's not really funny - it's a genuine challenge marketers face daily. Operations, finance, sales, and even board members all have opinions about marketing decisions they'd never dream of weighing in on for other departments. Try telling the CFO about where they should invest all that cash you generated!

Here is how he suggests you handle those suggestions: figure out which ones might have merit, prioritize them appropriately, and learn to say no constructively while maintaining collaborative relationships.

We briefly discussed LinkedIn’s own flavor of BS: those trade show announcement posts. They're mostly checkbox exercises - the real value comes from personalized outreach using the event as a conversation starter.

Given all of this, I asked about being more creative and effective. And I loved his answer. Stop selling your product and start selling your knowledge. Be generous with what you know. Don't focus on what your tool does; focus on sharing your perspective on industry challenges and different approaches.

This philosophy of thought leadership before product pitching makes perfect sense, especially in life sciences where people are always eager to learn. Scientists want to understand the "why" behind solutions, not just the "what." When you establish credibility through knowledge sharing, product conversations happen naturally.

Abdul shared an example: his client published an industry article, and at a recent conference, the CEO overheard two people discussing that very article. He joined the conversation, revealed he was the author, and one of those people turned out to be an ideal customer prospect. That's how thought leadership creates real business opportunities.

On the other side of that, I asked about the common CEO dilemma: wanting to be thought leaders but not wanting to be the face of their companies. Abdul acknowledged the risk - invest in building someone into a thought leader and they might leave. People do move around. But you're better off benefiting from that voice while you have it than getting no benefit at all.

Instead of getting caught up in the latest marketing technology or tactic, Abdul's focus on fundamentals understanding your customer's buying process, being transparent, and sharing knowledge generously feels more authentic and is likely more effective.

These cold conversations have been a blast and educational for me beyond the content. I have more lined up. If you aren’t subscribed, now might be a good time…

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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When we talk about gene expression, most of the focus is on DNA and RNA sequences, but there’s a lesser-known, more subtle layer of regulation: RNA modifications. In this episode, I spoke with Gudrun Stengel, CEO and co-founder of Alida Biosciences, to explore how this fine-tuning mechanism affects everything from cell differentiation to cancer survival, and how her company is helping to decode it.

RNA Modifications: A Hidden Code Within the Code

Gudrun kicked things off by explaining how RNA modifications influence gene expression at multiple levels: splicing, translation initiation, intracellular trafficking and mRNA half life. These changes enable the cell to switch functions on or off quickly, presumably in response to some cue or cascade of events.

The most studied RNA modification is m6A. Its effects depend heavily on the context in which it occurs, acting through “reader” proteins like YTH family members. m6A plays crucial roles in processes like stem cell differentiation and cancer survival. For instance, without m6A, pluripotent stem cells fail to differentiate. On the other end of the spectrum, overexpression of m6A-related enzymes in cancer can help tumor cells evade programmed cell death.

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The Tools Are Just Now Catching Up to the Biology

One of the big hurdles in studying RNA modifications has been detection. These modifications occur at low frequencies, sometimes affecting just 0.1% of a given base, and lack a "reference genome" to compare against. Traditional approaches using mass spectrometry or antibody pull-downs have significant limitations in resolution and specificity.

That’s where Alida Biosciences’ EpiPlex platform comes in. It allows multi-target detection of RNA modifications with a sequencing-based approach. Their method attaches barcodes to RNA segments where modifications occur, enabling quantification without relying on antibodies.

Unlike academic tools built for discovery, AlidaBio’s platform is designed to be robust and scalable, bringing more reliability and speed to RNA modification analysis. It offers about 100–200 base pair resolution and focuses on three key modifications: m6A, pseudouridine, and inosine.

Why It Matters: From Diagnostics to Drug Discovery

There a several potential applications. For diagnostics, RNA modification patterns could help differentiate between disease states that look nearly identical via RNA-seq alone. Gudrun mentioned studies in glioblastoma where RNA modification profiles enabled more accurate cancer staging.

RNA modifications could also guide drug development. For example, Storm Therapeutics is already testing METTL3 inhibitors in leukemia. There’s also growing interest in plant engineering, and tuning the epi-transcriptome could help increase crop yields and stress resistance.

Alida Biosciences’ Vision: More Than a Tools Company

Gudrun sees AlidaBio not just as a platform company but as a partner in solving real-world problems. Long-term, she hopes to expand into clinical applications and potentially therapeutics, either by developing companion diagnostics or helping modulate modification states for therapeutic benefit.

I’ve been studying biology for 45 years. This episode gives me a renewed appreciation for the complexity of biological systems. Every time it seems we have it figured out, there is a new level of regulation to be discovered. It reminds me of when we thought atoms were just protons, neutrons and electrons. Then we discovered quarks.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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I had a great time speaking with Meg Schlabs, co-founder and creative director at Wizardly. While it may be difficult for early-stage life science companies to think about branding, Meg makes a clear case for why it matters, even before you go to market, especially when you are trying to raise capital and recruit talent.

Meg’s LinkedIn profile mentions that she likes books and cheesy videos. So before we got into the branding discussion, we took a short detour. (This was our first ever conversation.) I mentioned that I had asked ChatGPT to make a few recommendations (three fiction and three non-fiction) based on what it knows about me. They could not be about life science. The jury is still out, but if you want to know what it suggested, the answers are at the bottom of this post.

Then we got into the heart of it:Why should biotech startups think about branding early?Because it validates your science. When a company tells a cohesive, compelling story from the start, it’s easier for investors to get on board, for scientists to rally around a mission, and for future hires to say “yes.” That story, she argues, should express why the company needs to exist right now.

…let's lay down, from the top down, from the CEO all the way, trickling all the way through the company, let's lay down who we are, why we exist, who we exist for, where we're going in five years, where we're going in 10 years, and let's memorize this story as a company so that we can make critical visual decisions or branding decisions that when they're validated or tested by an outside audience, they actually have some legs underneath them.

We talked about her approach to uncovering that story. Wizardly’s process often starts with what might sound like a ridiculously simple question:“What does your company do?”It’s the kind of question that seems obvious until you realize no two people on the team are answering it the same way. Meg’s workshops build consensus and create a shared foundation before any logos or taglines come to life.

Another thing that stood out to me was how she described designing for the long term. Unlike SaaS companies that can iterate daily, biotech teams are often playing a 10-year game. That means the brand you launch with has to scale with consistency and flexibility as you grow. This is an idea I had never heard before. Meg emphasized designing not just for today’s website or pitch deck, but for the brand library you’ll need 18 months from now.

We also covered:

• How design choices (like color) are driven by a 3-pronged strategy: story, user psychology, and competitor positioning

• Why Figma is a game-changer for collaborative branding in biotech teams

• The risk of too much feedback, and how a single point of contact can keep branding projects on track

• Why consistency doesn’t mean rigidity—and how great brands evolve

Finally, here is an idea I loved: rather than gatekeeping the assets, give your clients the tools and training to extend their brand. Her team hands over not just files, but Loom tutorials and templates in Figma, so internal teams can stay on-brand long after the agency engagement ends.

Longtime listeners know the metric: how much do my cheeks hurt from smiling because of all the great insights? 5/5 Definitely recommend.

These cold conversations have been a blast and educational for me beyond the content. I have more lined up. If you aren’t subscribed, now might be a good time…

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

Books ChatGPT recommended for me. As I said, the jury is still out on these. Non-fiction seems more promising.

Fiction The Overstory, The Master and Margarita, Stoner

Non-fiction Antifragile, Amusing Ourselves to Death, The Art of Noticing

Wild Card The Peregrine by J.A. Baker

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This webinar is also available for listening:

In this live conversation, I sat down with two of my friends, both smart thinkers in life science, Elizabeth Chabe (CEO of High Touch Group) and Hamid Ghanadan (Founder of the Linus Group) to talk about disruptions in science from funding cuts and possibly tariffs.

The goal of this session was to make sense of what’s happening and offer perspective on how to move forward.

We opened by acknowledging the massive wave of uncertainty hitting our industry: $1.8B slashed from the NIH budget, talent flowing overseas, and companies unsure where or how to invest. Elizabeth laid out how these cuts don’t just stall progress now, but also limit the breakthroughs we’d expect 10 or 20 years from now. As a result, countries like France, Germany, and China are welcoming U.S. researchers with open arms—and open budgets.

Hamid added critical data points from his recent reports, showing how fear and indecision are paralyzing budgets across sectors. Companies are scaling back because they don’t know what assumptions to trust. That freeze is what’s truly dangerous.

What to do?

We explored what smart companies are doing right now—rethinking commercial strategy, investing in pilot programs that break the old marketing-sales divide, and leaning into thought leadership that actually connects. One of my favorite moments was when Hamid said, “The best way to see what the future looks like is to run small experiments today.”

We also talked about empathy, not as a soft skill, but as a competitive advantage. Many scientists and labs are hurting. Those who can build trust and show up with value (not just offers) are the ones who’ll be remembered when budgets return. Elizabeth highlighted the fact that brands are built in a downturn. Now is the time to create content that solves problems.

Another standout section was our discussion on AI. Both agreed that while AI opens up massive potential, it also exposes new risks—limited infrastructure, hidden costs, and overdependence on tools that few companies actually own.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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Every day, roughly 10 people in the U.S. die from SUDEP (Sudden Unexpected Death in Epilepsy), most found face down in bed. Soterya is changing that with an ML-powered bed that detects sleep position and can gently reposition a person without waking them.

I spoke with Norman Wen about how ML, robotics, and thoughtful design are merging to improve sleep health, and potentially save lives. Norman is the CEO of Soterya, a company building what you might call a smart bed. Their bed, Korus, is built around a basic but life-saving idea: don’t let people sleep face down. That insight led to a system that can detect and reposition sleepers safely without relying on intrusive cameras and without waking them.

Embedded pressure sensors provide a real-time pressure map, which feeds into a machine learning algorithm trained to recognize body positions. While image-based AI has the benefit of massive open datasets, Norman’s team is tackling the harder path: building their own data internally to preserve privacy and stay within the mattress itself.

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The actuation system comprises equally clever engineering. Pneumatic cells, each one both a sensor and a mover, create a modular surface that adjusts to the sleeper’s position. The system is being designed to reposition users without waking them, which means it needs to recognize both position AND sleep state. And all of this runs on the device, not the cloud, for reliability in critical situations like seizure prevention.

Beyond SUDEP, Norman sees a much broader opportunity: addressing sleep apnea, gastric reflux, chronic back pain, and even maternal health in pregnancy. Sleep position can affect all of these, and for people who are bedridden or aging with multiple conditions, this kind of intervention could be significant.

Right now, Soterya is pursuing a go-to-market path that starts with health-conscious consumers and moves toward regulated medical devices. That approach gives them room to develop, collect data, and refine the product while still making a difference. For people who can’t fall asleep wearing a device, a bed that just does the work passively may be a better answer.

At a time when we are becoming more aware of the importance of good sleep, this is one path to improvement that ultimately may have a huge impact.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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Recently, I’ve enjoyed interviewing people I have never spoken to before. Harrison Waid, the co-founder of Succession, is one of those. Shout out to Teddy Lin for connecting us. I took this as an opportunity to learn about Harrison and his business as well as a personal challenge to interview someone “cold”. OK, I did some research, so maybe “room temperature”.

First of course, I needed him to explain Succession, co-founded with Nick Clare (who I hope to have on another time). They noticed life science companies struggling to translate great technology into successful market entry and sales growth. Succession was founded to address this, offering specialized services exclusively for life science sales teams – everything from lead generation and sales training to recruitment and optimizing internal systems like CRMs with automation and AI. Harrison called it a "vertical service company" for life science sales.

The idea for it wasn't a sudden flash of insight but more of a "slow burn." While at Synthego and after moving to the UK, he initially thought about general consulting. He quickly found that clients wanted concrete outcomes, not just advice. The real traction came when they packaged their expertise into specific, deliverable-focused services – that’s when things really took off.

I’m always interested in people who come from other backgrounds outside of life science. He made his start was in software sales. A friend brought him into Synthego, a CRISPR company, initially for consulting. At that point, his knowledge of biology was that "the mitochondria is the powerhouse of the cell." But he was excited by the potential of the technology. He immersed himself in learning the science and business of biotech, leveraging online resources and learning from his colleagues. Once again, curiosity = superpower! Asking "dumb questions" is an underrated skill. Those outside perspectives can challenge assumptions and benefit both the business and the individual willing to learn.

I'd prepped some questions, but the morning of our interview, I stumbled upon a recent LinkedIn post Harrison made contrasting "old" and "new" ways in biotech sales. I saw some insightful comments from people we both respect, like Owen Swift. I knew this would be worth digging into.

Harrison framed the "new way" around leveraging technology to move beyond inefficient models like (old way) simply scaling headcount. I picked a few points from his post for discussion:

Small, High-Output Teams + RevOps/Content/Automation: He explained how technology now allows high-performing reps to be supported by robust systems (managed by Revenue Operations) that automate much of the prospecting and research previously done by separate inside sales roles. This frees up skilled sellers to focus on closing.

AI for Intent & Sequencing: We discussed how AI can go beyond basic alerts to analyze market signals, identify key opportunities, score leads, and even assist with outreach, providing reps with powerful, timely intelligence.

Content & Personal Brand for Demand Gen: I strongly agree with this one. There is a compelling case for reps building their personal brands on platforms like LinkedIn. He argued, quite correctly in my view, that authentic content from individuals resonates far more than corporate posts and that companies restricting this are missing a huge opportunity.

Video Outreach: I shared my own recent positive experience with video messaging, having secured a meeting from one just last week. Harrison pointed out how video cuts through the noise, humanizes interactions, and is effective for both prospecting and follow-ups. We agreed authenticity is more important than perfection.

The Best Reps Get the Best Opportunities: This one may be controversial, as it goes against the idea of pure "fairness" in lead distribution. He would argue that for maximizing company revenue, it makes sense to give the highest potential leads to the reps most likely to convert them. He acknowledged territory assignments are inherently unfair anyway and suggested lower performers could develop on less critical leads. This leads to discussions about efficiency, long-term strategy, and even healthy team turnover.

Compensation plans inevitably drive behavior and can always be gamed, so no system is perfect. It comes down to your goal and again, long-term strategy. As someone who hasn’t formally been in sales, I can see the attraction to developing skills on low risk opportunities.

If these ideas got you thinking, you might check out the SalesDNA Podcast, Hosted by Harrison and Nick.

These cold conversations have been a blast and educational for me beyond the content. I have more lined up. If you aren’t subscribed, now might be a good time…

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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Large language models (LLMs) seem to dominate the discussions, at least in my world lately. In this episode and the next, we’re diving into AI on a different scale. In this episode, I spoke with Josh Hinckley, co-founder and CEO of Bioqore. AI is being applied to the way we make things — in this case, food. Josh’s background in materials chemistry has led him to focus on process optimization for alternative proteins, where the challenges in the market are high: you have to make large quantities efficiently, the price point has to be realistic for consumers and on top of all that, the end product has to meet all your sensory requirements. A fancy way of saying it has to smell, taste and feel right.

When you're making pharmaceuticals, small yields are fine because the value per milligram gram is high. But for food, you need much larger quantities. People aren’t going to pay $100 for a gallon of milk. So alternative food companies are under pressure to optimize production at a scale biotech typically doesn't deal with.

The example he gave was alternative milk. It’s real milk, but produced without cows. It looks, tastes, and behaves exactly like traditional milk but doesn’t require pasteurization. But moving from liquid milk to structured products like meat is a much bigger challenge, because the texture and mouthfeel matter just as much as the composition. Food isn’t just chemistry, there is an emotional component to eating (memories, adventure…).

That’s where Bioqore’s AI platform, Voyager, comes in. In contrast to traditional design of experiments (DOE) methods that can be rigid, and sometimes inefficient, Voyager uses active learning, a machine learning approach that continuously refines its model based on outcomes. Instead of running 20 experiments at every stage, you might only need five targeted ones to find your optimal process. It's smarter, faster, and cheaper.

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Josh broke down Voyager’s process into three stages: sampling, exploration, and exploitation. First, it samples combinations of variables broadly to get a feel for the landscape. Then it explores areas where the outputs look most promising more deeply. Finally, once the model understands the system, it exploits that knowledge to hone in on the ideal process.

What stood out to me was how machine learning is enabling discoveries humans would likely dismiss. Biology often behaves in unpredictable ways. Human beings are biased by our own limited experience and expectations or mental models of how things should work. Machines don’t suffer from those attachments. They can explore n-dimensional spaces we can’t even visualize and show us possibilities we wouldn’t have believed without the data in front of us. AI is allowing us to see things where we never would have looked.

Josh and his team are close to a major leap forward: they’re finalizing investment rounds to support not only their food optimization platform but also rapid therapeutic development, including more efficient insulin production. In just six weeks since we first spoke, Bioqore’s trajectory has accelerated dramatically.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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When I invited Max Gilbert on the podcast, I suspected the conversation might go beyond sales tactics. Max is the founder of Tiferet Consulting, but he’s also a sourdough baker, amateur rabbi, armchair philosopher, and like me, a pretty bad golfer. Our conversation covered everything from startup struggles to spiritual identity and the joys of sourdough.

Helping Scientists Become Salespeople

Max works with founders selling into biotech or pharma that want to make sure their first sales hire works out. Spoiler: He has seen it go bad which gave him the idea.

One can imagine a founder with a science or engineering background thinking, “I’m not a sales person. I need to offload this to someone who can make calls, pound the pavement and hit a number.”

The early-stage sales role is fundamentally different. It’s about iteration and discovery, not just execution. So instead of trying to fit a traditional salesperson into a startup that was still finding its feet, Max found more success coaching fermentation scientists and bioprocess engineers to do the selling. They could speak their customers’ language and earn trust through technical credibility. Max helps them build the confidence and process to go with it.

Here is some good, if scary, news for those folks. As a scientist, you have skills that are useful in sales. Once again, your curiosity is a superpower. Sales, according to Max, is asking questions, looking at a problem from a lot of angles and figuring out how it might be solved. The challenge, as I see it, is that having developed a product or service, a founder might feel they have the answer in hand and they can’t wait to tell everyone who might be interested. They end up filling the silence with features and benefits.

Sales as a Scientific Process

Maybe a better approach is to think about your product or service as a hypothesis. And every sales call tests that hypothesis by asking more questions of the prospect about what they do. What’s this person struggling with? How do they think about their problems? When you listen that way, your product becomes a natural extension of the conversation. Then you can frame your product as a possible solution and let the prospect decide if they want to have another call to talk about it some more.

The process becomes a collaborative journey. Are we solving the right problem? Do we even understand the problem? Can we help? And if not, Max coaches his clients to say so and maybe even refer that prospect to someone who can.

Why Scientists Should Own the Sales Process Early

On top of all that, for the first few sales, only the founder can have the context to ask all the right questions as well as see how the answers might help refine the product or its positioning.

We like to say sales is about relationships, but that can mislead people. It’s not about charm or charisma. For early-stage companies, it’s about using structured conversations to gather data and test hypotheses. Max frames the process like an experiment: design, build, test, learn.

When you stop seeing sales as persuasion and start seeing it as discovery and iteration, it becomes a lot more accessible, especially if you’ve been trained to think that way already.

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Sales is a rollercoaster. Some calls go nowhere. Some start off promising and then you get ghosted. Founders have to keep showing up with curiosity and resilience even when they don’t feel like it. That’s where Max’s coaching comes in. (There is a theme here.)

Max’s secret sauce is that he lived the resistance. Like many, he didn’t start out wanting to be a salesperson. In fact, when a mentor suggested he lead sales, his first reaction was visceral rejection. (I laughed out loud as Max mimicked throwing up.) But going through that discomfort gave him a blueprint for coaching others through it. It’s the classic hero’s journey.

He told me his coaching isn’t about copying someone else’s process. It’s about helping each founder build their own. Picking the right structure, sticking to it, and having the mindset to carry it through especially when motivation disappears. More on that in a minute.

Coaching the Whole Person

I asked Max about this quote on his website: “When we ground ourselves in the identity that transcends our own contradictions, we’re tapping into our authentic self.”

Max named his consulting business Tiferet, concept of harmonizing seemingly opposite forces. In a sales context, that means acknowledging both the part of you that wants to help someone and the part of you that needs to hit a number. Instead of shutting one side down, you bring both to the table and accept the tension.

Disconnecting from the emotional side of selling and getting comfortable between the extremes is helpful and projects confidence.

Avoiding the Trap of the Shorter, Longer Way

We wrapped up with a story Max told from the Talmud about two roads: the short, longer way (full of obstacles and distractions like LinkedIn cheat sheets), and the longer, short way that actually gets you to your destination. TL;DR: You can’t hack your way to real progress. Shortcuts are tempting but costly. Where does success come from? Thoughtful, slow work. Daily practice. Making the process your own.

About That Bread…

Before we finished, we had to talk about sourdough. Max spends 10 hours a week baking bread. He grinds his own flour and employs some complicated fermentation processes (might be another episode), and thinks of bread as something primal and sustaining.

Max’s plan: feed the world with his bread and his wisdom when AI takes all our jobs.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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I had the chance to speak with Petrina Kamiya, Global Head of AI Platforms and VP at Insilico Medicine, as well as President of Insilico Medicine Canada.

Insilico Medicine is what Petrina calls a “tech bio”—developing both AI platforms and therapeutic assets, with a flexible model licensing both. Their pharma.ai platform was created to address challenges in drug discovery all the way from target identification to the clinic. In just a few years, they've gone from having two core products to a suite of about 12, all built with a heavy emphasis on validation.

When I think about AI in drug development, I think about all the failures in clinical trials. I’ve always wondered: are the molecules themselves to blame, or is the reason for so many failures rooted in the aspects that surround their testing—like patient selection, procedures, or trial design? Petrina confirmed that the two biggest reasons for failure are safety and efficacy. Many failures are turn out to be preclinical issues—either the wrong target was selected, or the molecule causes unintended side effects. AI and machine learning are being used to better predict both, by identifying high-confidence disease targets and designing safer molecules.

But predicting toxicity is still a major challenge. There are models at every stage—from in silico predictions to in vitro and animal models—but each layer adds complexity, and good data to train AI models is notoriously hard to come by. A lot of data around failed molecules never makes it into the public domain because it’s proprietary. That means valuable insights about toxicity are often lost, though some substructures known to be problematic are at least captured in public databases. I realize that companies need a return on their investment and even failure data has competitive value. But you have to wonder how much money is wasted chasing dead ends that could have been avoided.

The other question I always have is about the mechanics of drug binding. Most approaches focus on the active site—the orthosteric site—where the protein normally interacts with its natural ligand. I asked about the possibility of other strategies like allosteric binding (where a drug binds somewhere else on the protein to inhibit function). Petrina validated that idea along with degraders, which are molecules designed to bring a protein into contact with the cellular machinery that destroys it. These newer modalities, including molecular glues, offer ways to selectively disable problem proteins without relying on traditional binding.

Nothing is straightforward. Allosteric sites can offer greater selectivity, which could reduce toxicity. But finding those sites is incredibly difficult because proteins are dynamic and mobile. It’s not just about structure; it’s about motion within the protein itself and context.

The body’s backup systems—redundant pathways, mutations, and rescue mechanisms—can undermine even well-designed drugs. This is especially relevant in oncology. Proteins like KRAS have so many variants that it’s not enough to design one effective inhibitor—you often need a panel of drugs to address different mutations. Petrina noted that the human body has many fallback mechanisms, which makes targeting disease pathways more difficult but also explains why drugs that seem perfect in vitro don’t always deliver in the clinic.

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Getting back to clinical trials, AI is mostly being applied operationally right now—to optimize patient selection, identify clinical sites with the right patient profiles, and monitor for trial reporting issues. The big advantage is in stratifying patients to improve the signal-to-noise ratio. As Petrina noted, sometimes a drug works for a subset of patients, but that signal is lost in the broader trial data. That resonated with my previous interview with Kurt Mussina who used AI to identify ideal site locations based on logistics and patient demographics—a very practical, high-impact use of the technology.

What if we could recover some therapies that have previously failed because it wasn’t tested on the right people? AI could help salvage and reposition those compounds by uncovering hidden signals in the data. You have to believe that improvements in AI will find a few lost nuggets—digging back through data with better tools to find value that’s already there.

Developing therapies aren’t the only application for new molecule discovery. Insilico is also working with companies in the herbicide space, and as Petrina explained, discovering herbicides isn’t all that different from designing drugs for people. You still need target specificity, safety, and cost-efficiency—but at an even greater scale of production. If people or animals are exposed, or if the herbicide lingers in the environment, it has to meet a high safety bar.

The unique challenge here is complexity and scale. It comes down to economics. We may spare no expense to extend a human life with doses in the milligram range. In agriculture, you’re looking for a simple compound that is cheap, can be produced in massive quantities, and can be stored in almost any conditions. It’s a new set of constraints.

AI in discovery isn’t about magic. It’s about building better foundations—more accurate models, more validated data, and more thoughtful decision-making—to improve every step from discovery to clinical success.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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I’ve never been great at conflict. Like a lot of people, I’ve leaned toward avoiding it—especially in the workplace. But I know that’s not a useful strategy in the long run, which is why I was excited to talk with Deb Nathan, a conflict navigation coach, on Life Science Marketing Radio.

Right off the bat, Deb drew a distinction between conflict resolution and conflict navigation. Resolution implies there’s a clear “winner” and “loser” or at least a compromise everyone can agree on—but let’s be honest, that’s not always possible. Navigation, on the other hand, is about figuring out how to work with each other even when we disagree. It’s about forward momentum, not just agreement.

Deb reminded me (and all of us, really) that conflict isn’t inherently bad. In fact, it’s often the spark for meaningful change—personally and organizationally. The issue isn’t the conflict itself but how we choose to engage with it.

What Is Relational Resilience?

Deb introduced a concept I hadn’t considered before: relational resilience. I’m used to hearing resilience in terms of the individual—bounce back, stay strong, push through. But relational resilience is about how teams manage conflict together. It’s rooted in the idea that we’re stronger and more creative when we work through challenges collaboratively rather than individually.

She outlined several components that make up relational resilience:

• Relational flexibility – being open to hearing and holding multiple perspectives, including conflicting ideas inside your own head.

• Relational confidence – allowing yourself to be vulnerable, which is only possible if the team environment supports that.

• Mutual empowerment – shifting from "self-empowerment" to a model where team members lift each other up.

• Creativity and imagination – thinking beyond current possibilities and co-creating new solutions.

• Appreciating complexity – resisting the urge to simplify when a nuanced approach is more useful. (This is probably my favorite.)

• Tensionality – the ability to stay engaged with someone else’s perspective while still holding your own.

• Comfort with uncertainty – resisting the rush to answers when patience could produce better outcomes.

• Reasonable hope – a grounded belief that things can improve with effort, even if it’s not easy.

It’s a powerful framework, and it aligns with how I like to think: long-term, with an eye on creating something that lasts.

Vulnerability as a Leadership Skill

When we got into the topic of vulnerability, Deb made a point I’ve seen play out in real life. The best managers I’ve had were the ones who gave me space to try things—even when those things didn’t work out. They made it safe to take risks. And when something failed it was a learning experience, not a career-ending mistake.

Deb emphasized that leaders don’t need to have all the answers or even agree with every idea. What they do need is to create an environment where people feel safe to experiment and speak up. That’s where vulnerability comes in—not just for individuals, but systemically. Managers who can admit uncertainty, invite multiple viewpoints, and reflect on outcomes together build healthier, more resilient teams.

Curiosity Is a Superpower

If you’ve listened to more than a few episodes of this podcast, you know I’m a big fan of curiosity. So is Deb. She described curiosity as the antidote to stagnation, a skill that allows us to continually learn, adapt, and better understand each other. Without it, we default to fixed positions, binary thinking, and conflict escalation.

Curiosity means asking open-ended questions, exploring ideas we don’t initially agree with, and staying open to being surprised. For leaders, modeling curiosity invites that mindset across a team. It tells people their ideas matter—even if they’re different or incomplete.

And while curiosity might sound like a soft skill, it has very real impacts on innovation, team cohesion, and ultimately, performance.

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Time Pressure vs. Long-Term Thinking

We also talked about time pressure. What happens when you're in conflict at work but feel like there's no time to sit down and work it out?

Deb’s answer was clear: if you don’t make time for it now, you’ll pay for it later—probably with more time, stress, and friction. Trying to push through without dealing with the real issue often leads to bigger breakdowns down the line. On the flip side, making space for dialogue (even just a little) can result in more durable solutions.

One of the ways to manage that time pressure, she said, is to get comfortable with not having immediate clarity. Sometimes the best thing a team can do is agree to keep talking, keep listening, and let the path forward emerge gradually.

Culture, Communication, and Cross-Team Collaboration

Later in the conversation, we got into cultural differences—across nationalities, disciplines, even departments. Deb’s background includes working with Israeli and Palestinian teens, and the lessons she learned there are surprisingly transferable to corporate teams.

The core idea: everyone brings their own lens to every conversation. We all interpret language, data, and goals differently. That’s even true when we’re technically speaking the same language. (I learned this while teaching sailing to someone from the UK—turns out “quite good” doesn’t mean the same thing in both countries.)

Within scientific companies, this plays out between technical teams and commercial teams, or between different functional areas. The solution? Again, it comes back to curiosity and creating space for people to explain their views before rushing to fix the “problem.”

Deb made a powerful point: even when people don’t agree, they can still work together if they respect where the other is coming from. That opens up new ways forward.

From Leads to Loyalty: Marketing with Relationship in Mind

Finally, I asked Deb to tie this all back to marketing. So many companies still operate with a “get me leads” mentality—but in reality, lasting impact comes from relationships, not transactions.

She was clear: if you want lasting value, you need relational resilience. Short-term wins might feel good, but it’s long-term trust that gets you through hard times and keeps customers coming back. That mindset applies to internal culture, too. If you're only focused on extracting value from employees during their two-year tenure, you're missing the chance to build something better—something that retains talent and gets stronger over time.

The Bottom Line

This conversation made me think more deeply about how we show up in teams—not just in crisis or disagreement, but every day. Deb’s framework of relational resilience gives us a better way to build cultures that support creativity, growth, and real collaboration.

For marketers, for scientists, for managers, for anyone in business: this isn’t about being soft. It’s about being smart. It’s about recognizing that long-term thinking, curiosity, and vulnerability aren’t just nice-to-haves—they’re the foundation of meaningful progress.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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In this episode of Life Science Marketing Radio, I spoke with Oliver Pearce, VP and Head of Marketing at Epista Life Sciences. Oliver brings a unique perspective to life science marketing, having started his career in the nightlife and hospitality industry. Now leading marketing at Epista, a consultancy firm specializing in pharmaceutical quality, regulatory compliance, and commercialization, we talked about what he learned from working in the nightlife scene and events, the importance of strategic narrative and where he sees opportunities for companies to do better ( be less lazy).

From Nightlife to Life SciencesOliver’s career took an unconventional path, beginning in nightlife and event promotion before transitioning into life sciences. This early experience taught him the fundamentals of building engaged communities, identifying the audience and who could amplify a message—an approach he has successfully applied to his work in the pharmaceutical industry.

Building a Global Community Around Trial Master FilesOne of Oliver’s most impressive achievements has been the creation of TMF Week, a large-scale online event dedicated to Trial Master Files. Initially conceived as a webinar series, TMF Week evolved into a high-profile industry event with over 40 speakers and thousands of attendees.

The idea emerged as a response to the need for frequent educational sessions on TMF. The COVID-19 pandemic accelerated its adoption by filling the gap left by canceled in-person events and industry professionals rallied behind the event, validating its importance.

Here is the part I find most interesting (and valuable). TMF Week initially launched as an unbranded event and gained credibility before becoming synonymous with Oliver’s (previous) company.

The event was organized with a small team and limited resources, using basic webinar tools and CRM integrations. Despite logistical challenges, it became a central platform for industry discussions and a key driver of business opportunities.

The Power of Strategic Narrative in MarketingI appreciate how Oliver emphasizes the importance of crafting a strategic narrative rather than just relying on a standard value proposition. While value propositions focus on what a company offers, a strategic narrative provides a broader industry perspective and aligns messaging across sales, marketing, and leadership.

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Elements of a Strong Strategic Narrative

If you’re familiar with The Hero’s Journey from Joseph Conrad, you‘ll recognize how it’s implemented here in a very succinct way:

• Define a major shift in the industry and explain its significance.

• Identify the challenges that come with that shift.

• Offer a clear perspective on how businesses should adapt.

• Demonstrating how your company helps customers navigate the change.

This approach produces marketing that is not just about features and benefits, but about leading an industry conversation in a way that builds authority and trust. This is an approach that works regardless of where someone is in the buying cycle. It doesn’t mean throwing features and benefits away, but rather provides value in an interesting way that increases the likelihood of being considered when a customer has a problem you can solve.

Common Pitfalls in Life Science MarketingI asked Oli to point out where life science marketing can come up short.

• Lack of Business Alignment: Marketing is often viewed as a cost center rather than a revenue driver because it isn’t directly tied to sales and pipeline growth.

• Overreliance on Vanity Metrics: Metrics like website traffic and lead volume don’t necessarily translate to business impact, leading to misaligned priorities.

• Random Acts of Marketing: Without a strategic foundation, marketing teams often engage in disconnected activities that fail to build long-term engagement.

Aligning Marketing with Business GoalsOliver advocates for tying marketing success to measurable business outcomes. LEad generation may be the easiest metric to track, but this doesn’t necessarily provide the best outcomes in the long run. Other metrics, while a little more challenging, can provide a better picture and improve overall results. Instead of focusing on lead generation alone, he recommends tracking:

• The conversion of marketing-generated leads into pipeline and revenue.

• Correlations between brand awareness efforts and increased inbound inquiries.

• High-intent engagements, such as direct requests to speak with sales.

By aligning marketing efforts with business goals, marketing teams can move beyond vanity metrics and demonstrate tangible value to the organization.

Lessons from Nightlife Marketing Applied to Life SciencesCoincidentally, I have spoken to two people recently who have transferred their skills from an earlier time in the nightlife world to life science. Oliver’s background provided him with a unique skill set, including:

• Community Building: Understanding how to attract and engage audiences for an event.

• Adaptability: Testing different marketing approaches and adjusting strategies based on real-time feedback.

• Focusing on Outcomes: Just as nightclubs measure success by attendance, marketing should measure success by business impact rather than surface-level engagement.

Life science marketing can go beyond traditional tactics and focus on strategic storytelling, community engagement, and measurable business impact. His experience proves that even with limited resources, marketers can build high-value industry events and thought leadership platforms that drive long-term success.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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I ran into Jackson Hyde, the CEO of Diaago, whom I had interviewed on Life Science Marketing Radio a few years ago at SLAS. Jackson showed me a new cold shipping unit and suggested I talk to Faizan Ahmed. That led to this conversation about his company, Invensify, and its innovative approach to cold chain logistics.

With an electrical engineering background and experience in solid-state physics, he started his career in the defense industry, leading the development of a precision coordinate scanning system for night vision goggles, a project adopted by the U.S. Air Force. As you’ll hear, this experience shaped his entrepreneurial mindset, exposing him to various disciplines beyond engineering, including sales, marketing, and strategic planning, .

Before Invensify, Faizan co-founded Genxsys, a company that developed a rain-deflector system for camera lenses based on centrifugal force. The product allowed photographers to take clear pictures in the rain or snow without interference. Within a short period, Genxsys secured a lot of orders and was rapidly acquired. This reinforced Faizan’s passion for identifying problems and developing innovative solutions.

At this point, I’m struck by the difference of someone in life science workig on a single problem for years as opposed to an engineer who solves a problem and moves on. I know it’s not a fair comparison between trying to understand biology and applying existing knowledge, but I find it interesting.

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Faizan’s inspiration for tackling cold chain logistics came from a personal experience. Watching his diabetic dad struggle to keep insulin at the correct temperature while traveling, he realized there was a major gap in the market. The existing solutions relied heavily on ice packs, which required precise handling, refrigeration, and compliance with transportation regulations. TSA often discarded ice packs at security checkpoints, forcing travelers to find alternative cooling methods. This inconvenience and inefficiency led him to explore better solutions for cold chain shipping.

As Faizan researched the industry, he learned that pharmaceutical companies still relied on Styrofoam boxes with ice packs to ship temperature-sensitive drugs. These solutions required significant manual effort, meticulous packing procedures, and real estate for refrigeration. The approach lacked reliability, with many shipments relying on overnight delivery to minimize temperature deviations. Additionally, the use of traditional compressor-based refrigeration was impractical due to power consumption and transportation restrictions on lithium-ion batteries.

Recognizing these limitations, he and his team developed a thermoelectric cooling system that eliminates the need for ice packs, compressors, and refrigerant. Their solid-state cooling technology is far more efficient than conventional thermoelectric systems, thanks to advancements in material science. The Invensify system charges in five to six hours and maintains a stable temperature (2 to 8°C) for over 100 hours without an external power source. The battery is compact, fitting into a shirt pocket, solving the power and weight issues associated with traditional refrigeration methods.

Beyond the cooling innovation, Invensify integrated smart tracking features. The system includes LTE, Bluetooth, and Wi-Fi connectivity, allowing users to monitor the shipment’s location and temperature in real-time. This level of tracking provides pharmaceutical companies with a level of assurance that was previously unavailable. Instead of relying on periodic temperature checks when a package changes hands, companies can now have continuous visibility into their shipments.

The business case for Invensify extends beyond improving logistics efficiency. In addition to financial costs, there are broader environmental concerns, such as the non-recyclable nature of Styrofoam and the energy consumption of traditional cold storage methods. Invencify’s solution reduces labor costs, eliminates the need for large-scale refrigeration infrastructure, and minimizes waste, making it an attractive alternative.

Faizan’s insights into the business side of innovation were particularly compelling. He emphasized that a great technological innovation alone is not enough—success comes from understanding and solving customer pain points. In this case, Invensify doesn’t just offer an efficient cooling system; it also simplifies logistics, enhances tracking, and provides a more sustainable option. The company’s approach streamlines operations by removing the complexity of handling ice packs and reduces liability for pharmaceutical companies by ensuring drugs are maintained at the correct temperature throughout transit.

Finally we discussed funding and what it takes for a startup to secure investment. Faizan highlighted three key factors: the strength of the idea, the quality of the team, and the credibility of the founders.

He credited his early career experiences for preparing him to navigate the startup world. Working at a small company allowed him to wear multiple hats and understand the full lifecycle of a product—from development to sales. By the time he launched Genxsys and later Invensify, he had built strong relationships with investors and strategic angels who believed in his vision. When he pitched Invensify, he was able to secure funding quickly, thanks to his track record and well-articulated business case.

Of course, having a track record of success makes raising funds easier. For first-time founders, he stressed the importance of bootstrapping to develop a minimum viable product (MVP) and demonstrating a clear market opportunity. Investors look for disruptive solutions with large addressable markets, and startups must frame their innovation in terms of its business impact rather than just its technological novelty.

He also underscored the importance of understanding not just the technology but the broader ecosystem in which it operates.

Invensify technology has the potential to reshape multiple industries. Beyond pharmaceutical logistics, there are applications in vaccine distribution, particularly in regions with unreliable power grids. It could also be a game-changer for individuals who rely on refrigerated medications, ensuring they have a reliable solution when traveling or facing power outages. The broader implications of a solid-state, highly efficient cooling system extend far beyond what we discussed.

Innovation happens at the intersection of technology, business, and human needs. It’s not just about inventing something new—it’s about making it viable, scalable, and impactful. Our conversation underscored the importance of thinking beyond the immediate function of a technology and considering all the elements that contribute to its success, from logistics and compliance to user experience and market fit.

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I had the pleasure of speaking with Heather Javier, a genomic sales specialist at Roche, sales coach, and host of the Transition to Sales podcast. Heather shared her journey from working in translational oncology and stem cell research to transitioning into sales, inspired by her desire to connect, problem-solve, and align her career with her values.

Heather’s Journey

Heather’s career started with a biology degree and a role in translational oncology at Genentech. Her early work involved managing mice for efficacy studies, followed by years in stem cell research, where her hours were dictated by the cells she was culturing.

Despite her scientific success, Heather felt a gap between her work and her passion. What energized Heather was networking, problem-solving, and collaboration. Inspired by her own interactions with sales reps, she realized she could make a bigger impact in sales by addressing customer needs more effectively. After a year of networking and revamping her resume, she made the leap into sales, which she describes as the best decision she made for her family and career.

Networking

Heather believes networking is simply about resourcefulness and taking a “heart-centered approach.” During her days at UCSF, she constantly collaborated with statisticians, vendors, and colleagues to troubleshoot experiments. This mindset carried into her sales career, where she emphasized the importance of building authentic connections.

Networking isn’t just a means to an end; it’s about helping others while advancing shared goals. For those who feel intimidated by networking, she suggests shifting your mindset: recognize that people often want to help and are energized by being part of your journey. I couldn’t agree more. I have experienced this many times over many years.

Transitioning from Science to Sales

Heather knows scientists and technical professionals have the skills needed for sales roles—they often don’t realize it. Sales, at its core, is about problem-solving, asking the right questions, and connecting solutions to customer needs.

Scientists are used to analyzing variables and troubleshooting experiments. In sales, this translates to understanding customer pain points, guiding discussions with targeted questions, and tailoring solutions. Heather highlighted the importance of being prepared, leveraging technical knowledge, and staying resourceful. These are things scientists do regularly.

Overcoming Fear and Building Confidence

One of the biggest hurdles for those transitioning into sales: building confidence. Her advice? Treat the learning process like you would in a lab. Just as scientists train to operate new equipment, aspiring sales professionals can prepare by studying their business, asking questions, and leaning on mentors.

Heather shared her own experience of transitioning into sales at QIAGEN, where she won President’s Club in her first year. Her success came from applying her scientific mindset to sales—studying customer personas, analyzing data, and proactively creating business plans. Confidence, she emphasized, comes from preparation and a willingness to learn. In other words: be curious and do your homework. Isn’t that what we’ve been doing our whole life?

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Bridging the Gap Between Sales and Marketing

Heather isn’t the first to point out that sales and marketing often operate in silos, which can lead to missed opportunities. She urged marketers to view sales teams as their “customers” and collaborate closely to create materials that resonate with what sales reps are hearing in the field.

Here is an idea she shared that I can get behind. Cultivate a sense of culture and community at conferences. Instead of relying solely on product demonstrations, create experiences that reflect the company’s values and culture, helping to attract ideal clients and foster stronger connections.

Connecting the Dots: Relationship Building in Sales

Heather frequently mentions the idea of connecting the dots. She described her role as a connector—both within her company and with her customers. Building trust and relationships is essential, whether it’s with decision-makers at a customer’s organization or with internal teams like R&D and technical specialists.

She stressed the importance of identifying “coaches” within customer organizations—people who advocate for your product or service and help you navigate the decision-making process. Heather’s approach to connecting the dots involves bringing people together, asking thoughtful questions, seeking feedback, and leveraging internal and external resources to solve problems collaboratively.

Sales Coaching for Startups

In addition to her sales role, Heather is developing a program to coach startups on building their own sales strategies. Hiring a dedicated sales team can be expensive. Heather’s vision is to help technical teams get comfortable with the fundamentals of sales. Her coaching focuses on skills like prospecting, navigating customer personas, and moving opportunities through the sales funnel, all while staying true to the company’s culture and mission.

For startups with a strong sense of purpose, Heather’s coaching aims to channel that passion into effective customer connections.

Empowering Women in Sales

Heather’s podcast, Transition to Sales, is geared toward women—particularly mothers—looking to move into sales roles from technical backgrounds. She provides actionable advice, free resources like resume guides, and insights into building confidence in sales. Heather’s mission is to create representation in an industry that is still predominantly male, showing women that their skills and perspectives are invaluable in sales.

Heather’s story is a testament to the power of aligning your career with your values and passions. Her journey from the lab to sales demonstrates how scientific skills can translate into successful sales strategies, and her heart-centered approach serves as an inspiring model for others considering a similar transition.

For anyone interested in learning more, be sure to check out her podcast and connect with her on LinkedIn.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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If you’ve been following me on LinkedIn lately, you know I spent a lot of time thinking about the importance of company culture and how marketing content can both reflect and drive culture. Done well, I believe the same content can both motivate employees and attract customers.

In this episode, we’ll take the impact of culture even further. Mykella Auld is the founder, Chief Culture Officer, and Executive Director of The Workwell Studio, and her work focuses on the intersection of organizational culture and societal well-being.

Mykella’s vision is to help organizations see culture as a strategic asset—a mechanism that not only supports employee engagement and productivity but also shapes the societal landscape in meaningful ways.

The relevant question, I believe is, “How can organizational culture best work to achieve the desired outcomes, whether in the public sector, the private sector, or in any community?”

Culture’s Ripple Effect

After getting a sociology degree, Mykella was working with a school district and the National Institute for Educational Leadership. A challenging legislative session on school reform opened her eyes to the impact of internal challenges. As is likely often the case, the culture within organizations and its impact often reaches as far as the services they provide (perhaps farther).

The Genesis of The Workwell Studio

Building on her experiences, Mykella pursued a master’s degree in leadership and later led a research team exploring the intersection of local government policies and community well-being. This work illuminated how public institutions—schools, nonprofits, and government agencies—impact not just their immediate stakeholders but society at large. Her findings reinforced the idea that organizational culture can be a powerful tool for driving positive change both internally and externally.

Strategies for Building Healthy Cultures

Culture doesn’t happen by accident—it must be strategically planned and invested in. Brian Thomson made the same point for life science companies in a previous episode. How does it happen. Mykella pointed out that HR departments, although essential, should not bear sole responsibility for culture. While initiatives around leadership and organizational development often fall to HR, they likely have enough to do and it might even be a conflict. Instead, she suggests organizations consider roles like a Director of Culture Initiatives to ensure dedicated focus on this critical area.

Key strategies include:

• Co-Creation: Building cultures that prioritize shared leadership and accountability. By involving employees in decision-making processes, organizations foster trust and inclusion.

• Well-Being: Focusing on social and emotional development, trust-building, and systems of care. Health outcomes are just one facet of well-being—the broader goal is creating environments where people thrive emotionally and socially. It strikes me that this is the kind of environment where people would be most happy and productive.

• Innovation: Encouraging a mindset that embraces trial and error, creativity, and exploration.

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The Role of Public Sector Organizations

Mykella noted that public sector leaders often lack formal leadership training, perhaps due to budget constraints, which can hinder their ability to prioritize staff and culture. (I wonder if it’s significantly different in the private sector. It seems most often that people who are good at their job get promoted to management without additional leadership or management training.)

Additionally, public institutions tend to focus outward on their mission to serve society, sometimes neglecting the internal health of their organizations. The behaviors and norms within these institutions often ripple into the communities they serve. It strikes me as a misalignment of values if an organization trying to serve the public isn’t modeling the world it hopes to create.

Mykella mentioned an art piece from the 1950s illustrating how workplace dynamics influence home life. This insight remains relevant today, emphasizing the societal responsibility public institutions have to model healthy behaviors and norms. Am I naive to think we should need to be reminded to treat others, whether they are colleagues, co-workers, employees or service providers with respect?

The Intersection of Public and Private Sectors

Here is why the above matters. To no one’s surprise, private sector leaders are having a huge impact on society in their public roles. While this trend brings opportunities for innovation, it also raises questions about balancing business-oriented approaches with the unique purposes of public institutions. From my point of view, none of us should outsource our cultural initiatives to people who don’t share our values. While there are certainly successful workplaces that reflect lovely communities, I don’t think that it makes sense to govern a society in the same way one would run a business.

The First Step

A centerpiece of The Workwell Studio’s work is its cultural audit tool. This comprehensive approach gathers data and human stories to assess an organization’s culture across areas like HR policies, well-being, social intelligence, and innovation. The findings provide a roadmap for organizations to align their strategies with their cultural goals.

Innovation, in particular, stands out as a critical component. Fostering an innovative mindset and new initiatives requires leaders to support risk-taking, value employee input, and view failures as learning opportunities. Without this openness, efforts to build a thriving culture may falter.

My Thoughts

One might ask if it’s the place of organizations, public or private to be the arbiters of culture. Fair enough. In a capitalist society, our workplaces often become our communities. For any organization, but especially large ones, there is the opportunity to shape societal culture - for better or worse I suppose. So if your mission is to make the world a better place, does your internal culture align with that?

At the same time I was recording and editing this interview, I was reading a book by Matthew…. entitled Shop Class as Soulcraft. The thesis of the book is largely about the value of manual work. The author is a motorcycle mechanic with a PhD in Physics.

The book explains how our educational system and workplaces are set up in some ways to devalue certain types of work.

In the course of reading it, I contemplated whether I am closer to being a craftsperson or a cog in the machine. All of that got me thinking about how we justify making organizations centers of culture to some degree. That may overstate their impact.

It strikes me that there are many legitimate ways of working, all of which have value, even though the satisfaction that comes from it may vary both in kind and degree. The motorcycle mechanic learns from experience and a hands-on approach. He or she is intimately connected to their work and the end product. For many organizations or businesses, however, this doesn’t make sense. It takes a lot of people to design, build, procure, and ship a mass spectrometer, for example. In that situation, leadership and teamwork are critical for success, which is why I believe that thinking about culture strategically is important.

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In this conversation with Elizabeth Chabe, CEO of High Touch Group and author of The Giant's Ladder: The Science Professional’s Blueprint for Marketing Success, we discussed a possible convergence between science communication and marketing. Reflecting on how few living scientists are household names, she talked about the importance of storytelling in transforming scientists into figures society admires even positioning them as rockstars or cultural icons.

Their lack of visibility isn’t because scientists aren't engaging but because the traditional academic outlets they utilize don’t effectively reach the wider public. She sees an opportunity for scientists to break free from academic journals and allow their work to inspire future scientists and communicate value to society. Elizabeth noted the healthcare sector's medical affairs professionals, who engage deeply with scientific education yet seldom achieve fame comparable to cultural figures like Neil deGrasse Tyson or Bill Nye.

The challenge, she says, lies in leveraging modern marketing tools to amplify these efforts effectively. We talked about how platforms, including YouTube, offer avenues for better engagement with the public and how scientists, through storytelling and proper marketing strategies, can expand their reach.

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What does this mean for companies? You might say that science is a little bit on the back foot lately. There is a definite issue of trust even as more and more of our daily lives are made better and more convenient by the discoveries of scientists. This is a topic that has been on my mind a lot lately.

Companies have an opportunity, and I would argue an obligation, to elevate both their brand and society’s perception of science. Elizabeth provided examples of organizations like Moderna. During the COVID-19 pandemic, Moderna focused on its broader mission of advancing RNA-based medicine. This strategic focus not only strengthened their brand but also helped reinforce trust in RNA-based therapeutics. That has likely opened up a whole new world of possible therapies but without trust, will they make it to market?

Finally, where are the lines between science communication, education, and marketing and how can companies think about these activities to grow their business and, if you will, the market for science and scientific advances?

Elizabeth has a framework for thinking about the nuances that I really appreciate. This segmentation—communication explains, education equips, and marketing connects—provides a foundational strategy for life science companies to build trust and competence and ultimately motivate action.

Science communication is about making information digestible for non-experts, education builds understanding and competence, while marketing’s goal is to foster an emotional connection and drive action.

Thinking long term, science communication not only helps the public to appreciate the work you do now, but feeds a pipeline to solve problems, possibly at your company, in the future. Education naturally follows to make that happen. As marketers we should take advantage of all of the above to create those connections, build our brands and create a public that accepts science, not blindly, but with real understanding.

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Last month, I went to Stanford and did four years of college in four hours. Jennifer Dionne has been on the podcast before. After showing me some amazing technology in her lab (nanoparticles - I’ll share some clips on LinkedIn later) we wandered over to the Polynesian Garden to talk about her class, the Science of the Impossible. I avoided the waitlist and got the Cliff Notes version, which was enough to fill my brain for the day.

Our conversation started with her path to becoming a scientist (inspired by The X-Files) and ended with discussion of deploying remote sensors in the environment to understand shark populations around Palau based on detecting their DNA in ocean water.

In between, we talked about the role media plays in sparking scientific interest, how she encourages students to think about big, difficult problems and the value of “curiosity-driven” research that can lead to unexpected discoveries, such as Faraday’s work with semiconductors and the accidental origins of chemotherapy. Oh yeah, teleportation was in there as well. Watch the video.

In the class, they discuss scientific breakthroughs that were once thought impossible but also how to approach scientific problems that seem impossible now. What are the mindsets and the approaches that lead to progress on significant challenges?

Jen suggests thinking of a conversation with future grandchildren. What do you want to say you contributed to the world they live in?

So here I’ll follow her model and maybe take a step forward. We start by thinking of the problem we want to solve and then the aspects of that problem that make it difficult to address now. These are not all technical challenges. It often comes down to policy and infrastructure.

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I’d like to help build an infrastructure of public understanding for tackling long-term threats like climate change. This has been on my mind, especially since reading Fire Weather: A True Story from a Hotter World.

As early as the 1970s scientists understood the challenge of global warming caused by CO2 emissions. It was neither polarizing nor controversial. But then, as now the perception was that there are more immediate threats - economic threats like inflation or unemployment, or physical threats of disease or geo-political conflicts that demand immediate attention.

Humans are very good at identifying near-term threats and dealing with them as best we can. Long-term opportunities provide plenty of motivation (usually money) and don’t need much help. Long-term threats, not so much. Can we reframe those threats to become opportunities in a tangible and meaningful way?

These opportunities are often called moonshots now, not just because of their lofty goals, but because of the inspiration they provide and the possibility of developing important and useful technologies on the way. One advantage for the Apollo program, besides national security considerations, was that every human being that ever lived has looked at the moon and wondered what it was like up there. The problem was relateable and easily visualized.

Reversing climate change is certainly a lofty goal. But success is not easily visualized. Rather than spinning off multiple technologies that can serve other purposes, it will instead require the development of many new independent solutions that each contribute to the goal. Based on the work that Jen’s lab is doing on carbon capture and environmental sensing as well as the work of others, I have no doubt the technical challenges can be solved. That leaves policy and infrastructure.

Solving climate change requires not just agreement within, but also between nations. Public understanding and trust in science comes back around to the media and storytelling.

The stories we tell as science marketers and communicators, like Fire Weather, are an essential component of driving the policies that will enable the infrastructure required for success. We must continue to highlight the scientific advancements and give more visibility to the people that are doing that work. Let’s inspire the next generation and restore trust in science.

In case you didn’t catch this on LinkedIn, here is some bonus content where Jen is talking about some mind-blowing uses for nanoparticles.

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Shifting our approach to feedback

In my recent conversation with mindset coach, Margaret Jennings (MJ), our conversation started with the emotional rollercoaster created by feedback—especially when you're early in your career. Feedback, both positive and negative, is useful but can also result in a wild ride. MJ once described herself as a “floundering high achiever” in her 20s. She is a more grounded and self-aware leader today. Her insights are both relatable and instructive.

Like many of us I’m sure, she once heavily relied on external validation. She was on top of her game when feedback was positive, but when it turned critical, it felt like failure. This is something that likely resonates with a lot of high achievers. Her sense of self-worth was tied to what others thought about her accomplishments, whether in school or sports. In many ways, this made her successful in the short term, but it came at the cost of long-term fulfillment.

She explained that it’s natural to want to please those around us—whether it’s parents, teachers, or coaches. After all, as babies, this is how we secure food, love, and safety. But the problem comes when we carry this strategy too far into adulthood, to the point where our identity is solely built around what others think of us. This approach eventually leads to burnout and can limit our potential for growth and happiness.

Consider the mental gymnastics we all do when we receive feedback. It reminded me of the challenge of a good golf swing: You can’t perform well if you are overanalyzing every aspect of it all the time. Margaret agreed and said her turning point came when she started working with a mental performance coach. This coach helped her realize that her value didn’t have to come from others' opinions; instead, she could generate her own sense of worth internally. That shift in thinking transformed the way she performed, both in work and in life.

Building a relationship with yourself

MJ brought up the concept of building a relationship with oneself: We’re constantly in a dialogue with ourselves, and it’s crucial to make that relationship a positive one. Through practices like journaling, meditation, and self-reflection, we can learn to identify and understand our own needs and desires, leading to a more balanced and sustainable approach to both work and life. Looking back at my own life, there was a time when I had a few ideas about a career path but was relying a lot on others’ expectations and evaluations of my abilities to show me the way. It took a long time to move past that.

I asked Margaret about how she specifically changed the way she talked to herself, and her response was insightful. She noted that awareness is key—you need to recognize the quality of your self-talk. Is it positive and affirming, or is it critical and self-defeating? She likened this to any relationship, explaining that you need to invest time and energy into yourself just as you would with a friend or partner. You’d have a difficult time building a positive relationship with anyone else if you were constantly critical of them.

It strikes me that adopting a growth mindset is your ticket off of the emotional rollercoaster. You no longer see constructive feedback as a personal attack but as an opportunity for growth. This mindset shift is vital, especially for high achievers who can often fall into the trap of seeing any criticism as a sign of failure.

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Embracing uncertainty

MJ talked about the importance embracing uncertainty, something that has been on my mind lately, and her thoughts on it really hit home. Our constant search for certainty is often counterproductive because so much of life is inherently unpredictable. Instead, we should focus on what we can control and accept that not everything will go perfectly. It’s about shifting from an all-or-nothing mentality—where you're either a success or a failure—to a more nuanced view where growth and learning happen over time. (If you’ve been a listener for a while you know how much I love long-term thinking!)

I think we waste a lot of time and energy trying to control things that are not in our power to control or trying to predict things that we do not have the capacity to predict.

So, our focus is such a limited resource, that if we have the choice to allow it to be consumed by things we can't control, which is going to fuel anxiety and overwhelm, or we can choose to look at this situation and say, okay, realistically, what can I control here in terms of having impact and creating clarity? Then we're able to make more progress forward.

We also touched on expectations and career transitions. This is where the growth mindset can make a huge difference for you. First of all, growth is about trying new things, stepping into new roles. It occurs to me that being ready for a new position and being good or great at it are two points on the curve. Our expectations for our performance at the beginning need to be realistic and not necessarily at the level of someone who did that job for 3-5 years.

Being ready means you have the tools and are able to grow (there’s that word again) into the role. Of course you will get better at it over time. For example, MJ is a hockey player. She described the excitement of lacing up her skates and getting on the ice for the first time. She pointed out that if she didn’t expect to fall on her face before learning how to do crossovers and stop and start, it would have been difficult to achieve any success.

You may have noticed I’ve been thinking and talking about culture within organizations a lot lately. It occurs to me that we each create a culture within ourselves that affects our ability to perform in any role we take on (leader, parent, contributor etc). MJ’s advice goes a long way toward helping us ensure that is a supportive and growth oriented one that will lead to our success.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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With the life science tools industry facing a 7% drop in revenues, innovation and fresh approaches are needed to hold on to your slice of the pie. I spoke with Marina Hop, Managing Director, and Gary Brooks, Creative Director at Viveo Consulting, to explore creativity in life science marketing. Our discussion focused on how creativity can be a powerful tool to not only optimize business operations but also generate new ideas to address these challenges.

In a downturn, companies often retreat into operational efficiency, cutting costs and tightening the reins. However, real growth and differentiation come from creativity—an approach that not only applies to marketing but spans across the entire business strategy, product development, and even internal team dynamics.

Creativity as a Key to Performance

Marina pointed out that while companies are focused on optimizing their operations, there's a limit to how much optimization can drive growth. “The optimization side addresses the bottom line,” she said, “but creativity really addresses the top line.”

I've seen the same pattern—companies cutting budgets and focusing on short-term savings. I once asked my VP of marketing why, instead of cutting back, we didn’t go full throttle to take market share when our competitors were pulling back. My guests agreed on the need to push forward with disciplined creativity, even when times are tough. As Marina pointed out, Bruker—a company that has excelled in this downturn—successfully combines operational excellence with what they call "disciplined entrepreneurialism."

Balancing Operations and Innovation

Gary elaborated on how companies often live in two worlds: the operational world of structure, metrics, and routines, and the innovation world, driven by curiosity and experimentation. He emphasized the importance of maintaining a balance between these two worlds, especially during challenging times. “When companies struggle, they revert back to the operational side because it’s manageable,” he said, but added that without creativity and innovation, growth stalls.

He pointed out, creativity is not just about artistic expression—it's about connecting insights to create something valuable, whether it’s a new marketing channel, product innovation, or strategy.

Creative Thinking in Marketing and Beyond

Around here of course, we’re focused on marketing creativity, and we discussed how companies could be creative not just in their messaging, but in the types of marketing they do. I suggested that creativity in marketing isn’t just about making clever ads, but about exploring new ways to engage with customers—new channels, content types, or interactions. Marina agreed, saying that creativity should permeate any generative business activity, from formulating a strategy to developing a new product.

One key takeaway from this part of the conversation was that creativity shouldn’t be confined to one department. As Gary put it, “It’s not just marketing, it’s communication.” Every interaction a company has, whether with investors, customers, or even internally, is a chance to think creatively about how you present your brand.

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The Power of Observation

Marina introduced a concept that I found particularly interesting—phenomenology, the practice of observing and describing human experiences without immediately analyzing them. This practice helps stimulate creativity by encouraging people to step back, observe, and understand what’s really happening before jumping to conclusions. Viveo might send teams to observe a simple activity, like how people interact in the cafeteria, and then come back and write a narrative about it.

Gary emphasized the importance of observation in creative thinking, noting that many people don't take the time to observe what’s happening around them. “People don’t really observe people doing stuff,” he said. By focusing on observation, companies can gather insights that lead to more informed, creative solutions.

One powerful example Marina shared was when Viveo worked with a client that had developed an automated sample prep system for next-generation sequencing (NGS). The company had expected this product to be a hit because it saved time and effort. But by observing how scientists actually worked in the lab, they realized the product wasn’t solving the problem scientists cared most about—reproducibility. Scientists didn’t mind spending extra time on manual prep because they wanted to ensure the highest quality samples for the expensive sequencing process. By shifting the marketing message to focus on quality and reproducibility rather than time savings, the company could better align with its customers' needs.

Creativity as a Learnable Skill

One of the most encouraging insights from Marina and Gary was that creativity can be learned. It’s not reserved for "artistic" types—it’s about curiosity and observation. As Gary put it, creativity doesn’t come from waiting for the “creative gods” to bless you with an idea. It’s a process of grinding through ideas, experimenting, and finding connections.

This process-driven approach to creativity is similar to how scientists work, which should make it especially relevant for life science companies where many marketers used to be scientists. Whether it’s through exercises like observing people in the canteen or training teams to be more curious and observant in the lab, companies can cultivate creativity throughout their organization.

Building a Culture of Creativity

Why not encourage creativity at every level of the organization. This includes fostering a culture of curiosity, where employees feel empowered to take risks and explore new ideas. “Safe adventures,” as Gary called them, allow teams to innovate within a structured environment where failure is a learning opportunity rather than a setback. My best boss was very good at this. I could call him with an idea and he’d say, “Let’s do it.” If it didn’t work as planned we just figured out why and tried something else.

Establishing a culture of creativity will allow you to deliver results regardless of market conditions.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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The process of content review, approval, and distribution is often perceived as a "necessary evil" in life science marketing. If you're reading this, you probably know how challenging this process can be. In this episode, I had the pleasure of chatting with Annalise Ludtke, Senior Manager for Marketing Communications and Strategy at Vodori, and host of the Amend and Progress podcast. She offered some great insights on how to streamline and improve this process while still keeping everything compliant, fast, and efficient.

Right out of the gate, Annalise laid out the core problem Vodori aims to solve: the complexity of managing content in life science organizations. Companies need to develop a lot of promotional and educational materials, and getting those materials reviewed, approved, and distributed is a complicated process. The challenge is not just about creating great content—it’s about managing the feedback loops, the endless rounds of revisions, and the hurdles of compliance.

Without a solid process for reviewing and approving content, life science companies can’t effectively market their products. Of course, you need to make sure everything you put out there meets legal and regulatory standards.

Best Practices

Annalise shared some best practices that Vodori advocates, and these tips stood out to me as practical and actionable regardless of any platform you might deploy or none at all.

• Parallel vs. Sequential Review: One of the key strategies Annalise mentioned is the benefit of parallel review processes, where all the necessary stakeholders—whether it's medical, legal, or regulatory teams—are reviewing content simultaneously rather than sequentially. This can save a lot of time because it encourages open dialogue between the different reviewers. If someone has an issue with a piece of content, they can discuss it with the other reviewers in real-time, instead of waiting for feedback to trickle in one department at a time.

I appreciated her point that while parallel review might seem more chaotic at first glance, it actually fosters more collaboration. Reviewers can resolve conflicting feedback before it gets back to the content owner, which can speed things up dramatically.

• Clear Ownership and Communication: Clearly defined roles and responsibilities make everyone’s job easier. Annalise emphasized that it's critical for each reviewer to stay in their lane and provide feedback based on their specific area of expertise. This helps avoid confusion and unnecessary edits, which can slow down the process. Additionally, it's essential for reviewers to communicate clearly—indicating whether a comment is a required change or just a suggestion, for instance. This small change can remove a lot of friction and keep the process moving forward smoothly. Color-coding comments to signify importance is a simple yet effective way to clarify expectations.

• Real-Time Collaboration: I imagine most companies now have the ability for multiple stakeholders to collaborate on documents in real-time, where everyone can log in, see the comments being made by others, and even have discussions within the document itself. This not only saves time but also reduces the likelihood of conflicting feedback, which would require another round of calls or emails to resolve.

Is this content helpful?

Where is the data for that claim?

If someone has a question about a claim, you’d like to know where to find the data that supports it. It seems a simple idea to have a claims library. Vodori’s platform allows companies to store and manage approved claims, making it easier to track where and how certain claims are being used in marketing materials. Likewise when claims are updated with new data, you’d like to know where they have been used in the past to find all the places where the claim was referenced.

How does your process compare?

Beyond best practices, setting goals and understanding benchmarks is another step toward making the content review process less painful.

Let’s invite our industry peers out for drinks after work to compare our review processes! - No one said that.

Fortunately, Vodori publishes an annual Benchmarks Report that looks at various metrics like average review time and number of review cycles, giving companies a way to see how they stack up against industry standards.

By comparing your metrics to industry standards, your company can decide what might realistically make the most impact and set goals for improving your review process.

For instance, some teams might set goals around reducing the number of review cycles content has to go through or improving the speed at which content gets approved. Compliance is another area —perhaps setting a goal to reduce the number of compliance issues flagged during the review process.

Reducing time to market

In my experience, content was always the last thing on the list before a product launch. The impact of improving the content review process is huge. By reducing the time it takes to get content through review, life science companies can get their products to market faster, which ultimately benefits customers/patients. Vodori’s platform not only helps streamline the process but also provides peace of mind by ensuring compliance every step of the way.

As Annalise pointed out, the goal is not just to make the process easier for marketing teams but to improve outcomes across the board—for the company, the team, and, most importantly, the patients.

Annalise’s Podcast: Amend and Progress

Toward the end of our conversation, we touched on Annalise’s podcast, Amend and Progress, which focuses on improving content review processes in the life sciences. She’s been hosting conversations with experts both inside and outside of Vodori, tackling topics like best practices, industry trends, and even the potential role of AI in content review. You should definitely check it out.

Her podcast is a great example of how even niche topics can have a dedicated audience, offering valuable insights for those navigating the complexities of content management in regulated industries. I think there’s a lesson here for all of us in the podcasting world—if you’re solving a real problem for people, there’s always an audience, no matter how specialized the topic is.

Final Thoughts

I’ve been thinking a lot lately of my second episode way back around 2014 or 2015 about how marketing communications can change an organization. This is one of those opportunities. By taking the lead on setting standards and implementing best practices for the review and approval process, marketing can improve the work lives of their colleagues in other parts of the company as well as their own. The added benefit of developing processes with rigor lets marketing communications be seen as more than a service provider, but rather a leader in unlocking innovation and success in an organization.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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Hooriya Hussain is a life science marketing leader and a fierce advocate on the National Board of Governors at the Human Rights Campaign. Before filming this video we had had only two conversations, one on zoom and one at BIO 2024 in San Diego. Both times, Hoori mentioned the idea of soul in the life sciences. I wasn’t entirely sure what she meant. I was definitely intrigued. We decided to explore that on a walk and talk.

Trailer:

Our discussion revolved around purpose and leadership. The last year has been a tough one in life science beyond the usual pressure and uncertainty. Maybe that was what had prompted Hoori’s thoughts about holding on to your soul.

Before diving into that, I was curious about what it was like to grow up in Qatar as the child of immigrants and then immigrate to yet another country you knew nothing about except what you saw or heard in pop culture. She didn’t say it explicitly, but I noticed that Hoori’s thoughts on leadership, nurturing your own soul and understanding your purpose are deeply tied to the experiences of her youth, trying to fit in where “it just felt like anything could change anytime”.

The folks that do the work to understand themselves usually have a slightly longer shelf life in science.

When Hoori talks about this, I interpret that as understanding and staying true to your purpose. Satisfaction often comes from knowing the contribution you are making. Purpose is what will sustain you through setbacks, various disruptions and even layoffs. Is your purpose aligned with your work? Do you see how you fit in?

I have seen this in my own career. I struggled in graduate school (limited shelf life) in part because I didn’t look around to see what other options were available before I applied. Grad school seemed like the thing to do to feed my curiosity and joy of learning. It turned out that while research was interesting for a time, I wasn’t driven by it in the way my friends who are successful scientists are.

It was difficult to explain to my family and friends why what I was studying mattered to anyone. That should have been a red flag for me. I’m not saying it didn’t matter. But one thing that mattered to me was to be able to talk about my work with people outside the lab.

My path was not aligned with my purpose. I’m driven more by helping a few handfuls of people directly (and seeing the outcome) than the thousands or millions of unseen individuals who would benefit down the road from any discovery I might make. Understanding that sooner would have been helpful for me. My advisor would likely agree.

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Success in this business isn’t all about the science. There are problems we can’t solve yet, problems we will solve and some we got wrong, possibly for reasons unrelated to science. Leadership also matters. Hoori talked about the need to see people as intersectional beings. There are many factors that make us who we are and influence how we show up.

Good leaders understand “human protocol” and can mobilize people with the idea that they are important.

This is where leaders can make a difference, especially when things go wrong, by keeping the focus on solving the problem.

One thing when you ask anyone is, “Talk to me about a time where you felt really good about something.” And usually it's someone else had done something for them, someone made them feel great, and people never forget that.

Outside of life science, Hoori is exercising her leadership muscle on the Board of Governors of the Human Rights Campaign, making sure there is a place for everyone in society, regardless of differences or background. She has found her purpose and is helping others to find theirs.

Our conversation seemed to be a reflection of exactly the things we were talking about. In the course of that afternoon, I began to understand who Hoori is and why she thinks the way she does because we started the conversation by talking about where she grew up and how she came to the U.S.

What kinds of things keep us from knowing our purpose? As Hoori says, we often find it looking backward at our own stories to figure out the times when we were in the zone and at our best. In the meantime, we put our heads down and do what needs to be done. That is also important, but tough to sustain without purpose. You can write your own story or have it written for you. When you finish writing yours, maybe you can help someone else understand theirs.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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Unlocking the Secrets of the Six-Base Genome

Epigenetics was somewhat vague when I was an undergraduate ( a long time ago). So I was curious to get an update on how we can investigate it more closely and what we are learning. I talked to Tom Charlesworth, Director of Market Strategy and Corporate Development at biomodal, a sequencing technology company focused on epigenetics. Tom explained how modifications beyond the traditional four DNA bases impact gene expression, development, and disease.

What is the Six-Base Genome?

Tom introduced biomodal as a sequencing technology company spun out of the University of Cambridge, focused on the interface between genetics and epigenetics. Their technology goes beyond the traditional four-base genome (A, T, G, and C) by adding two epigenetically modified bases: methylcytosine (5-MC) and hydroxymethylcytosine (5-HMC). This “six-base” approach captures critical modifications that play distinct roles in gene regulation.

5-MC is associated with repressing gene expression, often keeping certain genes “turned off,” while 5-HMC is linked to opening chromatin and activating gene expression. Understanding these modifications provides a more dynamic picture of how our genes are regulated—not just by the sequence of DNA but also by chemical marks that change over time.

Bridging the Gap Between Genetics and Function

The traditional four-base genome gives us an invaluable map of our genetic code, but it falls short of explaining how the same genetic sequence could lead to such diverse outcomes—from development to disease. Epigenetic modifications, like 5-MC and 5-HMC, offer another layer of regulation that’s essential for gene expression.

Tom highlighted research that illustrates the value of this additional information. He mentioned the work of developmental biologist Emily Hodges, who uses the six-base data to study chromatin accessibility during neuronal stem cell differentiation. Emily found that early changes in 5-HMC could predict chromatin opening, an insight that would be invisible if one only looked at 5-MC. This kind of nuanced view helps us understand the precise moments when genes are primed for activation, offering a clearer picture of developmental biology.

Applications From Oncology to Neurology

Tom described three main areas where their customers are leveraging the six-base genome: fundamental research, oncology, and neurology.

In oncology, there’s a growing recognition that multi-omic data—integrating genetic and epigenetic information—can improve cancer detection and treatment response. Tom shared examples of ongoing projects in Canada and Australia, where researchers are using six-base sequencing to better understand the complex dynamics of tumor evolution. By distinguishing between 5-MC and 5-HMC in circulating tumor DNA, they hope to pinpoint which DNA fragments originate from cancer cells, providing a more accurate snapshot of the disease’s state and progression.

The six-base genome also shows promise in neurology. Tom explained that the brain is unique because it has an unusually high level of 5-HMC compared to other tissues, yet we still don’t fully understand why. Early research is exploring this epigenetic landscape to uncover new biomarkers for diseases like Parkinson’s, Alzheimer’s, and various brain tumors. The ability to profile these epigenetic marks could lead to breakthroughs in diagnosing and potentially treating neurological disorders.

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Epigenetics as a “Life Record”: The Developmental and Environmental Context

Here’s another way think about the six-base genome—as a record of a cell’s developmental journey and its responses to the environment. During early development, epigenetic marks guide cells down specific paths, setting up the blueprint for tissues and organs. But later in life, these marks are influenced by external factors like diet, aging, and environmental exposures. This can lead to changes in gene expression that contribute to disease, aging, or even resilience against external stressors.

We also touched on how this concept applies to reprogramming cells, such as in induced pluripotent stem cells (IPSCs). When cells are reprogrammed, they don’t just revert to a blank slate; their epigenetic history still influences how they behave. Tom described work showing that successful reprogramming often involves restoring specific epigenetic marks, essentially rewinding the “epigenetic clock” to a more youthful state.

Rethinking DNA as the Sole Blueprint

Traditionally, DNA has been viewed as the ultimate blueprint for life. But the static genome represents only a portion of the story—it’s the interaction with the adaptable epigenome that truly dictates how our genetic potential is realized. The six-base genome isn’t just a scientific curiosity; it’s another tool for decoding the complexities of life.

Tom describes DNA as the “possibility space” of an organism, but it’s the epigenetic modifications that trim and shape this space into the reality we observe. This nuanced view challenges us to look beyond the sequence and consider the rich layers of regulation that determine who we are and how we function.

I am most excited to learn how environmental conditions like diet and maybe even experience influence the epigenome. As a bacterial geneticist, my basic model is substance A interacts with some regulatory protein to turn a gene on or off. I want to know how the epigenome records my environment. Do the conversations I have had leave detectable marks on the chromosomes in my brain? What would be the mechanism for that? Regardless of the outcome, it’s fun to see the ever increasing depth of our understanding of biology.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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A year ago, Mark Herbert, VP of Biopharma Business Development at Varda Space Industries, joined me on one of the most popular episodes of this podcast. Today, he’s back with some exciting updates on Varda's latest mission, which involved launching a satellite and conducting pioneering drug manufacturing experiments in space. From overcoming regulatory hurdles to making groundbreaking discoveries, Varda’s journey is a glimpse into the future of pharmaceuticals—and it’s happening above our heads.

Launching and Landing: The Mission to Space

Mark began by describing Varda’s June 2023 launch, where they became the first company to send a satellite with re-entry capabilities on a SpaceX Falcon 9 rocket. Varda was one of 35 satellites on the launch, but the only one designed to return to Earth. After orbiting for eight months, the spacecraft re-entered the atmosphere and landed at the Utah Testing and Training Range. The mission took longer than expected due to the complexities of obtaining a re-entry license from the FAA—a groundbreaking process as they were the first to go through it.

While in orbit, they reproduced terrestrial experiments using their custom-designed hardware. One of the key achievements was rediscovering a new form of ritonavir, a widely studied HIV drug, which had experienced stability issues in the past. This discovery and the successful replication of these results in orbit demonstrated Varda’s ability to conduct controlled pharmaceutical manufacturing in space—a major leap forward in drug development.

Navigating Challenges: The Complexities of Space Re-Entry

The mission wasn’t just about science—it was also a complex regulatory and logistical feat. One doesn’t just bring a satellite back whenever and wherever you like.There is a lot of planning required for the re-entry, from coordinating with the FAA to clearing commercial airspace over the Western United States during their 35-minute descent. The spacecraft re-entered the atmosphere at Mach 25, a speed that necessitated strict safety protocols to avoid any conflicts with other air traffic.

Varda’s spacecraft had to endure extreme temperatures during re-entry, reaching three times the surface temperature of the sun. The team licensed the protective shield licensed from NASA, allowing them to maintain a stable internal temperature throughout the process. This ensured that the drug samples remained intact and unchanged during their return to Earth—a critical validation for future missions.

Small Capsule, Big Impact: The Benefits of Space Manufacturing

The whole purpose of manufacturing in space is to solve formulation challenges. In microgravity, Varda was able to manipulate ritonavir’s crystal forms in ways that are impossible on Earth. Beyond the chemistry, the technical and logistical challenges of this mission, honestly, blow my mind. The spacecraft’s small size belies the complexity: inside, the “huggable” capsule maintains the temperature within a one-degree range, even while moving from sunlight to shadow multiple times every day in orbit.

To ensure they could isolate the effects of microgravity, the team included controls—different forms of ritonavir that were stable on Earth. This careful experimental design allowed Varda to confirm that the re-entry process did not alter the drug samples, proving that drugs manufactured in space could be brought back without compromising their integrity.

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Looking Forward: Expanding Horizons in Space-Based Drug Manufacturing

Varda’s success presents new possibilities in space-based manufacturing. Currently, their focus is on small molecule crystallization. By 2025, Varda plans to expand into solvent-based applications, allowing them to test a broader range of small molecules. By 2026, the company hopes to launch biologics—complex molecules used in cutting-edge therapeutics that often face formulation challenges on Earth.

Mark spoke about how Varda’s work could eventually transform biologics manufacturing. For instance, many biologics are currently restricted to intravenous administration because of stability issues tied to Earth’s gravity. Microgravity could help overcome these limitations, enabling new formulations that are more convenient and accessible to patients.

Hypergravity: A New Tool for Drug Development

How does one determine that gravity influences the crytallization of any particular molecule? Draw the curve for the effect of increased gravity and extrapolate backward. Varda has developed a hypergravity platform at their El Segundo facility, which allows them to study the effects of increased gravity on pharmaceutical processes. By simulating up to 5G conditions, Varda is able to screen molecules and processes terrestrially, providing valuable data before investing in the high costs of spaceflight. This approach not only maximizes the chances of success in orbit but also adds a new dimension—literally—to pharmaceutical research.

Hypergravity serves as a negative dataset, helping researchers anticipate how microgravity might alter their processes. By tweaking the “gravity knob,” Varda can better design experiments that leverage the unique conditions of space to create novel drug formulations.

Future Vision: Monthly Missions and New Frontiers

Varda’s ultimate goal is to conduct space missions on a regular cadence, with plans to have quarterly launches through 2026 and the potential for monthly missions if the demand arises. Their focus remains on pharmaceuticals, particularly small molecule crystallization and biologics. Varda’s platform is designed to make space accessible for drug development, offering new tools to researchers looking to solve problems that Earth’s 1G environment cannot.

Beyond the immediate applications, Varda’s work represents a paradigm shift in how we think about drug development. As Mark pointed out, this technology could enable the creation of entirely new therapeutics that would be impossible under Earth’s gravity. It’s a thrilling prospect—one that could redefine the future of medicine and bring treatments manufactured in orbit into everyday healthcare.

Final Thoughts

Varda’s journey is not just about the technology—it’s about opening up new possibilities for researchers and patients alike. As someone who grew up during the space age, I never imagined that some day, we could be receiving treatments that were made in space. This is just the beginning, and Varda is leading the way into a new era of drug manufacturing.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

If you appreciate this content, you likely know someone else who will appreciate it too. Please share it with them.

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I spoke with Brian Thomson, HR consultant and leadership coach, about leadership, hiring, retention, and culture in early-stage life science companies. Brian’s practical insights offer a roadmap for building and sustaining a thriving company from the ground up.

The Importance of Modeling the Right Behaviors

From the beginning, Brian emphasized a key concept: intentionality. In his view, leadership is not just about making the right decisions; it's about being intentional in how you model behaviors and build culture within your organization. This is particularly crucial in the fluid environments of startups, where the pace is fast, and the stakes are high.

He pointed out that it’s not about whether a particular culture is right or wrong—what matters is that it’s intentional and authentic. This intentionality shapes hiring, retention, and performance management, all of which are crucial for the long-term success of a company. He argued that strategic planning should not just be a buzzword but a disciplined practice that informs every decision, from the type of culture you want to build to the kind of people you need to hire.

The Rule of Threes: Core Competencies in Startups

Brain has a rule of threes when it comes to what founders of early-stage life science companies need to focus on: disruptive science, a strong core team, and a high degree of intentionality around culture. While it’s easy for founders to get fixated on the science—because it’s their passion and it’s measurable—the other two elements are just as critical.

This resonated with me, especially considering how often we see startups with groundbreaking science but no clear direction on how to build a team or a culture that can sustain the business. The science might make headlines, but it’s the culture and the team that will drive the long-term success of the company.

Strategic Planning: More Than Just a Process

Brian’s sees strategic planning as more than just a process; it’s a foundational practice that lends clarity, focus, and discipline to an organization. He mentioned that in his role as a coach, he often works with early-stage organizations to develop a strategic plan that is as concrete as possible. The goal? To ensure that at any given moment, everyone in the organization knows the top priorities.

Be very disciplined. Be very focused. Make your plan. Make it as concrete as possible. At any given time, if I go and ask two of your employees, anywhere in the organization, “What are the number one and what's the number one and what's the number two topmost priority that the company has at that moment?”

If they can't answer that, it indicates to me that you haven't done a good enough job of being very clear and being very focused.

This approach to strategic planning directly feeds into the hiring process. By being clear on the values and culture you want to create, you can ensure that the people you bring into the organization are aligned with those goals. Hiring isn’t just about finding people with the right skills; it’s about finding people who will thrive in the specific culture and environment of your company.

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Hiring: An Internal Competency, Not a Task to Outsource

Many startups make a mistake by outsourcing their hiring processes. Hiring is too critical to be left to an external agency, especially in the early stages of a company’s development. The first 10 to 15 hires set the tone for the entire organization, and if those hires don’t align with the company’s culture and values, it will create long-term issues.

Brian argued that hiring should be an internal competency, with the leadership team taking an active role in the process. This ensures that everyone who joins the company is fully aware of the environment they’re stepping into, whether it’s a messy startup with lots of ambiguity or a more structured environment.

The Value of Transparency in the Hiring Process

Brian shared a story from his time as Chief People Officer for a small biotech spinout during the Great Resignation. Despite the mass exodus of employees across industries, his organization navigated that period with zero regrettable turnover and zero R&D turnover. The secret? Radical transparency.

From the first conversation with potential hires, Brian and his team were upfront about the realities of the company’s environment. This honesty helped attract the right people—those who were excited about rolling up their sleeves and getting their hands dirty—and it also helped filter out those who weren’t a good fit. Brian emphasized that transparency in the hiring process not only attracts the right talent but also helps candidates self-select out if the environment isn’t right for them.

Retention: A Balancing Act

When it comes to retention, 100 percent retention isn’t the goal, nor is it ideal. A little turnover can be a good thing, as it brings in fresh perspectives and prevents complacency. However, the key is to ensure that the turnover is natural and doesn’t result in the loss of essential talent.

Brian talked about the importance of building a talent engine within the organization—an environment where employees are developed and prepared for their next roles, whether within the company or elsewhere. This approach not only boosts retention but also enhances the company’s reputation as a place where people can grow and develop their careers.

The Power of a Coaching Culture

Finally, we talked about the value of creating a coaching culture within an organization. Brian argued that this is one of the most effective ways to develop talent and increase engagement. Instead of relying on traditional training programs, which can be expensive and often ineffective, he advocates for on-the-job learning and continuous development through coaching.

In a coaching culture, managers act as mentors, helping their employees navigate their careers and develop the skills they need to succeed. This not only empowers employees but also creates a more dynamic and engaged workforce. This approach doesn’t require a huge budget—it’s more about a shift in mindset and behavior.

Final Thoughts: Intentionality Is Key

As we wrapped up our conversation, the theme that kept coming back was intentionality. Whether it’s in strategic planning, hiring, or building a coaching culture, being intentional about your decisions and actions is crucial for the success of any startup. The best companies are those that are clear about who they are, what they value, and where they’re going.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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When I first heard about hydrosomes, I honestly thought, “That can’t be real.” Hydrosomes are microscopic bubbles that stay in water without coalescing and rising to the surface. Then I met Nick Jackowetz, the Senior VP and Principal Scientist and the team from Hydrosome Labs at BIO 2024 in San Diego. They answered my questions and I invited Nick to be a guest on the podcast to share the story with you. Hydrosomes are also known as ultrafine bubbles, and they have incredible potential for many applications. If you’ve ever wondered how something as seemingly simple as a bubble could revolutionize fields like agriculture, cosmetics, and even fermentation, then this episode is definitely one to tune into.

Nick started by breaking down the basics of what makes these ultrafine bubbles so unique. We’re talking about bubbles so small that they’re measured in nanometers—around the size of a virus particle. To put that into perspective, imagine a champagne bubble, which is already tiny to the naked eye. Now, pack a trillion of these ultrafine bubbles into that single champagne bubble, and you start to grasp just how small we’re talking about. It’s mind-boggling, right? These bubbles don’t even float like the ones we’re used to; they stay suspended in solution because they’re not governed by the same buoyancy rules. This leads to some pretty wild implications for how they can be used.

Even the physics of these bubbles changes at such a small scale. For instance, the pressure inside these bubbles can reach up to 30 atmospheres, which is 30 times the pressure we experience in our everyday environment. This intense pressure doesn’t make them pop as you might expect; instead, it opens up new possibilities for gas delivery in various applications. Imagine being able to deliver oxygen directly to cells in a way that’s more efficient and targeted than ever before. Because the bubbles have an enormous collective surface area, believed to be charged, the team is looking at how they attract and move nutrients around.

While the concept has been around since the 1980s, the science has only really taken off in the last decade. The early research mainly came out of Japan, where these bubbles were first studied in applications like agriculture and aquaculture. It turns out that these tiny bubbles can help grow plants more effectively by delivering nutrients and gases directly to the roots.

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I was curious to learn about potential applications. One area that’s particularly exciting is their potential in consumer packaged goods, especially in cosmetics. Imagine being able to deliver active ingredients like vitamin C or retinol more effectively into the skin without the need for added chemicals. That’s exactly what these ultrafine bubbles can do. By improving how these ingredients penetrate the skin, we could see a new wave of cosmetic products that are not only more effective but also safer for consumers.

We didn’t stop there. The potential for these bubbles in the beverage industry is another game-changer. Picture your favorite sparkling water, but instead of regular carbonation, the drink is infused with ultrafine bubbles. These tiny bubbles could enhance flavor profiles, reduce the need for added sugars, and even change the overall sensory experience of the drink. Nick mentioned ongoing research into how different gases inside these bubbles—like nitrogen or nitrous oxide—could create new taste sensations and improve the mouthfeel of beverages. The idea that you could enjoy a sweeter taste with less sugar is not just intriguing; it could have significant implications for the health-conscious consumer market.

For life sciences, the interesting application is in fermentation processes. These bubbles could play a crucial role in making fermentation more efficient, which is especially important as industries increasingly rely on fermentation not just for food and beverages but also for producing pharmaceuticals, enzymes, and other valuable compounds. The idea that you could boost the growth and productivity of cells in a fermentation tank just by adding these bubbles is something that could have wide-reaching benefits, particularly for biotech companies looking to optimize their production processes without the need for expensive new infrastructure. To be clear, it’s not just putting bubbles in the media. The effect, in addition to transporting oxygen, is enhanced by how the hydrosomes attract and transport nutrients.

One of the most exciting projects Nick mentioned is a preclinical study on how these bubbles might affect the gut microbiome. Early evidence suggests that drinking water infused with ultrafine bubbles could positively impact gut health, potentially altering the microbiome in ways that benefit overall health. This could lead to a whole new category of wellness products that deliver health benefits just by changing the way water is consumed.

Of course, there are still challenges ahead. One of the biggest hurdles is accurately measuring these bubbles, especially as they get smaller. The equipment needed to detect and analyze these tiny bubbles is still catching up with the science, which makes it difficult to fully understand their potential. But as technology advances, we can expect to see more precise tools that will allow scientists like Nick to push the boundaries even further.

Whether it’s improving the efficiency of fermentation, enhancing the delivery of cosmetic ingredients, or even opening up new frontiers in drug delivery and gut health, ultrafine bubbles are something to keep an eye on. I’m excited to see where this technology goes next, and I hope to have Nick back on the podcast in the future to update us on the latest developments. I’m particularly interested in what RNA analysis might tell us about how gene expression might change in cells grown in hydrosome-infused media. Stay tuned. But for now, enjoy the episode.

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Issa Kildani is the founder and principal consultant at Ambrosia Ventures. Our conversation centered on his journey from metabolic and cardiovascular research into the consulting world. Even if you are not planning on becoming a consultant, one can learn a lot from his approach to acquiring skills and building relationships with customers.

Transitioning from Research to Consulting

You don’t need an MBA to become a consultant. I’m sure it helps in some areas, but there is a lot to be said for rolling up your sleeves and figuring it out. Issa started his career in metabolic and cardiovascular research as a graduate student at Vanderbilt University. He eventually realized while working at startups that his longer-term goal was to help people and companies rather than stay at the bench.

Transitioning into consulting requires a diverse skill set, including project management, strategic thinking, and analytical skills. There was a lot to learn but he saw a path to make it happen by being self-driven and inquisitive, eager to learn and explore new areas, one of which was strategic thinking.

Strategic Thinking

I’m always interested in what it means to think strategically. Issa shared his experience at a neurofeedback and biofeedback startup in Michigan. Working closely with the CEO, he learned the importance of strategic thinking by understanding different markets and thinking ahead about potential expansions. With multiple opportunities for expansion, how do you choose where to focus? Issa considered what were the emerging markets and where that would put them 5 years down the road.

So you want to jump on it just now, you know, like the AI and machine learning, things like that in drug discovery.

These are hot topics, but which one is going to take you a lot further in the company and what's your long-term vision? Does it align to your long-term vision? Do you plan on selling five years from now or do you plan on growing to a bigger company? Those are the kind of decisions that play into it and help them align to that strategic goal.

Understanding Industry Dynamics

Beyond understanding markets, one also needs to understand how the industry works. There are many components to the life science ecosystem. Issa talked about the unique challenges faced by biotech companies, such as funding issues, regulatory hurdles, and clinical trial recruitment problems.

In the early stages, refining their pitches and helping them communicate their value more effectively is a key for success. At later stages, the focus might be more on regulatory issues or broader strategic goals. My overall impression is that Issa is very good at talking to potential customers and figuring out in detail what their current challenges are. That is a skill in itself.

Building Relationships and Winning Business

Issa takes a very long approach to building relationships and winning business. He emphasized understanding clients' needs, being genuinely interested in their success, and maintaining long-term relationships. It can take a long time to land a client. Issa’s process involves regular check-ins, understanding the client's challenges and milestones, and providing insights so potential clients can understand the value he brings to help them achieve their strategic goals.

The Value of Mentorship

We talked about the value of mentorship. He described how his mentor, who was also his boss, played a significant role in his development as a consultant. By being upfront about his desire to learn and improve, Issa received invaluable guidance and feedback that helped him fine-tune his skills. The key thing here was simply to ask. Sometimes this may seem like a bold move. “Can I really ask a senior executive to be my mentor?” (It’s not the only way but as an older parent, I can tell you nothing gets your attention faster or makes you feel better than when a young person asks for your advice.)

Even if they don’t have time to be your mentor, it will put you on their radar as someone who is looking to do more for the company. You can’t lose.

If you take away nothing else from this message, being curious and asking for advice will take you a long way regardless of your goal. I challenge you to find some one and talk to them this week.

Opportunities and Challenges in Smaller Biotech Ecosystems

Issa is based in a smaller biotech ecosystem, Ann Arbor, Michigan. While smaller ecosystems may lack the resources and investment opportunities of larger hubs like San Francisco or Boston, they offer a chance for a consultant to make a significant impact. Add to that the possibility of connecting with larger hubs and applying those insights locally, you can make a difference to foster growth and innovation in these emerging ecosystems.

The Broader Implications of Consulting

From my own experience, the best thing about being a solopreneur or consultant is the opportunity to see what’s happening across all of life science. If you are the person who feels that life at the bench is too slow or too narrow, this may be the path for you. I enjoy the feeling of helping others in life science directly. I may not find the cure that affects millions but I get to build relationships and see the value I bring t people I actually know. At the same time, I know they are helping millions.

For anyone considering a career in consulting Issa's journey offers valuable lessons. Check out Issa's website and blog for more insights and resources.

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In this episode, I spoke to Cassandra Rix, the owner and chief leadership coach at The Resonance Coach. Our conversation centered around understanding individual motivations and expectations within group efforts, especially in the context of company acquisitions. I think you will find the insights applicable to many situations at work and at home.

Cass's Background and Expertise

Cass has spent over 20 years working with businesses either in the process of being acquired or on the tail end of an acquisition. She specializes in service agencies selling expertise and time, such as consultancies and communication specialists. Her focus now is on helping founders looking for investment or seeking an exit strategy, and the businesses interested in investing in them. She believes that many acquisitions fail despite thorough due diligence because the underlying human motivations and behaviors of the individuals involved aren't fully understood.

Understanding Motivations

While people may outwardly agree on a common goal, such as selling a company, their underlying reasons can be very different. These differences will show up during times of significant change (after the investment or acquisition). Everyone’s motivations are influenced by their own personal experiences and beliefs, which drive their decisions and behaviors.

Cass's own interest in understanding motivations stems from her background in sales and marketing, where she worked with buyers and wanted to comprehend why people made specific purchasing decisions. Our beliefs drive our behavior, and it's crucial to recognize that we often make assumptions about others' motivations based on our own perspectives. We expect them to act the way we would. I’d like to look deeper into this in future episodes.

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The Challenges of Assumptions

It’s risky to assume that everyone's motivations are similar. Cass used the analogy of wearing someone else's shoes – just because you're in their shoes doesn't mean you understand their journey. This is especially relevant in business settings, where assuming that all founders or team members share the same motivations can lead to conflicts and dysfunction.

Cass illustrated this with an example of how misaligned expectations can derail an acquisition. For instance, if one founder decides they have enough financial security post-acquisition and leaves, the remaining team dynamics can be severely disrupted:

So the things that fall apart there is, well, we all think we've agreed to sell this business or invest, have investment in this business so that we can carry on.

What does carry on mean? What if that means that one person has generated enough income in the acquisition process, not to need to stay throughout the earn-out. And suddenly you go from a leadership team or founding team of four to three or three to two. What if the other two people in that business were beautifully balanced by that third individual?

And so the relationship that they're left with is dysfunctional. They don't really like each other. They don't know how to communicate with each other. They've never had to without that third person as a foil. And probably the most flawed thing is the assumption that the rest of the business, whether you're talking about another twenty people, fifty people or thousands of people, the assumption that those people don't know.

This scenario can lead to conflicts and a decline in business performance, which affects everyone's livelihoods.

The Role of Vulnerability and Communication

As individuals climb the corporate ladder, they often create personas that might not align with their true selves. This can lead to exhaustion and dissatisfaction, as they try to maintain an identity that doesn't reflect their genuine motivations.

Cass said that vulnerability is not a weakness but a strength. When leaders and team members are open about their true motivations and feelings, it fosters understanding and empathy. She shared that when people reveal their authentic selves, it often leads to relief and better teamwork. This openness can help teams navigate change more effectively, as everyone understands each other's perspectives and can support one another.

Practical Implications and Real-World Examples

Cass pointed out how small habits and cultural norms, such as which hand you use to hold a fork, can shape our perspectives and lead to emotional attachments about how things should be done. If we feel that strongly about cutlery, imagine the intensity of our feelings about approaches to business where the stakes are much higher.

Translating this to business settings, she explained how deeply ingrained beliefs about success and behavior can affect decision-making and team dynamics. Differing motivations for making money can lead to misunderstandings. Some people might want to make money to retire early and spend time with family, while others aim to leave a legacy or achieve a prestigious position. These differing goals and expectations can create friction if not openly discussed and understood. Whether you are the acquiring/investing company or the company being invested in, understanding these things can make a huge difference in your long-term happiness (money, legacy…).

The Courage to Be Disliked

Our conversation concluded with a serious reflection on the importance of self-awareness and the courage to be true to oneself. Cass recommended the book "The Courage to Be Disliked," which explores the concept that what others think of us often reflects their own beliefs and insecurities. She encouraged leaders and individuals to focus on their own motivations and well-being rather than constantly worrying about others' opinions.

Her final thought: "The most liberating two words in the English language are 'let them...'" Letting go of the need for external validation and embracing one's true self can lead to greater fulfillment and success, both personally and professionally.

Let them.

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In my recent conversation with Larry Kaplow, we talked about brand strategy in the life sciences, why, when and how.

Defining Brand Strategy

We kicked off the discussion with Larry describing the danger of not having a strategy. In a world overloaded with information, a brand has to cut through the noise and make its value clear. Even if a company has groundbreaking technology, it’s easy to be overlooked if the brand strategy isn’t aligned with the audience's needs. People—whether researchers, investors, healthcare professionals, or patients—are primarily concerned with their own interests.

A brand is the sum of all associations that audiences have about a company. This definition, which he credited to Uli Applebaum, highlights that every touchpoint, from sales calls to investor decks, contributes to building these associations. As a result, a deliberate and intentional strategy is crucial for creating consistent and meaningful connections with the audience.

Simplifying the Brand Message

Larry argued that while nuances might change, the core brand message should remain consistent. He likened it to owning a space in the audience's mind—when they think of your company, they should think of one defining characteristic. This consistency makes it easier for the audience to remember and relate to the brand.

Here is a real-world example. Thermo Fisher faced the challenge of convincing diverse audiences to switch from traditional methods to mass spectrometry in toxicology. By identifying two primary audience groups—those looking to grow their business and those pushing the boundaries of research—they could tailor their brand message to resonate broadly. This approach allowed them to lead with a brand-focused message about pushing toxicology forward, which connected with all their target audiences. It took doing some homework to get there. This involves understanding the audience's motivations, barriers, and pain points.

Larry shared another example from a different company in the medication management space in hospitals. The initial tech-focused message wasn't resonating. Hospitals were resistant to new technology because new tech often means a lot of work. By shifting the narrative to focus on patient and hospital safety, they aligned their message with what was truly important to their audience. This not only made the brand message more relevant but also helped position the technology with respect to existing budgets for safety initiatives.

Personality Archetypes for Commoditized Products

Brand personality archetypes can differentiate a company in a commoditized market by mirroring what's important to them or by representing something they aspire to be. For instance, McDonald's uses the "Innocent" archetype, creating a sense of happiness and nostalgia. In contrast, Burger King has struggled with consistency, resulting in a less impactful brand presence. As I look at it, BK is focused on the burger, McDonald’s is focused on the experience.

Crafting a Long-Term Brand Vision for Investors

If we think about smaller biotech firms, even prior to commercialization, crafting a long-term brand vision is crucial, especially when communicating with investors. Larry noted that investors are people too, influenced by compelling narratives. Investors looking for long-term returns want to see a cohesive brand strategy that promises sustainable growth and market relevance. A strong brand story in the investor deck can be as important as the technical details. The other lesson here is knowing what kind of investor you have or are looking for.

Brand Architecture - Balancing Messages Across Different Levels

We wrapped up the conversation by discussing how to balance messages across different levels—company brand, technology, and specific applications. Larry differentiated between brand architecture and communication structure. Brand architecture involves categorizing and integrating different brands, especially post-acquisitions, whereas communication structure focuses on maintaining a consistent brand story across various touchpoints.

He highlighted the importance of having a comprehensive brand position that can be communicated at all levels, from the high-level mission and vision to the detailed technical aspects. This consistency not only strengthens the brand but also adds credibility and value over the long term.

Final Thoughts

Larry’s insights were a masterclass in brand strategy, particularly for the life sciences sector. His emphasis on consistency, relevance, and the importance of doing the homework provides a clear roadmap for any company looking to strengthen its brand. For me, the takeaway was clear: a well-defined and consistently communicated brand strategy is essential for cutting through the noise and making a lasting impact. And for those in the biotech space, understanding and addressing the needs of all your audiences, including investors, is key to building a strong, sustainable brand.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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At BIO2024, I spoke Sam Clark, CEO and founder of Terran Biosciences, about their development of new long-duration dosage forms for the treatment of schizophrenia . We discussed the development of prodrugs, the potential of psychedelics, and the journey of founding a biotech company.

The Genesis of Terran Biosciences

Sam's journey into biotech was personal. Growing up around friends and family members with severe mental illnesses like bipolar disorder and Alzheimer's disease, he saw the limitations of existing treatments. Through his studies at MIT and Columbia, he recognized the slow pace of development and the significant side effects of available medications. Existing treatments for mental illnesses have many unpleasant side effects from cause weight gain to Parkinsonian symptoms and hormonal disruptions. All of that led to his decision to found Terran Biosciences hoping to transform the standard of care.

Terran's Pipeline

Terran's lead asset, TerXT, is a novel combination of prodrugs of xanomeline and trospium, compounds that have been around for a long time, but with less than ideal pharmacokinetics. They also have Idazoxan XR, an adjunctive treatment for schizophrenia, and several new forms of psychedelics like psilocybin and MDMA with differentiated pharmacokinetics aimed at making these treatments more accessible and affordable.

Sam explained the significance of prodrugs in their approach. Unlike simple reformulations, prodrugs are entirely new compounds created by attaching a side chain to the original molecule. This attachment improves pharmacokinetics, allowing for more effective absorption and longer-lasting effects. For example, the older compounds xanomeline and trospium, which need to be taken twice daily, have been modified into prodrugs that can be administered once daily or as long-acting injectables with multi-month durations. This innovation not only simplifies the regimen for patients but also leverages the FDA's accelerated 505(b)(2) pathway, potentially bringing these new treatments to market faster.

Overcoming Development Challenges

Creating effective prodrugs is no small task. Sam described the extensive process, involving a team of world experts and over 200 FTE chemists working tirelessly. They designed over 10,000 prodrugs, synthesized 700, and conducted 500 preclinical studies to refine their approach. This massive undertaking, though challenging, has led to promising results.

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The Potential of Psychedelics

I also wanted to explore psychedelics, a field that has generated significant interest in recent years. Terran is developing new forms of MDMA, psilocybin, and 5-MeO-DMT, aiming to improve their pharmacokinetics and make these treatments more accessible. Sam highlighted MDMA's potential, currently under FDA review for treating PTSD, with a decision expected soon. (Right after we spoke, the FDA advisory panel recommended rejecting approval for MDMA. The decision has not been made yet.) By creating new forms and leveraging the 505(b)(2) pathway, Terran aims to overcome patent barriers and ensure these treatments are affordable.

Insights into Brain Function

I am particularly curious about anything we can learn about neurobiology from studies around these therapeutic compounds and psychedelics. Here is the challenge: Psychedelics, for example, act on multiple receptors. Teasing out different pathways in the brain is complicated. Functional MRI studies of people undergoing psychedelic trips show reproducible changes in brain pathways, suggesting potential mechanisms but the circuitry is complicated. There are no simple answers yet.

The Journey of a First-Time Founder

I asked Sam about his experience as a first-time founder. Terran's success is in large part due to its corporate structure, modeled after fast-moving Silicon Valley companies. By avoiding traditional hierarchical structures and instead utilizing a flat organization with world experts leading sub-teams, Terran has managed to solve complex problems efficiently.

Team building has been essential to Terran's achievements. Sam's approach involves creating specialized teams for different facets of a problem, ensuring a comprehensive and collaborative effort.

“Workflows” for the Win

I have seen a pattern in several interviews recently. Changing a process can have as big of an effect on solving a problem (and creating success for a company) as developing a new product. In this case, it’s a bit of both. The problem being solved by TerXT is the patient regimen. Prodrugs with longer-duration pharmacokinetics make adherence easier for the patient. At the same time, I appreciate the enormous amount of development effort that went into creating those prodrugs. A different approach to assembling teams and managing them is also a significant change in the workflow that will have an impact.

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In this episode, recorded at BIO2024 in San Diego, I had the pleasure of speaking with Martin Brenner, the CEO and CSO of iBio. Our focus was the challenges and innovations in developing antibody-based therapeutics, particularly through their AI-driven discovery platform. Martin shared his insights into the current landscape and future directions of antibody therapies, touching on key aspects such as target selection, engineering challenges, and the role of AI in optimizing therapeutic antibodies.

The Challenges of Developing Antibody Therapies

Antibodies have revolutionized therapeutic approaches over the past two decades, with numerous successful drugs already approved. However, as Martin pointed out, we've now picked much of the low-hanging fruit. The target space is becoming increasingly complex, with most approved antibodies focusing on a small set of targets. For instance, about 40% of all approved antibodies target PD-1. While anyone can now develop a PD-1 antibody, the real challenge lies in identifying and effectively targeting novel, more complex antigens.

Another significant challenge Martin highlighted is improving the safety and therapeutic window of antibodies. Highly potent antibodies, particularly in oncology, can cause severe side effects. Enhancing the safety profile while maintaining efficacy is a critical area of ongoing research.

Potency vs. Therapeutic Effectiveness

It turns out that the best-binding antibody isn't always the most effective therapeutic. For example, in bispecific molecules, where one arm binds to a tumor cell and the other to an immune cell, the tightest binding isn't always ideal. Overstimulation can lead to cytokine release and toxicity. Instead, finding the right balance in binding characteristics is crucial to avoid adverse effects.

Traditionally, the goal was to find an antibody that binds quickly and stays bound indefinitely. However, this might not always be the best approach. Understanding on and off rates of antibodies is important for delivering the desired response. Novel technologies now allow us to screen for these characteristics early, optimizing therapeutic effectiveness and safety.

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iBio's AI-Driven Platform

iBio focuses on generating small, high-dimensional data sets to train their models. Their technology starts with an epitope steering engine, which creates engineered epitopes that precisely reflect the surface of target proteins. This innovative approach allows for targeted antibody development, even against challenging targets.

For example, iBio can create PD-1 agonists that activate receptors instead of merely blocking them. This capability opens up a new realm of possibilities in antibody therapies, particularly for complex and hard-to-target proteins.

Discovering New Biology Through Targeting

One of the most exciting parts of our conversation was discussing how iBio's platform not only targets known regions of proteins but also helps uncover new biological functions. By addressing the entire protein surface with engineered epitopes and screening them, iBio can identify antibodies that reveal new aspects of a protein's role. This approach not only enhances therapeutic development but also contributes to our broader understanding of biology.

Smart Antibodies and Masking

Martin explained their concept of smart antibodies, which are designed to be inactive until they reach the disease tissue, like a pro-drug. This masking technique, particularly useful in tumor biology, involves connecting a mask to the antibody with a linker that is cleaved off by enzymes in the tumor environment. This method allows for higher precision in targeting and reduces side effects by ensuring the antibody is only active in the intended tissue.

For example, targeting the epidermal growth factor receptor (EGFR) can be problematic due to its expression in the skin, leading to side effects. Using a masking approach, iBio can target EGFR in tumors while minimizing impact on the skin, potentially allowing for higher dosing and improved efficacy.

Optimization and Rapid Development

iBio's approach to optimization sets them apart. Traditional methods like phage display create large libraries of molecules but require significant time to identify and develop drug-like characteristics. In contrast, iBio uses machine learning to create localized diversity in a smaller, more manageable library. This method mimics the diversity of large libraries while maintaining high developability, drastically reducing optimization time from months to weeks.

Focus Areas and Future Directions

I asked Martin about what areas they are focused on with their pipeline. iBio is currently focusing on cardiometabolic and immuno-oncology areas. Their preclinical pipeline includes promising targets in immuno-oncology, with plans to partner these developments strategically. Additionally, Martin's background in diabetes and obesity research has driven their pivot into cardiometabolic diseases, aiming to develop drugs for those indications that avoid muscle and bone loss, crucial for the aging population.

Other molecules, single chain antibodies from sharks or human heavy chain alone may eventually form the basis of new therapies for more complex targets.

For me, the attraction of this approach is the broader look at the target molecules to survey all the possibilities beyond developing a small molecule that fits in a binding site and the benefit of everything we learn about biology that may lead to new discoveries in the future.

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In this episode of CC Life Science, I had the pleasure of hosting Neil Spooner, the founder and chair of the Patient-Centric Sampling Interest Group (PCSIG). Neil shared his insights into patient-centric sampling and its potential to revolutionize healthcare and clinical trials.

Introduction to Patient-Centric Sampling

Neil began by explaining the concept of patient-centric sampling, which prioritizes the patient's needs over traditional methods that often inconvenience them. Traditional methods like venous phlebotomy or standard urine collection are designed with the analytical labs, clinicians, and logistical chains in mind rather than the patients. For patients, that means they have to have to take time out of their day, possibly missing work or school, to visit a clinic for sampling.

This is an added burden for patients, particularly those with chronic conditions requiring frequent testing. I shared the example of a family member, who had leukemia and needed to visit the hospital twice a week for tests. This was a significant strain not only on her but also on family members. Neil explained that patient-centric sampling offers a more convenient alternative, allowing samples to be collected at a time and place that suits the patient, whether at home or any other location.

Benefits for Clinical Trials and Healthcare

I was curious about what this approach would mean for clinical trials and healthcare. Neil pointed out that easier and more flexible sampling methods could improve patient recruitment and retention in clinical trials. It could also help gather data that is currently difficult to obtain, such as samples taken during a clinical event like a migraine. This approach not only enhances data collection but also broadens the patient pool to include those who might otherwise find it difficult to participate due to geographical or physical constraints.

Current Research and Stakeholder Engagement

Bring this concept to life isn’t just about workflows and analytical science. Marketing plays a big role as well. And I don’t just mean promotion. I mean understanding the needs of everyone involved. Neil explained that the PCSIG is actively engaging with various stakeholders to understand their concerns and benefits regarding patient-centric sampling. They are doing market research to identify key stakeholders in different use cases, such as clinical trials, therapeutic drug monitoring, diagnostics, and drug testing in sports. By having conversations with these groups, PCSIG aims to educate and address their concerns while identifying potential benefits and gaps in the current system.

Addressing the Resistance to Change

One of the significant challenges discussed was the resistance to change within the healthcare and clinical trial sectors. Neil ponted out the importance of finding passionate individuals within organizations who can champion the adoption of new sampling methods. These individuals need the support of their superiors and a network of like-minded professionals to overcome the inevitable hurdles that come with implementing new technologies.

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Technological and Logistical Innovations

We spent a little bit of time discussing sample formats and logistics. Currently labs doing routine analyses operate large analyzers that are set up for huge volumes of a standard set of tubes. Neil provided insights into the technological and logistical innovations required for patient-centric sampling. He mentioned various devices that can collect blood samples through finger pricks or from other body parts like the arm or thigh, often producing dried samples that can be mailed to labs. The COVID-19 pandemic demonstrated the feasibility of such home-based testing, showing that logistical systems can adapt to handle new sampling methods.

Impact on Drug Testing in Sports

I was surprised to hear about the application of patient-centric sampling in drug testing for sports. Chain of custody is crucial here to ensure the integrity of the samples. Neil explained that while athletes would still need to be witnessed during sample collection, blood sampling could be a more comfortable and less invasive (in terms of witnessing) option compared to urine sampling. Ultimately it’s likely to be complementary to urine testing. It does bring benefits for the athlete. It can make ongoing monitoring more practical for providing valuable data for athletes' training and health.

Sponsorship and Future Plans

Finally, we touched on the PCSIG's funding and sponsorship. Neil explained that the organization aims to keep sponsorship levels low to encourage broad participation, including startups and companies from less affluent regions ensuring that no one sponsor has outsized influence on the direction of the group. Sponsors benefit from visibility on PCSIG's platforms and involvement in the sponsors' advisory group, which helps shape the group's activities. Sponsors recently voted on nine proposed activities, and the top two priorities would soon be announced.

Reducing the burden on patients needing frequent testing alone makes this effort worthwhile in my opinion. The benefits for recruitment and retention in clinical trials and drug/health monitoring in sports are icing on the cake.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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David Ormesher, the CEO of CGLife, and I had a conversation about communicating science broadly to the public and within the scientific community. David went immediately to the power of storytelling in making science approachable. He highlighted the hero’s journey, the narrative arc used in literature and film, as a powerful tool to engage various audiences, whether they are scientists, physicians, patients, or the general public.

That narrative of the hero’s journey applies to patients and caregivers as well as scientist looking for breakthroughs. Not only can it help demystify science but it can also create emotional connections that make complex scientific concepts more relatable and engaging for the general public.

I think it’s important for society to understand and appreciate the work of scientists as well as understand how science is done especially when the details might not seem immediately relevant to them. By highlighting the human element and the persistence required in scientific exploration, we can help the public understand that scientists are ordinary people with an extraordinary commitment to solving complex problems. This can shift the public perception from seeing science as something inaccessible to recognizing it as a collective effort aimed at improving lives as well as simply appreciating the universe we live in.

What does this mean for life science marketers? David gave us a complete primer on the journey of a new medical product from inception to market launch. I was roughly aware of the roles various teams play in bringing a new drug to market. He covered the spectrum and filled in the details for me. Market insight, brand development, and market shaping involves understanding the needs of both physicians and patients, conducting extensive research, and building awareness through unbranded communications. As has come up several times over the years on this podcast, the importance of early engagement with healthcare professionals and patients before a product is approved can not be overstated. It helps ensure that by the time a drug is approved, there is demand and a well-informed audience.

It's that ability to personalize content that is also key. And this is where not only the agencies of the future that we need to help shepherd these products from clinical development through approval, launch and growth, they need to understand the science. They also need to understand that digital component of targeting, segmentation, (and) personalization.

Data and analytics play a critical role in this process. By capturing and analyzing data from the early stages, companies can refine their marketing strategies, personalize content, and measure the effectiveness of their campaigns. This data-driven approach ensures that the communication is relevant and impactful, reaching the right audience with the right message at the right time.

One aspect I found particularly interesting was the preparation for day zero – the day the FDA approves a new drug. David described having all the marketing materials ready, including a “day one” website and direct email marketing. At the same time, a launch team needs to be prepared to very quickly make any changes required for labeling, etc. when the approval comes along.

Finally, we touched on the challenges of educating physicians about the latest medical advancements. For a doctor who completed medical school 20 years ago, and has been seeing patients all day every day, keeping up to date is near impossible. Highly targeted communications including bite-sized, relevant, and easily accessible content, such as short video interviews and 3D animations can help physicians keep up with the latest developments.

As marketers, there is plenty of work to be done to keep both the public and people in the healthcare sector educated on the value of the science being done, ultimately helping patients find the treatments they need.

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I kept hearing about the use of organoids in clinical trials and elsewhere and was curious to know more. Luckily, I connected with Samantha Nicholson, the Global Technical Marketing Manager for Cell Culture at Millipore Sigma. She has a very cool job. Samantha is a hub, as she calls it, bringing together scientists to make progress in this exciting new area of research. She described her role, the applications of organoids, and their implications for future scientific research and healthcare.

Organoids, as Samantha explained, are critical in basic research like organogenesis and developmental biology, offering insights into organ functions and disease modeling. Beyond that, their utility spans from drug discovery, where they aid in understanding drug effects and disease development, to pharmacogenetics and even regenerative medicine, potentially leading to breakthroughs like synthetic organs or alternative meat production.

Organoids are not just a mix of cells from a particular organ, they mimic the structure and function of the organ itself. She gave the example of a colon and an organoid having a mucosal layer, an absorptive layer, and a muscle layer , derived from a specific subset of adult stem cells. This allows them to model diseases and organ functions more accurately than traditional 2D cell cultures.

Perhaps most interesting is how organoids can significantly improve the inclusivity and diversity of clinical trials. Historically, clinical trials have suffered from a lack of diversity, often excluding women and other demographic groups. Organoids can be developed from tissue samples from diverse populations worldwide, allowing for a broader understanding of how diseases and treatments affect different demographic groups without the ethical and logistical complexities of human trials.

We'll also be able to do patient stratification. So we're able to look at specific metabolic profiles or racial profiles or genetic mutational landscapes and thentest those drugs in those patients as a stratified process.

So we can compare female and male, Caucasian versus African versus Middle Eastern, for example. And we can also start to develop patient-specific models. So we can take, for example, someone who has hereditary cholesterol and compare it to somebody who has developed cholesterol. And what does that mutational profile, differences in that mutational profile, what does that mean for those people?

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As someone whose last job in a lab was studying host pathogen interactions, I got pretty excited when she told me about the applications in this area. Organoids may fill the goldilocks region between expensive experiments in small animals like mice and the limitations of 2D cell cultures with representing a single cell type. I could have used this 25 years ago!

We briefly dove into process of creating organoids, starting from the isolation of stem cells from a tissue biopsy or through induced pluripotent stem cells. This involves cultivating these cells in specialized media to promote growth and differentiation, mimicking the natural growth environment of cells within the human body.

Despite the promising applications, there are challenges in organoid technology concerning the variability and reproducibility of organoids. The size and shape of organoids can vary, which complicates their use in high-throughput screenings and other standardized tests. Achieving full functionality and maturation of organoids remains a hurdle, as they often lack certain cell types found in natural organs, such as immune or endothelial cells.

When I asked her what is next in the world of organoids, Samantha was optimistic about their potential to democratize drug development and reduce reliance on animal models. She believes that advancing organoid technology could lead to more personalized and effective treatments, enhancing the inclusivity and ethical standards of biomedical research.

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By now, I imagine most of you have interacted with ChatGPT in some way. You can use it to summarize a document, brainstorm a campaign or plan a vacation away from technology. The capabilities are mind-boggling and the BS (if you detect it) is amusing. All that aside, how can you use an internal vertical GPT to serve your customers?

I spoke to Ian Birkby, CEO of AZONetwork about Azthena, the internal vertical GPT they built as an AI assistant deployed on their various websites to help users find relevant news and product information. If you are not familiar with AZONetwork, Chat GPT describes them like this:

The AZoNetwork is a company that specializes in digital marketing and content solutions within the science, healthcare, and technology sectors. They provide a range of services aimed at connecting scientific, medical, and technology communities globally. These services include content creation, marketing strategies, and communication solutions designed to disseminate knowledge and promote products through various online platforms. AZoNetwork operates several websites that publish articles, news, and resources relevant to professionals in these fields, helping them to stay informed about the latest developments and technologies.

As a media and marketing company, AZONetwork has a lot of content, over a million assets, by Ian’s estimate. This is the content was used to train Azthena to to answer users queries.

The value of this type of GPT is that the data it has been trained on has been reviewed and vetted by humans in the course of publication over many years. The same can’t be said for everything one finds on the internet, some of which ends up in the answers to your ChatGPT queries, not to mention outright hallucinations.

General LLMs, if I'm going to exaggerate, are a mile wide and a few inches deep. We're trying to be, you know, maybe 12 inches wide, but three foot deep… - Ian Birkby

Azthena took nine months to build. That was impressive to me given that includes putting some structure around all of their content.

The quality of the output should enhance the customer experience by providing specific answers to queries along with relevant references.

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Ian and I discussed what this will mean for companies, buyers and human creativity broadly.

External GPTs trained on the same broad collections of data may all end up homogenized. How will you differentiate your company to be a source of unique and valuable (essential) information? Building your own specialized GPT is one possible answer.

We agreed that the buyer’s journey will change. Once people adapt to the new approach (this will take some time but too much), they’ll expect to find answers and recommended next steps regarding what to look for or look at along the way to a purchase. No more clicking through multiple links hoping to find the best information. As I write that last sentence, I’m stunned at how quickly we are spoiled by new technologies. I’m old enough to remember mailing away to get a catalog or brochure from one vendor! If you are a marketer, you should be thinking about what comes next.

In reaction to this change, big information providers e.g. The Guardian, etc. are blocking crawlers from sucking up their information. Models built on search might also change. Will we have to pay for things that were free for the last 20 years?

Finally, I asked Ian about the future of human creativity.

…emotional intelligence… that's definitely an area where, you know, the human has still got a role I think, in that, very pure form of creativity… seeing what nobody else has seen before and thinking something different. You know, that I still think there's mileage in, in humans having a role to play there. However, there's probably 80 percent of the drudgery-related tasks that we all face that are going to end up sitting on the desk of AI.

But for those routine tasks, the efficiencies will be too attractive to pass up. The next question is where is the line that makes a task routine?

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Could bacteriophage be an alternative to antibiotics for Group B Strep (GBS) in pregnant women?

GBS is a commensal bacteria, found harmlessly in the gut of some people. But it is an opportunistic pathogen that can cause significant disease - sepsis, meningitis, lung injury and bacteremia - in newborns exposed to it in the vaginal tract during birth, for example.

Lucy Furfaro is an Emerging Leadership Fellow at the University of Western Australia in Perth. I spoke to her about her research in this area, how she became interested in the microbiology of newborns and their mothers, and the advantages of living in the most remote city on Earth.

Lucy works at the King Edward Memorial Hospital, the referral center for all of Western Australia which covers an area approximately equal to the US west of the Rocky Mountains.

What makes the hospital unique is that it hosts The Raine Study, the world's oldest prospective birth cohort, which has been collecting ongoing health data on mothers and their babies for 35 years.

Preventing infection of newborns is done differently depending on where you are. The standard in Australia and the US is universal screening, typically a swab test. Expectant mothers testing positive for GBS in the vaginal tract (about 1 in 4) are given antibiotics pre-emptively.

The UK and New Zealand take a risk-based approach (e.g., a history of infection) to determine who gets the antibiotic. While antibiotic resistance is not an issue of concern in GBS yet, we know that eventually it can be. Also of interest is what antibiotics do to the microbiome of moms and their babies.

These concerns lead to the consideration of phage as a possible targeted therapy for GBS. At least a few challenges, both scientific and regulatory, remain to be solved.

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Bacteriophage or simply phage are viruses that infect and kill bacteria. They are typically specific to a single type or closely related bacteria. Some are obligately lytic phages that infect a bacterium, replicate inside, lyse the cell and move on to the next bacterium. Others can hedge their bet, taking either the lytic pathway or occasionally integrating their DNA into the DNA of the host bacteria. These temperate phage might later be induced to lyse their host cells and move on.

Ideally, phages chosen for antimicrobial therapies are of the lytic variety. But every phage found to infect Group B Strep so far is a temperate phage. That is either a sampling problem or an interesting biological question of why that is so.

Beyond the biology are the regulatory questions. Are phage biologicals? They aren’t alive. However, neither is an engineered antibody, which is subject to a lot of analysis to confirm its identity.

One possible solution is to avoid using intact phage particles. It involves the engineering of phage lysins, the enzymes that disrupt bacterial cell walls and membranes. These might be delivered in a topical cream to prevent infection at birth avoiding broad spectrum antibiotic resistance and causing minimal disruption to the maternal microbiome.

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When I’m eating blueberries from Chile here in California, I assume that they arrived by air after being picked a couple of days ago. That isn’t necessarily true. Delivery by sea could take weeks from the time they are picked by the grower until they arrive on the shelf at my local grocery store.

In this episode, I talked to Tristan Kaye, Director of Global Marketing and Business Development at It's Fresh about the challenges of shipping fresh produce across the planet while avoiding waste and spoilage.

According to the UN Food and Agricultural Organization, up to 45 percent of all fresh produce grown is never consumed. For two reasons. One is food loss. So this is through poor infrastructure, lack of appropriate cold chain, mishandling these sorts of things, or food waste.

Another significant challenge in the supply chain is controlling the levels of ethylene, which is a signaling molecule produced in plants for many things, including maturation and ripening. And it doesn’t take much to have an impact on fruit during shipping.

…kiwi fruit can be sensitive down to four or five parts per billion. So to give that a sort of sense of context, a billion seconds is about 33 years. So it's lik if you're looking for ethylene in kiwifruit, that is the equivalent of trying to find five seconds of a 33-yearr period… But it fundamentally affects all of the elements in terms of the fruit and many vegetables that are developed.

It’s Fresh offers an interesting solution to this challenge. We didn’t go deep into the chemistry of their ethylene control technology. It allows growers to pick fruit a little early and allow it to ripen slowly so that, ideally, it shows up on our local shelves ready to be consumed. Our conversation focused on all the other aspects of the supply chain that illustrate the challenge of getting fruit to market in a condition that consumers expect regardless of where they were grown:

Growers get paid based on what arrives at the destination. They must decide when to harvest their fruit at some interval before ripening, yet they have no control over much of what happens or how long it takes before fruit arrives.

Market pricing and seasonal demand influence the decision of whether to ship by air or sea.

There can be tremendous uncertainties around the time spent in a warehouse at either end. Even shipping routes are facing uncertainty as there is a restriction on what can go through the Panama Canal due to a drought that has Lake Gatun at record low levels. Ships may have to wait in an anchorage at the canal, deliver some containers elsewhere or go around the tip of South America. Conflict near the Suez Canal, or the inability to access the Port of Baltimore might also be a factor right now.

Damaged fruit produces ethylene as a stress response. To top it all off, there is ethylene in the exhaust of internal combustion engines. Warehouses that store fruit may use electric machinery like forklifts, but imagine the challenge of keeping motor exhaust out of your entire supply chain.

The next time you grab a handful of blueberries grown out of season in the other hemisphere, give a thought to all the considerations and decisions that help preserve them from the moment of harvest to the moment you enjoy them.

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If you have a PhD in life science, are working toward one, or just considering it with an eye toward getting an academic job, the math is not in your favor. There are way more PhDs than the number of academic slots available. How that gets resolved with respect to your career was the core of my discussion with Ali Divan, Founder of Trulitica, where he is helping life science PhDs get into biotech.

Don’t miss the SPECIAL OFFER at the bottom of this post.

For many, there is a mismatch between expectations of what a career in life science might look like and where you end up working. But it’s not all bad. There are good jobs to be had. Just maybe not the ones you expected.

Ali’s job is helping folks reframe their skills (and conversations) to open up new opportunities.

A math problem

Our discussion covered the challenge from several angles. PIs need to generate publications. Historically, that has been done in the process of training scientists who then go on to train more scientists in their own quest for publications.

This has led to an oversupply of scientists looking for academic jobs. Entering graduate school now betting on an uncertain outcome eight years down the road (generously) is risky. But should you give up your dreams of doing science? No. The system is definitely ripe for change. At the same time, it’s important to be open to new possibilities. That’s good advice for anyone looking eight years ahead.

We don't really walk in and go, “Yeah, I'm, I'm going to do some career planning. I'm going to figure out what I'm going to do.” Most of us, we go, “Hey, I'm pretty good at school. I should keep doing it.”

Universities need to change

Check out Ali’s article at the end of this post for details. Ali says some of them are aware:

What I've seen when I started speaking to the deans of graduate schools at universities, they're very well aware of this. And a lot of them, what they say is, “You know, I think we just need to be a little bit more responsible at the time that graduate students are applying and beginning.

We need to tell them what they're signing up for and what the landscape is” so that they don't show up thinking, as I thought, that if you just show up and be excellent and try hard enough, that's enough because (for) everything up to that point in your life, that was enough.

The other challenge for PhD graduates is that university career centers are set up for undergrads. For a new PhD, your PI and whatever network you have created through conferences, your committee etc. is your career center. The problem is that the only job they can likely help you get is one that looks exactly like theirs. Because of the bottleneck or for other reasons, some people will decide to leave academia. But their training (they’re 30+ years old now) has not prepared them.

The rest is up to you

How do you build a good life as a scientist? Isn’t that the real goal? Do good science, make discoveries, solve problems and enjoy all the other things life has to offer?

What should you do if you had planned on a career as academic scientist and now need to look elsewhere? And how do you make that transition? How do you frame the skills you have in a way that’s relevant for employers?

Here’s the good news: Ali says most of what you need is around strategy and communication, not hard skills. You’re only a few months away from being ready.

The way that I help them is we first start out by sort of dismantling some of the practices that are that are so common and valued in academia. And so, as an example, in academia, it's highly valued to debate.

It's highly valued to ask anytime you feel like you have a question or an argument. You just, you put it out. What I generally say is, well, in the industrial setting, when you don't have time, you have to have a very good reason for meetings. It's much more valuable to listen…

That’s just one example of the difference you might find in industry.

Focus on skills as opposed to topics

You must realize that the people who will be hiring you probably don’t have a problem that your dissertation will solve. They have problems that require similar skills. Talk about those.

The first step is networking. Ali also gives some great recommendations here. I could go on forever about this because there is good networking and bad networking. I’m sure I have been an instigator and a recipient of both types. No one enjoys it until they really understand it. But it doesn’t have to be uncomfortable. Be human. Build a relationship and don’t be in a rush to hand someone your resume.

This is a valuable skill worth developing for the long haul. You had a long view when you started grad school didn’t you? I’d add that getting good at making conversation with anyone, is not only a good skill to have, it actually will bring you joy.

I like what Ali said here:

…so if somebody says something nice to you, and they're sincere, and they say, “Oh, hey, it looks like we also both study at this university, or I see you're a fellow immunologist… You know, my default answer, when I don't know anything, is cytokines. That'd make them laugh and they'll go, okay, who is this, who is this guy?

My own perspective

I find this whole topic fascinating. I went to graduate school because I didn’t look around enough to see the opportunities a bachelor’s degree would give me. I thought, “Who’s going to hire me?” My undergrad advisor founded a biotech with some of my other professors. I didn’t even ask them for fear of being laughed at. They wouldn’t have.

It took me too long to realize that I wasn’t cut out for the bench. I feel fortunate to have eventually found positions using what I had learned that were scientifically stimulating, fun and rewarding. Personally, I enjoy a broader view of cutting-edge science as opposed to chasing a single thread to the end in the hope of a significant discovery.

I also hope that the life science ecosystem (universities, funding agencies etc.) can evolve to help people find their path more quickly while maintaining the pipeline of PhD scientists we need to do basic research. Because beyond the bench, we need more science and appreciation of science in our communities.

There are so many ways to use your scientific knowledge and skills. I promise that there is a job out there that you will enjoy. I only wish I had met Ali thirty-five years ago.

SAVE 10% on the Trulitica Biotech Careers Course (Affiliate link valid until 5pm PST, April 30, 2024.) Use Code: LIFESCIENCE

And if you’re in a hurry, you can hire Ali to work with you at Trulitica.

How universities can prepare Ph.D.s for a changing job market.

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Reduce. Refine. Replace. These are the three Rs of animal research. The intent is to reduce the number of animals used, refine methods to be efficient and humane and replace animals with other models where possible.

This cc: Life Science episode is sponsored content, courtesy of MediLumine.

I talked to Stephen Marchant, Founder and CEO of MediLumine about the importance of animal research, how imaging in small animals is different from humans and innovations that support the 3Rs of laboratory animal sciences.

While the FDA no longer requires the testing of all new drugs in animal models prior to clinical trials, for some drugs, the requirement may stand. Animal research has been essential for many advances in human health and will surely remain relevant in the quest to discover new treatments in the future.

As compassionate beings, we want to help our fellow humans whenever possible. When a child has cancer or a mother with a diagnosis of early onset Alzheimer’s tells her children that at some point she may not recognize them (or they her), no options will be left unexplored to look for and find solutions and those options likely include some research using animal models to better understand disease.

The animal technicians and scientists working in laboratory animal sciences have a passion for developing therapies and treatments for human disease but also for taking care of animals. For those interested to know more, Stephen recommends the GetReal Podcast by Dr Cindy Buckmaster to truly appreciate the reality of this and what it is like to work with laboratory animals in the life sciences.

In vivo imaging is used to better understand disease progression or response to treatment, and it is one aspect of research that isn’t likely to be replaced soon. The development of novel contrast agents allows scientists to visualize structures such as tumors or vasculature much deeper in the organism thus precluding the use of visual inspections and use of a caliper to measure tumor size. This breakthrough is built in to MediLumine’s tag line ‘Vision without Sacrifice’.

Imaging structures in a mouse, whether by MRI or PET scan is very different from imaging in humans. The structures are (obviously) much smaller. What I hadn’t realized previously is how the small size requires longer measurements to get the desired resolution. Typical contrast agents like CT contrast agents used in the clinic are rapidly cleared making it more difficult for small animal micro-CT systems to generate high resolution images with these contrast agents. Stephen explained how the development of contrast agents like Fenestra HDVC, allows improved imaging of mouse organs with in vivo micro-computed tomography (CT).

Depending on the goal of an experiment, modalities like MRI or CT can provide good resolution which allows researchers to calculate, for example, the volume of an object such as a tumor. Other modalities, such as optical imaging, are preferred when sensitivity is important. Bioluminescent reporters can sensitively be detected in vivo with the trade-off being resolution.

…with optical imaging, it's a very sensitive modality. So you might be able to see something at lower concentrations, for example, with bioluminescent imaging. If you look at some of the tumor studies, in some of the publications, we see even a few days after the injection of tumor cells, we're able to see signals, but we're not necessarily able to localize them very well. So, for example, if you have, let's say, a signal in the right lobe of the liver, you would see something coming with optical imaging, but you wouldn't necessarily be able to localize it and say precisely exactly where it is.

Without these in vivo imaging methods, understanding the biology of tumor progression would require a larger cohort of animals, with a requirement to euthanize some fraction at various time points to locate tumors and measure their size. That’s the reduction element of the 3 Rs.

Refinement is also possible. Stephen shared an example of how new contrast agents in microCT allow the study of fatty liver disease that couldn’t be done previously with terminal studies and histology.

As for replacement, the development of organoids, small collections of differentiated cells, offer an alternative to some animal assays while more closely reflecting an in vivo condition than monolayer cell cultures. I’ll be covering that in a future episode.

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AgBio, sustainability and DoE all come together in this episode. Tim Cuthbertson is the Chief Science Officer at VelociGro where they are using Design of Experiments to optimize plant growth media for vertical farming.

I was curious to learn about the concept of vertical farming and how it can make an impact relative to the massive acreage involved in traditional agriculture. There are scenarios where it makes a lot of sense. First of all, greenhouse-grown produce is nothing new. Tomatoes are the most commonly grown crop in what is known as protected agriculture. And overall, in 2019, 55% of vegetable growers had some component of indoor operation, extension of the growing season being the primary reason. A greenhouse can produce 2.5 pounds of food per square foot per year. That’s horizontal growth.

Growing plants vertically should increase that productivity further. So where is the impact? Consider what it takes to send blueberries from Chile to Alaska. Now what if blueberries could be grown indoors locally year-round? With LED lighting (which apparently doesn’t have to work on a 100% duty cycle) there could be significant savings in carbon emissions. Not to mention loss from spoilage etc in transit.

In case you haven’t heard, the Panama Canal is backed up and the largest container ships can’t go through with a full load currently because there is not enough water in Lake Gatun due to decreased rainfall. That means produce either being offloaded elsewhere and sent by train or truck or a longer trip around Cape Horn and associated delays. Don’t miss my upcoming episode on “the ethylene problem”. We’ll talk about what it takes to keep fruit “fresh” on those long journeys.

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Either way, I appreciate you spending time here.

Local access to fresh produce in urban areas is another opportunity to deploy vertical farming. It occurs to me that a lot of empty office space is ripe (yeah, I said it) for conversion to urban indoor agriculture. I’m beginning to imagine a back-to-the-office campaign where a company leases some of its space for growing produce to be sold while allowing people who come back to the office to have access to a share of the crop to take home each week.

Where does Design of Experiments come in? We covered DoE in a previous episode. Briefly, it’s a method of testing multiple variables simultaneously to quickly iterate and find the optimal solution to a problem or process. A typical one-factor-at-a-time (OFAT) approach makes all the results dependent on the optimal value of the first variable you test. That doesn’t in any way guarantee the best final outcome.

How is VelociGro using DoE? We didn’t go into details about their products. Whether plants are grown on a substrate or in a soil-free environment, they need nutrients to grow. DoE allows their company of six people to iterate and optimize formulas for new products in as little as six weeks. Even if agriculture is not your field, you can see how DoE can save huge amounts of time in product or method development.

It strikes me that once again, regardless of what area of the life sciences you work in, thinking about how things are done is as important for delivering a successful product as the science that goes into the product itself.

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Thomas Farb-Horch is the CEO of Thrive Bioscience. He has founded 18 companies. Seven of those turned out to be unicorns (sold at a valuation of >1 billion dollars).

I was curious to know how he had identified so many opportunities correctly. BTW, Tom is not a scientist and has no advanced degrees in case you were thinking that was a requirement.

He credits his success to being observant and inquisitive. That means keeping your eyes open for problems and asking why things are the way they are. The most attractive problem is one where people have been working the same way for a very long time. And if a process can be digitized, even better. As ever more computing power and storage capacity becomes available, more processes are in reach.

Yet good ideas and smart solutions aren’t enough. Tom told me that every one of those unicorns came close to failure multiple times.

How did he manage to dodge the bullet so often? One area where data and computing power won’t solve anything is our interactions with other people. To be successful as an entrepreneur, in addition to solving whatever technical challenges you have identified, you are still left to deal with customers, investors and board members. This is where Tom’s experience struck me.

If you think reproducibility is a challenge in science, no amount of data or computing power can make humans more predictable.

Getting people to change something that has been done the same way for decades is difficult. First for them to recognize the value and then to adopt new behaviors. Even early and late adopters won’t respond the same way. Your solution needs to appeal to both.

At another level, while all your investors have a common goal of getting a return on their money, how and when they expect that to happen may be different. As you are likely to pivot at some point, it’s worth considering how you will keep them aligned on the new approach.

The makeup of your board is critical and Tom has some essential advice on how you should negotiate their selection with investors. Listen to the episode for details. When it comes to what you are looking for, I’ll share one example here. Board members are sometimes (often?) selected for their name recognition as opposed to their domain expertise. Alexander Haig (former NATO Commander and Secretary of State) might have fit that description. Nevertheless, he brought value to the table in other ways. Tom told me that his skill at observing people and making sure everyone was heard to get to a result was off the charts. Given the roles I just mentioned, maybe that’s not so surprising. These skills are applicable everywhere.

Board of directors is one of my favorite topics. It's so incredibly important. Many entrepreneurs don't spend enough time focusing on compatibility across the board. And kind of the profile of what they want.

Every founder is likely to encounter a dark night of the soul moment. Tom said, “Fear is a terrible advisor.” It’s at those times when having chosen the right investors and board members will pay off. Who will stand by you and brainstorm solutions to see you through?

Science is complicated and often difficult. Human behavior is even more so. It strikes me that in science, even if we don’t yet know the answer, we know it’s there and that certainty is comforting. I wonder if we shouldn’t spend more time thinking about how the people around us are going to affect our success and who we choose to do that.

As an example of how humans can make an impact in our interactions, more than once over several conversations, Tom asked me, “How can I make this podcast successful for you?” I replied, “That mindset alone is all I need.”

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Susanna Harris is the Director of Community at Breakout Ventures. She is also the Founder of PhD Balance, a collaborative community empowering graduate students to build their personal and professional resilience and the 2023 recipient of the SAMPS Young Person of the Year Award.

This episode is a little different. For the last couple of years, I have interviewed the winner of that SAMPS award on this podcast. Susanna has been a guest before and although we’ve chatted a few times since and both live in the Bay Area, we had never met face to face. Susanna mentioned hiking in one of our calls so I thought this would be an opportunity try something new. I suggested we meet up for a hike and record some stuff along the way. Thank you Susanna for being game for one more experiment.

We had a free-flowing conversation covering our inspirations in science, science communication, marketing, career paths, longevity, mental health, and more. AI, psychedelics and The Andromeda Strain all came up as well. Give it a listen to find out the context.

I typically focus these episodes around a theme and try to point toward a specific takeaway. While there is a thread to the topics we discussed, the takeaway for me this time was simply about the value of conversation. I trust that the listeners to this podcast will learn something about each of us and may be prompted to think about something they heard from a new perspective.

As a listener, you don’t have to be part of a conversation to benefit from it. That’s the magic of this medium. You can listen in as if you were there. Taking that beyond podcasts, consider the value of people listening to your team members, executives and subject matter experts in their natural, unscripted style. Podcast listeners report (and I can verify this both as a host and a listener) that they feel like they know the people they hear from regularly. There is a level of know, like, and trust that is hard to replicate except face-to-face.

Finally, one never knows where having a conversation will lead in the long run. I don’t even remember how Susanna and I connected initially. Yet here we were, 3 years later, hiking the hills, sharing our experiences in science and creating unique content along the way. If we get a chance to help one another out in the future, that would be icing on the cake. It all started with a conversation.

Mentioned in this episode:

Books: Where Good Ideas Come From by Steven Johnson

The End of the World is Just The Beginning by Peter Zeihan

Movie: The Andromeda Strain (also a book by Michael Crichton)

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Kurt Mussina is the CEO of Paradigm Clinical Research. Their model involves dedicated sites chosen for access to their desired patient and physician populations to participate in clinical trials. Access to historically underrepresented populations for both patients and healthy volunteers is a key requirement.

One can imagine it takes a lot of effort to figure that out from demographic data etc.

Kurt shared with me their approach using ChatGPT with some plugins not only for determining the best places to lease space, but also for qualifying and scheduling potential participants and determining which contracts to pursue based on their historical successes and current strategy.

3 Applications of ChatGPT or AI:

Where to lease and build out clinical trial sites

Kurt and his head of clinical operations are based in Boise Idaho. The first requirement was to be able to visit sites without spending too much time traveling. He searched the website of the Boise airport for nonstop destinations that were reachable in a half day or less. That narrows things down to the western half of the US. They queried ChatGPT to identify which of those have, within a two-hour drive, populations with a significant proportion of people historically underrepresented in clinical research.

For example, Chico California is one of those cities. Paradigm already has sites in Sacramento and Redding, which allows them to use the staff they already have on the ground and existing relationships to get a good start.

Using AI chatbots to qualify patients and volunteers for studies

Paradigm runs ads on Facebook to recruit potential participants. When a person visits the website looking for trials to participate in, rather than delivering a long list to browse, a chatbot will ask them questions about their age, background etc, to preview relevant trials and pre-qualify the person. It can then help schedule a phone appointment for further information and qualification.

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Contract assessment and budgeting

There are thousands of trials going on at any one time. Which ones does Paradigm want to bid on based on their patient populations, investigators, and desired indications?

Paradigm uses Salesforce to manage their sales pipeline. A sponsor or CRO may send out a feasibility questionnaire. This clip from the interview explains how an AI, based on their previous successes, helps decide which studies they’d like to bid on as well as providing a range of cost estimates and contract terms.

I asked Kurt, how they decided to take this approach to all of these important steps. It turns out the husband of a board member is pretty AI-savvy. Would you be as comfortable trying something similar if you didn’t know anyone with that kind of AI expertise?

In a couple of years, no one will think twice about this kind of approach. As I see it right now, the real barrier is our own imagination in terms of what problems do we need to solve and how to ask the right questions. Many of the current examples we see are using AI to generate content - images or drafts of written content, or some data analysis. It might be helpful to think of ChatGPT and its “colleagues” as individuals you hire to do a specific job.

In this example, it would be like, “Hey Joe, can you compile a report on cities we can get to easily that have historically underrepresented populations? When you are done with that, set up a web page to qualify and inform people interested in participating in a clinical trial. Oh, and then, take a look through our historical data and let me know which of our leads in Salesforce are the most promising.”

Those are the jobs to be done. I should say that Kurt was very clear that they worked with people outside the company to get these tasks done. In the end, one can see how it improves efficiency at every step.

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Up to this point, I have resisted doing any episodes around cannabis because 1. I’m a little old-school 2. I probably don’t know enough and 3. I want to avoid, in the words of my guest, “being painted with green paint” and tainting the brand.

Separating emotions from logic, however, if there are cannabis components that could be effective therapies, it would be foolish to ignore them.

There is already one cannabis-derived compound approved by the FDA. Epidiolex is pharmaceutical-grade cannabidiol (CBD) prescribed for the treatment of seizures associated with Lennox-Gastaut syndrome and Dravet syndrome. Pebble Life Science is taking a rigorous approach to investigate whether other compounds derived from hemp might be effective as therapies, either for other neurological disorders or even cancer, initially focused on ovarian.

I spoke with Patrick Moran, the founder and CEO of Pebble Life Science about their approach, the challenges they have faced, and the success they have had in forming collaborations with the MD Anderson Cancer Center as well as participating in the NCI Applicant Assistance Program.

Everything we discussed is in the pre-clinical phase, preparing for and gearing up toward clinical trials. A key event in this journey was the 2018 farm bill that allows the cultivation of hemp as long as the THC content is below 0.3%. That opened the door to growing and extracting components from hemp, all non-psychotropic, for investigation.

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One obstacle was bridging the gap between (clinically unproven) claims of cannabis killing cancer and putting in place procedures to rigorously investigate those possibilities. Another challenge, as mentioned above, was breaking through the cloud of suspicion that exists around cannabis. After being invited to apply for a drug development grant by the Cancer Prevention and Research Institute of Texas, one reviewer labeled them as drug dealers.

While the research staff took that hard, their legal team suggested taking their data and the positive feedback they had received from the other three CPRIT reviewers and contacting the NCI. That led to an NCI sponsorship for the NIH Applicant Assistant Program which Patrick said was invaluable in helping his executive team prepare to submit an SBIR grant to help fund clinical trials.

Based on pre-clinical studies in mice, Pebble is currently focused on the potential of a hemp-derived compound as both an adjuvant therapy and a frontline monotherapy for ovarian cancer.

At the end of our interview, I asked Patrick what he had learned that would be helpful to any biotech startup whether or not they are in the cannabis space.

Interestingly, I’ve recently had another conversation with someone I hope will be on this podcast soon. We concluded that science is difficult. People can be more so. It’s yet one more challenge to get people to change their thinking or to deal with the obstacles they place in front of you, intentionally or not. I hope this episode help you figure that out on your own journey.

There were a few terms I had to look up in our conversation. You may find these useful:

RPPA analysis

Entourage effect

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This week, I talked to Dr. Michael Harman, an executive advisor, and consulting partner at Harmon Consulting about commercializing medical diagnostics, exploring various aspects from technology development to market trends and the integration of different scientific disciplines.

I asked Michael about the process of transitioning laboratory technology into clinically viable products. He described a series of well-defined steps, starting from concept generation to prototyping and feasibility testing, eventually leading to a minimally viable product ready for market launch. It starts with identifying a gap in the market and scouting relevant technologies.

Scouting is the process of identifying existing technologies that can be utilized to construct different subsystems of the proposed diagnostic tool. He used the analogy of assembling Lego pieces. While innovation can add value and is, of course, a little more exciting, it also increases risk.

The engineering process of diagnostics involves bringing together various fields like industrial design, electrical and mechanical engineering, and crucial business aspects like sales and marketing.

I didn’t know much about the world of diagnostics that lies between lateral flow tests like the ones we all use for COVID-19, and large analyzers running thousands of samples per day delivering results of multiple assays to your doctor.

Michael noted a significant shift from centralized laboratory instruments to more compact, point-of-care devices, largely influenced by the COVID-19 pandemic. He highlighted the growing trend towards personalized medicine and home testing kits, demonstrating the evolution of diagnostic technology in response to global health challenges.

This got me curious about the role of electrical engineering in diagnostics. So we took a little sidebar into the intricacies of technologies like thermocyclers for PCR. While heating a metal block seems straightforward, doing so evenly across 96 samples may not be. And I never put much thought into what it takes to cool that block quickly and where the heat needs to go. Needless to say, I have a new appreciation for electrical engineering beyond circuits and robotics.

A key takeaway from our conversation was the integration of various scientific disciplines, such as computer science, biology, and physics, in developing new diagnostic methods. He mentions several innovative diagnostic projects he's involved in, such as non-invasive tests for endometriosis and personalized contraception compatibility tests. These projects exemplify the potential of predictive diagnostics to revolutionize patient care and treatment.

There have been significant strides made in this field, largely due to the collaboration across different scientific domains. He emphasizes the importance of bioinformatics and the role of computer science in medicine, marking a paradigm shift in how medical research and diagnostics are approached. It also presents challenges:

People don't always necessarily know what to do with diagnostic information either. That is a big challenge in terms of, okay, great. You've identified a marker now exists, but what is that now? How do you then inform the patient of or change their treatment based on that information?

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As we often do, we discussed the challenges faced by academic founders in transitioning their ideas from academia to industry and the mindset changes required for successful commercialization. He notes that while academics are used to being highly independent and handling various aspects of a project, success in the industry often requires a more collaborative approach. Founders must learn to trust and leverage their teams, allowing each member to contribute their expertise to the project.

Michael mentions the debate about the necessity of having clinicians or scientists in leadership roles in medical companies. While their deep understanding of the technology is beneficial, it can also be challenging for them to step back and allow others to handle aspects of the business they are less familiar with. This transition, from being an independent academic to a team-oriented industry leader, is crucial for the successful commercialization of medical technologies.

Our conversation shed light on the complexities of commercializing medical diagnostics and highlighted the importance of interdisciplinary collaboration in driving innovation in this field.

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When it comes to chemical reactions, if you can imagine it, somewhere out there a microbe is already doing it. This was something we used to say in graduate school. The challenge is finding that microbe among the billions that exist in environments all around us.

Surehka Karudapuram is the VP, Commercial Operations at Isolation Bio where they are helping researchers solve that needle in a haystack problem. In this episode we talked about the what, the how and the why.

Check this out:

Isolation Bio specializes in high-throughput and automated isolation and cultivation of microbes. Surehka explains that Isolation Bio's platform consists of an instrument, consumables, and accessories that enable the efficient study of new microbes, their unique products, and their impact on the world.

One could isolate many different microbes by diluting and plating extracts from your environment of interest on petri plates and then waiting to see what grows. Isolation Bio's technology allows researchers to perform massively parallel cultivation of hundreds of bacteria from various samples, such as soil or feces. This takes place in an array with over 6,000 nanoscale wells. I found it amazing enough to sort microbes into the wells. What blew my mind was the ability to then pick the desired samples out of those wells and transfer them to 96- or 384-well plates for further analysis.

Incubating the array under specific conditions is the first step in screening for the type of bacteria you are looking for. In one example, the desired bacterium grew slowly and would typically be overtaken by other species. Creating individual isolates gave researchers the chance to find and cultivate exactly the species they were looking for.

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Microbiome research has evolved from observation and cataloging into studying actual biology. We’ve gone from metagenomics (identifying what's there by next-gen sequencing) to identifying the capabilities of bacteria and purifying compounds. We discussed various application areas, including human health, animal health, agriculture, and environmental sciences, where microbiome research and bacteria play a crucial role.

Human health is a big area for our customers and the microbiome space and it's just so many kinds of diseases that are now being linked to the microbiome and then also getting to that point of that causation. I'll just use the example of drug response or immunotherapy response in cancer patients. There's a clear population difference between the responders and the non-responders.

And now we're starting to see work where the bacteria from the responders are being isolated and then being used in mouse models and then again, down to the next step, which is purifying, you know, maybe from the supernatant, the molecules, and then seeing that that can enhance immunotherapy drug response.

Getting back to “If you can imagine it…”, we discussed potential commercial applications of isolated bacteria, including the development of probiotics, therapeutics, and products for various industries. Surehka highlighted the possibility of bacteria as "chemical factories" that produce beneficial compounds and explained how synthetic biology can be applied to engineer bacteria for specific functions, such as producing biodegradable plastics.

It’s an exciting time to learn about the connection between our gut microbiome and other aspects of human health. On the other end of the spectrum is the possibility of discovering useful new compounds or ways of synthesizing them in living chemical factories. Where do you see the biggest potential?

Leave a comment.

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Rochelle Prosser is the founder and president of Orchid Healthcare Solutions, the company she created to consolidate cancer treatment information and improve access to that information. We discussed the difficulties in navigating healthcare systems and the importance of having comprehensive, scientifically-driven resources for cancer patients and caregivers.

Rochelle is a neurotrauma critical care nurse with 30 years of experience. She has had her own journey in healthcare and felt the impact of cancer on both her husband ( a two-time survivor) and young daughter. She described the challenges of a family trying to stay together and making decisions for a daughter who was only beginning to experience life when she was diagnosed with a rare cancer at the age of four.

She had this arbitrary, completely rare brain cancer and it took nine years to figure it out for her to find survival. And that's a long time. Most people can't deal with that. Marriages are lost, finances are ruined, but we remained intact.

Although her daughter was put into hospice five times, Rochelle never gave up advocating for her. I was curious about how you persuade a doctor to try something new when your child is already in end-of-life care. Her advice was to try to always be collaborative. Doctors and nurses want to help. There is value in being persistent, but it’s also important to listen. Not every treatment is the right one. If the doctor says no, there is likely a reason. But that doesn’t mean you stop trying:

And so I had to find a way. to politely and effectively navigate and communicate so that I could get to that next cure, to that next option. For me, 50 percent chance of working for two years until the next treatment was a better option than 10 percent chance on a conventional treatment.

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Based on genomic analysis, her daughter’s tumor was a mosaic of glioblastoma and DIPG (diffuse intrinsic pontine glioma). Imagine how complicated that sounds even to a healthcare professional, let alone anyone else. In addition to advocating for her daughter, Rochelle decided she would try to help others in similar situations.

I felt the need to intercede in that space intentionally with what I knew and how to navigate. So this is why I started Orchid Healthcare Solutions. I created a cancer treatment library that houses all cancer treatments from soup to nuts. Everything that's out there that is scientifically driven in one place. One of the biggest pain points, being on the provider side, but also on the recipient and caregiver side that I found was there wasn't a place that had a unified place to go.

It was really difficult to navigate to get information just to find out that knowledge. And I said, if there was one way that I could share my knowledge was to consolidate that, remove the silos so that you have effective and appropriate information sharing, and that will help vulnerable populations. That will increase knowledge and awareness and increase participation in clinical trials.

Because genomics was so important in her daughter’s case, Rochelle feels strongly about the need for diversity in clinical trials to understand how treatments affect different populations. Representation in those trials is critical to advance medical science that benefits everyone. At the same time, she is very clear about the importance of informed consent and the conditions around consent for participation. Bottom line - we need more people to participate AND understand their rights regarding their tissues and data. That’s how we get to the end goal of more diversity and better understanding of which treatments will work for different populations.

That is the only way to move us forward. We all must come together because where it works or is expressed in one, it doesn't work (in another), but we need to find out why. And when you find out why, it is that nuance of why that then can put protection and then advancement and an improvement in care overall for all of us.

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Jeffrey Kiplinger is the co-founder and partner at Selling Science, a consulting firm dedicated to helping life science, contract research, and tools companies boost revenue by building and optimizing their scientific sales teams. He is also the author of the book "Expert to Entrepreneur."

Jeff shared his personal journey from obtaining a PhD in organic chemistry in the late '80s to his corporate experience with Pfizer. He highlighted the frustrations he faced being siloed in his role and the desire to take his expertise on the road.

I appreciate his perspective on the disconnect many scientists face when building businesses. I guess I would say, your expertise is the product, but it is not the business. I’m still chewing on that one as I think there is a lot to be learned from that. Jeff emphasized the importance of viewing the business as an entity itself, separate from the scientific expertise it offers, and focusing on growing the business side.

Personally, I find marketing easy (talking about what I do). But sales is hard (asking for money). We talked about that and how to find the right people for your offering, stressing the need to identify the ideal customer and tailor marketing efforts to address their specific problems.

What is, what do you do that's provided real value for your customers in the past? And the easiest way to find that out is to ask them. And that's also something that we're terrified of doing.

I asked him about a quote from Brian Tracy. “Sales is just a transfer of enthusiasm.” When you believe in what you have, you can have a conversation and talk about why you are enthusiastic. But first you need to find out if the person in front of you has a problem you can solve.

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The conversation also touched on hiring experienced salespeople, both within and outside the scientific domain, and the critical factor of finding the perfect customer. Jeff outlined the significance of defining an ideal customer profile, which guides marketing efforts and ensures a more focused and effective approach. Does the salespersons skills and experience match what you are trying to do? Do they have the right mix of science and sales expertise? For example, selling from a catalog is different from selling a solution comprising components from a catalog.

If you're buying somebody's expertise in your science and they can't sell, that's a wasted investment. If you're buying somebody's network and their network isn't your ideal customer base, that's a waste.

…I guess what I see is when people hire experienced sales reps or senior people who've already got field experience, very frequently they're not looking at whether that person is a match for what you're trying to achieve. They might be a match for your company, they might be a match in terms of the revenue they've produced in the past, but are you really checking them against what the company is trying to do?

If you are on the road to selling your hard-earned scientific expertise, you should definitely give this episode a listen.

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Tom Pesnot is the Head of Medicinal Chemistry at Concept Life Sciences. I invited him to talk about AI and virtual screening in the drug discovery process.

By way of review, Tom laid out the overall process of discovery. One needs to identify a target whose activity can be modulated in a way that is of course, relevant to the disease of interest. Most often we are trying to stop a protein from carrying out its normal function.

Then we are looking for hits — interactions of candidate compounds with the target molecule. The quality of those hits are important.

Typically, this has been done in high throughput screening using in vitro assays. This requires lots of compounds and lots of assays, making the process inaccessible for many. As you might imagine, it is very expensive with fancy robots etc.

All of this provides the rationale for virtual screening because computers are becoming more powerful for predicting interactions between small molecule compounds and target proteins.

Instead of starting with a compound collection (that few have access to), you start with a database. It’s possible to virtually make tens of billions of compounds in silico for screening. What blew my mind was the fact that they are only screening molecules that can be made in two or three steps from existing building blocks. Tens of billions! That means the time from identification to testing is essentially the time needed for shipping the constituent compounds.

And of course, at the other end, you still need a model to recapitulate the proposed activity in vitro.

AI is used along with known protein structures to see what molecules fit and how well in the target’s binding site. I asked about binding in other places that would affect activity. Ligand-based interactions are legitimate, Tom told me. For example, GPCRs (G-protein coupled receptors) elicit different pharmacology depending on where binding occurs, but AI has more impact in structure-based screening focused on active site binding.

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The big innovation is narrowing down the possibilities to test. The traditional brute force approach, even with AI, is to screen one compound at a time. This requires huge amounts of computing power. An AI-derived algorithm that tests the most likely candidates can accelerate the process 1000-fold.

“And that means that because you're accelerating the process by a hundredfold or a thousandfold, then you don't need 10,000 CPUs. But you need 12 CPUs. And then you can screen billions of compounds using, you know, average Joe’s (gaming) computer and get that done in a week. So that's really one of the aspects where AI is having a huge impact on virtual screening. It means that even for huge collections, this process is accessible to small biotechs, to everybody.”

While machine learning is working on making hits more relevant, false positives are a still a challenge. Many things need to work well for a drug to be approved. Safety, efficacy, solubility etc are all important.

We’re not making virtual medicines

So how many compounds from a screening will be tested in an actual in vitro assay? Tom says they might start with 500-1000 molecules. Then those are whittled down to 50-100.

Then they make/buy them and do an in vitro assay.

I’ve been curious about where we are in terms of AI developed drugs in the pipeline. It’s still early days with respect to approved drugs from discovery by AI. According to this article, as of August 2023, none are yet at the approval stage.

One big problem, yet to be overcome, is that typically negative data are not published.

“The problem is, We have a lot of positive data points, negative data points are not necessarily as available because we don't tend to publish negative data. Even though there are some channels to do that and the problem is to build and test and validate a machine learning model or any model, you need to have positive and negative data.”

There are many reasons why a tested compound doesn’t work including a specific protocol or human error. Yet, I can’t help but wonder how much money and effort is wasted on testing compounds that have already been shown to be ineffective, but the data not shared.

Worse yet is the fact that there are published papers with fake data written by AI which is a whole other topic.

Maybe drug discovery is getting harder because we are getting to the proteins that are involved in more complex processes. But Tom points out that many targets that were thought to be undruggable have seen success. Ideally, AI will help us get there faster.

My question for all of you: Where else might AI be applied to make drug discovery more successful, improving on the 90% failure rate? And is anyone working on that?

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Note: For this episode, I asked ChatGPT to write a summary based on the transcript of our conversation. I enjoy doing these interviews and consider myself a decent writer. However, it takes a lot of time each week to write a summary that I find minimally satisfying and acceptable. You deserve better and I can put my efforts to better use elsewhere or upgrading the whole experience here. I did lightly edit this to make it sound as if I could have written it. This is my second attempt following some feedback from a respected colleague (you know who you are). I’m beginning to see how my own style differs from ChatGPT, even if what it produces is perfectly readable, but somewhat less memorable. Let me know what you think in the comments.

Miranda Lipton is a talented freelance writer, photographer, and multimedia storyteller. In this episode we talked about earned media from a freelancer's perspective, focusing on how companies can collaborate with freelancers to get their stories published in widely read publications. Our discussion centered around Miranda's recent success in securing a feature in Fast Company about cultivated meat from fish. Our conversation should be enlightening for both freelancers and the companies that work with them.

Miranda's Journey into Freelance Writing

Miranda journey into freelance writing began in high school, and continued at the local town newspaper, a path that eventually led her to major in journalism at Ohio State University. Her desire to explore different facets of storytelling, including writing and photography, drove her to the freelance world.

The Genesis of the Lab-Grown Fish Story

Miranda's fascination with food sustainability and innovation in the past few years led her to investigate the idea lab-grown fish. The idea for the article emerged from a deep dive into the world of lab-grown meat, a concept that had been around for nearly a decade. Miranda recognized a gap in coverage, particularly in the realm of lab-grown fish, which was an emerging and innovative field. This, combined with her passion for food sustainability, created the perfect recipe (ChatGPT made a pun!) for a compelling story. She did her research and interviewed folks at relevant companies, eventually leading to the publication of her story in Fast Company.

The Art of Pitching to Publications

I was curious about the pitch process. How did she get an articled idea accepted at Fast Company? She utilizes a consistent pitch outline, typically comprising two to three paragraphs that encapsulate the essence of the story. Miranda stressed the importance of familiarity with the publication's focus. In her case, she had been an avid reader of Fast Company for years, allowing her to confidently identify the magazine as an ideal platform for her lab-grown fish story. .

Navigating Interviews with Companies

While pitching to publications can be challenging, arranging interviews is more straightforward. Companies are generally eager to discuss their work. Her process involves reaching out to individuals at relevant companies, often beginning with CEOs or co-founders identified through LinkedIn. Of course, it’s important to gather a diverse range of perspectives to provide a well-rounded view of the subject.

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Feedback and Challenges

I asked her if she had gotten any feedback. While direct feedback from readers is not common, she occasionally receives emails from individuals who have read her articles. The overarching response to her articles on topics like lab-grown and 3D-printed food often revolves around skepticism and the novelty of the subjects. Many readers express interest in these innovations as well as uncertainty about trying them. The unfamiliarity of concepts such as 3D-printed food explains their hesitation. She thinks that as research in these fields progresses, more people will embrace these innovations. I have similar feelings of hesitation. I did an episode several years ago on the SDBN podcast.

Guidance for Companies Seeking Media Coverage

For companies without extensive PR resources, it is still possible to secure media coverage. Miranda recommended using platforms like Muck Rack to connect with journalists directly. The key is to reach out to journalists who cover topics relevant to the company's work. Tailored and timely pitches can catch a journalist's attention and pave the way for a mutually beneficial collaboration.

Collaborating with Freelancers

To get the writer’s attention and interest, you need a story with a clear angle and a sense of timeliness. Timeliness is one of the most critical factors. A story needs to be relevant in the current moment or have enduring relevance. Other elements, such as impact, prominence, proximity, and oddity, can also contribute to making a story compelling and newsworthy.

Understanding the freelance writer's perspective and the dynamics of storytelling can be instrumental in building successful media relationships and getting your stories into the limelight.

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Note: For this episode, because we are discussing the narrative capabilities of AI, I asked ChatGPT to write a summary based on the transcript of our conversation. I enjoy doing these interviews and consider myself a decent writer. However, it takes a lot of time each week to write a summary that I find minimally satisfying and acceptable. You deserve better and I can put my efforts to better use elsewhere or upgrading the whole experience here. I did lightly edit this to make it sound as if I could have written it. Let me know what you think in the comments.

In this episode, I had the opportunity to chat with Matt Lewis, the Chief AI Officer at Inizio Medical. We dove into the world of artificial intelligence (AI) and its pivotal role in the field of medical affairs, particularly in aiding the commercialization of medical innovations. This conversation shed light on the remarkable ways in which AI can be harnessed to enhance decision-making, streamline data analysis, and shape the narratives around product launches.

Introduction

Inizio supports various players in the life sciences arena, including pharmaceuticals, biotechnology, medical devices, digital therapeutics, and more. Inizio helps these entities translate their scientific endeavors into compelling narratives tailored for a diverse set of stakeholders, from clinicians to regulators, payers, and patients.

AI has been a significant player in the medical field for several years. Matt, with over a decade of experience in medical affairs and 15 years in AI, highlighted how AI first emerged as a solution to address the overwhelming volume of scientific data, including clinical research, published papers, and patient information. This surge in data presented a challenge as it exceeded the capacity of an individual to process effectively.

Matt went on to explain how AI, particularly Natural Language Processing (NLP), was employed to sift through vast amounts of content. This enabled the identification of relevant terms and concepts that were crucial for strategists and scientists to focus on. It essentially acted as a tool for surfacing meaningful insights from the sea of information. The AI-driven lexicon analysis and scientific platform considerations played a vital role in ensuring that medical professionals could efficiently navigate the complex landscape of scientific data.

The Role of Subject Matter Expertise in AI

While AI is a powerful tool, it requires substantial input from subject matter experts. To effectively utilize AI, you need to define the key terms and concepts that the tool should focus on. In the medical field, this entails understanding the therapeutic area, specific indications, and relevant terms and vocabulary that are integral to the domain. Without this critical input, AI can't effectively sift through and categorize the data. It should be viewed as an amplifier of human expertise rather than a replacement for it.

Crafting Effective Narratives with AI

How can AI be used to craft narratives that resonate with various audiences? Matt explained that in the past, narrative development was often based on subjective, qualitative discussions within multidisciplinary groups. While these discussions were essential, they sometimes lacked objectivity. The loudest voices or the strongest opinions often win.

There was a lot of evidence, but sometimes the subjectivity and the qualitative nature of kind of what made sense of the organization kind of won the day, if you will. I think when we started moving into more of an evidence-centric, data-centric, AI-centric type of environment, those contributions are still there for sure, but they're kind of counterbalanced by more of an objective evidence-based approach…

AI has transformed this process by providing an evidence-centric, data-driven approach. Instead of relying solely on subjective opinions, AI can analyze data to reveal how different narratives perform in the market. For example, if several competitors dominate a specific narrative, it might not be the best strategy to enter that conversation. AI can help identify unexplored "blue ocean" areas where the competition is less intense.

Matt also highlighted that AI has evolved to provide real-time insights based on citation information, sentiment data, and relevant word associations. This dynamic approach allows companies to adjust their narratives based on changing market conditions and emerging trends. The ability to capture contextual intelligence from medical encounters, such as conversations between medical science liaisons and opinion leaders, provides valuable insights for crafting narratives. AI's role is not to replace human input but to augment it and ensure that strategic decisions are grounded in data-driven insights.

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AI and Drug Repurposing

AI is also playing a vital role in drug repurposing. AI can help identify existing drugs that have the potential to be repurposed for new therapeutic uses. By analyzing vast amounts of scientific data, AI can uncover hidden connections and suggest novel applications for existing drugs. This approach not only accelerates the drug discovery process but also helps in finding treatments for conditions that were previously overlooked. The ability to sift through extensive literature and uncover these hidden gems is a game-changer for the pharmaceutical industry.

The Data Sources for Insights

Conversations between medical science liaisons and key opinion leaders are a primary source of the data used. These conversations are crucial for understanding the sentiments, opinions, and insights of experts in the field. Additional data sources include advisory board meetings, market research, and physician interactions with medical information customer centers.

Currently, conversations are not typically recorded due to privacy and legal considerations. The information is likely captured in field notes, which are then input into Customer Relationship Management (CRM) systems. AI is used to analyze this data and extract insights, but the human touch remains essential in filtering and interpreting the information.

The Future of AI in Medical Affairs

There is the potential for AI to capture not only the words spoken but also the tone and emotional cues in conversations. AI could help detect subtle nuances in conversations, allowing for a deeper understanding of sentiment. This level of emotional intelligence could be a valuable tool for improving customer interactions.

The integration of AI in CRM systems is also expected to grow, providing more robust insights and streamlining the entire process. With advancements in technology and an increasing comfort with AI in the medical and scientific community, we may see a shift toward recorded conversations, enabling more comprehensive and context-rich analysis of customer interactions.

Conclusion

AI, when combined with human expertise, has the potential to revolutionize the way medical professionals navigate the sea of data and make informed, data-driven decisions. The future promises even greater integration of AI, enhancing the quality and depth of insights, and ultimately improving the medical and scientific landscape.

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All of us in the life sciences are in the business of making the world healthier. The instruments and reagents we sell and the technologies and therapies that result save lives.

A scientist (after a lot of research) will look at a disease or problem and say, “I think I can find a way to fix that.”

Can we, as an industry, look at trade shows like a scientist would, and ask, “How can we do this better and stick to our mission of making the world at least less sick if not healthier?”

If you’ve been with me for a while, you know I have a love-hate relationship with trade shows. When I was a MarCom director, events were by far the biggest part of my budget. I imagined all the other awesome campaigns I could execute with that money. And then there is the waste. The stuff that ends up in the hotel trash before you get back on the plane and the shipping of huge amounts of equipment all over the world.

On the other hand, if a lot of customers are going to be in one place at the same time… it makes sense to take your offering to them. And human connection is important.

I know it’s important because this episode came out of my trip to ADLM, the event formerly known as AACC.

Stuart Warrington is the CEO of Envoke. They create virtual demos to make your instruments accessible at more events and present a consistent story across the customer journey. More on that below.

Stuart is a filmmaker. He has been created videos for the likes of Thermo and Bio-Rad. Videos used to have a longer useful lifespan. Then his customers wanted new content at a faster pace that was more engaging. Stuart suggested video games.

“No. That’s not it.”

“How about a virtual demo?

“Yes!”

It turns out those are basically the same thing just packaged differently. (They are both virtual experiences that tell a story with the user as the hero.) Stories are the key here. (The crowd cheers.)

People need to tell their own story, right? And sales and training and all that is about that. It's like, how can I communicate the message of what this thing does in the most accurate possible way? And you need to give people freedom to craft that story. And that's why we do things the way we do them.

We make this story block library and it's loads of little clips. And in each clip tells its own individual message. And then your user, your sales rep, your engineer, your trainer can take from that library and craft this story. It might be about a really specific bit of qPCR on the qPCR devices in the platform. And you know your customer only really cares about that. So we give you the opportunity to just pull those bits in and tell a story that is about your product with your product rather than PowerPoint presentations and brochures and videos and things like that. It just takes that to a slightly higher level and it also then starts saving you loads of money on shipping. Right?

The result is that consistent experience for the user from the web to sales to training to maintenance and service. We talked about training people the same way pilots train. On a simulation. They can make mistakes without breaking an expensive piece of kit.

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In addition to the contribution to sustainability without shipping products, the ability to customize a story improves the sales process.

So one of our customers built a storyline for the event from the story block library. So they built something that was like, this is what we want to talk about. This is the story we're telling here. But then what it also did was they put on a QR code, so that you scan the QR code as your customer, and what you do is, you walk away with a different storyline that's specific for you, that's just about the thing that you were talking to him about.

It's all come from the same place, we've just pitched it slightly differently. So it's all come from that story block library, we've just created specific storylines for different environments. And one of those environments is, “I need something a little bit better to take away and show to my boss.” And they take, they scan the QR code, they get their demo, and it's just for them, it's tailored for them, and they walk away and they show their boss, and it's a path to sales, right?

This sounds better than walking away with a PDF or printed literature that the boss has no interest in reading.

What is the path to this magical virtual future? For now, Stuart thinks companies will continue to send at least some products to events. The change comes from the bottom up where they no longer send instruments to smaller shows or remote locations.

At some point, customers and salespeople see the benefit of this approach and hopefully, we all get more creative about how to use our space at larger events. Instead of bringing one instrument or a few, companies could present their entire catalog or larger configured solutions.

This is only one way that we can improve the trade show experience and get a better return on investment. In an upcoming episode, we talk a little bit about the interactions that happen in the booth and how they can be improved as well.

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Barry Goldman, founder and CSO of Pluton Biosciences introduces the concept of microbial cover crops as a new and innovative approach to improving soil health and sustainable agriculture. A plant cover crop e.g. alfalfa, is typically grown in the off-season and plowed back into the field to enrich the soil before the actual crop is planted.

Barry and his team set out to see whether some bacteria can do this, particularly around nitrogen fixation, adding ammonia to the soil from the atmosphere. He points out that since the 1950s and 1960s the world’s population has gone from roughly 3 billion people to 8 billion. Some part of that is due to the use of synthetic fertilizers - ammonia made from the Haber-Bosch process. That has fed a lot of people. But that process creates a lot of greenhouse gas as well.

Is there another way to add nitrogen to the soil that avoids undesirable side effects? When Barry and I were classmates and labmates in grad school studying Salmonella genetics, We had a saying. “If you can imagine it, a bacterium is already doing it.”

Starting with a soil sample containing about 10,000 different species, the scientists at Pluton Biosciences have identified a consortia of bacteria that will grow in the absence of carbon and nitrogen except for what they can get from the air. The consortia work together using energy from the sun to reduce CO2 into usable energy sources (photosynthesis) and fix N2 to ammonia which can be used to synthesize amino acids etc.

As an additional benefit of deploying microbial cover crops on a large scale for nitrogen fixation, it’s possible to sequester a significant amount of carbon dioxide from the atmosphere.

"If you could now take this on a hundred million acres, you removed a hundred million tons of CO2 per year... you can start tackling this and give ourselves more time to come up with even better solutions. We also believe we can put on 30 pounds of nitrogen per acre. So now, if you're on that for that much, you're essentially almost turning the amount of the Haber-Bosch process to zero. That's roughly 20 percent of the greenhouse gases that are being emitted. You put those two together, now you have a massive impact on climate change."

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What would it take the bring this potential to reality?

Of course, like anything else in life science, safety and efficacy matter. These consortia need to be tested in the field. Because they are not genetically modified, the EPA would be satisfied to know that the constituents of the consortia have been identified and are typically present wherever they are intended to be applied.

The second challenge is getting farmers to test the consortia in their own field (or a portion thereof). They will want some assurance that they would at least be compensated for any reduction in yield. And to be paid for their effort as well.

Testing in real-world fields is crucial to prove that these microbial cover crops work as expected. This involves multiple phases, from starting with a few fields to expanding once efficacy and safety are demonstrated. Amazingly, the consortia create a visible crust on the soil. Similar to what we discussed in a very early episode of this podcast, drone technology and machine vision can be used to monitor the fields and gather data on microbial cover crop performance.

Oh yeah. What’s the business model? Someone needs to pay for this. If the consortia works, the grower gets value from savings on synthetic fertilizer. There is also the carbon market. Right now that’s at $15-30 per ton of carbon sequestered per acre. Finally, does the soil improve? Does it result in better yields (more revenue)?

Barry reminds us that this is not a complete solution. But microbial cover crops have the potential to put a significant dent in greenhouse gas emissions giving us more time to develop additional remedies for climate change.

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I traveled to Disneyland Orange County for AACC ADLM back in July to connect with a few folks and walk the floors of the exhibit hall. I was on my way out when Derek Hamre from Launchworks CDMO stood up at his table and got my attention with the best elevator pitch I have ever heard. And that landed him a spot on my podcast. I’ll share what it was at the end of this post.*

Imagine this scenario. You’re in an academic lab or small biotech and you’ve developed a diagnostic test for a molecule or a disease. How do you go about commercializing your test?

Do you need to get a bunch of regulatory approvals? What else do you need to think about? After all, you’re in a small research lab stepping into a whole new world. It turns out there are people who do this for a living and can help you plan out your strategy.

Launchworks is a CDMO for molecular diagnostics. Services range from commercialization strategy and supply chain management through to fulfillment. A company might come to them with a locked down bill of materials and work instructions for kitting tens to hundreds of thousands of units at a time, or maybe they are early in the process and need help thinking through strategy from the beginning.

…one of the reasons that we are pretty present at ADLM, AACC is the RUO kits. Those that are taking an idea from the R&D space and bringing it to the market and that commercialization process is a big, you know, lift for a lot of companies, even if they're bigger. Um, but especially for smaller companies when they have 5, 10 workers that have never gone through the commercialization process.

Beyond that, what level of regulatory approval do they want? In some cases, a kit might be sold as RUO (Research Use Only), but a customer’s customer might want to take it further:

And a lot of our customers, so we won't make those claims, obviously, our customers will go through the FDA filings or whatever, um, but some of our customers will just not want to go through the FDA process, so they'll make their kit RUO and then maybe one of their customers will buy the kit and then go through the FDA or 510K, PMA process… …so allowing another customer or their companies that they're working with to go through that process on their behalf might be the pathway for them.

Regardless of the regulatory path chosen, Derek described the four main areas where a CDMO can help get a product to market.

• Risk mitigation

• Commercialization strategy

• Manufacturing process

• Supply chain

You’d like to avoid surprises in any of those areas. Taking supply chain, for example, it would be important to know if a supplier might be closing shop in the near future. Will you be able to maintain quality as you scale up?

I asked Derek about the logistics of assembling and shipping hundreds of thousands of units from different vendors. Everything is done in-house. Mixing buffers, putting kits in bags, labeling and shipping. Launchworks has about a 30,000 to 40,000 square foot facility in Beverly, Massachusetts.

Prior to this I knew that there were CDMOs for pharma, but not for diagnostics. ADLM was an eye opener in terms of the world of clinical chemistry. And this isn’t the only episode I recorded as a result of that visit. More in a couple weeks.

*I don’t remember his exact words, but it was along the lines of “We’re helping visitors to ADLM become vendors at ADLM.”

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Dr. Antonio Tito is the Founder and CEO of rEthix in Houston, Texas. rEthix is the world’s first Liaison Research Organization (LRO) facilitating clinical trials in Mexico and Latin America.

A search of clinicaltrials.gov shows that several large pharma companies are currently running trials in Mexico. rEthix is leveraging the ICH (International Council for Harmonisation) guidelines to run these trials in Mexico and use that data to support IND-enabling studies in the US. The ICH sets the guidelines that the FDA and equivalent agencies in other countries follow. COFEPRIS, the Mexico Ministry of Health, assesses the laboratories. rEthix also prepares those laboratories to pass that assessment.

One advantage is cost. According to Dr. Tito, the cost of a trial in Mexico may be 15-25% of the cost for a similar trial in the US.

Another advantage is meeting your goals for testing diverse populations.

While it’s common to run trials in Mexico, it is not common to start them there.

…that is reflected only that only 3. 5 percent of new drugs are generated out of Mexico. And most of that has to do with communication. It's important that we have these type of channels, like the one that you are promoting, Chris, to teach people that it's okay to start your clinical trial in Mexico. You can approach the FDA about it. Be very transparent with the FDA always. But don't let the communication gap, not only the language, but also the culture… the paperwork is very extensive in Mexico.

Don't let that stop you from generating data that you can later use for submitting to your investors and, obtaining more funding.

Antonio also mentioned the opportunity to expand into Latin America with, for example, devices already approved in the US.

For a 510K device that you already have obtained approval for in the U. S., You can easily transfer that into Mexico very simply because you have all the data that you've used, you’ve generated it to demonstrate that it works and is similar to other predicate devices out there in the market.

And you've generated that information for your filing for the FDA. All that information can be then translated by our team and we can pass it on to COFEPRIS and the process is similar to the U. S. as well. But it's... You get the advantage of tapping into sometimes virgin markets where there is absolutely no other alternative to that device or to that diagnostic in Mexico or Latin America.

So you have a winning hand in leveraging tactics to negotiate with, like commercializing agencies in those countries. Whereas in the U. S., you have more competition. It takes longer to get your market traction. So it's a win-win situation.

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rEthix is developing an app…

Let's say you have a new discovery in your research institute, and you've received approval from your tech transfer office to take your technology out into the commercial markets and you have partnered with us to help you get your innovation out. We are, as part of the app, what it's going to be, it looks at all the data that you have, implements AI, And determines what is the best pathway in terms of the study design, the type of protocol that needs to be developed for better for commercialization for your device or your drug or your diagnostics.

Until the app is ready, they are building an incubator in Houston at the medical center to connect life science companies to share ideas and facilitate access to data that will generate traction for IRB studies in Houston.

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Jamie Gier is the Chief Marketing Officer at Dexcare, responsible for establishing the company as a category leader in modernizing the way consumers discover, access, and choose their healthcare services – from digital search to booking an appointment.

We enjoyed a wide-ranging discussion about marketing beginning with selling high-value products with long sales cycles and multiple decision makers. You’ve heard it before, but no one wants to be sold to. That’s the expressway to the delete button. Jamie emphasized building relationships and educating, showing customers how their lives could be better.

At Dexcare, her team learns a lot from early adopters about why they chose their product and continue to use it. Ask as many questions as you can, just like we talked about last week… We don’t know what we don’t know.

Jamie and her team are taking advantage of thought leadership in a big way.

We happen to spend a big portion of our media budget on LinkedIn, for example, that happens to be the channel where a lot of our buyers are, and there's a lot of thought leadership.

And so if anything, we've really focused our paid media on a single channel and we want to get really, really good at that. And so that's where we're placing a lot of our investments, but it's one of many. We know as soon as we capture their attention, a relationship begins. And that's where we have to start developing even higher levels of trust and rapport beyond just what they see with us in a digital way….we spend a lot of time with our clients simply promoting their own thought leadership on these topics.

That's number one. Two, we do spend time on building content that is education- rich.

Measurement is important and of course. I asked her how she makes the case for the tactics that are harder to measure. Observation and paying attention. When you land a large deal because someone heard about you on a podcast, that’s a pretty good sign.

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Jamie thinks that because of the emphasis on measurement, marketers have moved away from creativity. That took us on a little side trip to talk about Jimmy Buffett, who died right before this interview, and storytelling. I had written a piece for LinkedIn (not posted) about the impact JB had on my career. (DM me for details).

Besides writing fun songs about pirates and exotic places, Jimmy’s clever use of language to make emotional connections set him apart. Jamie said:

The thing about Jimmy Buffett is he brought you into his world, or he went into yours. And that was the power of the words he used in his songs.

With one top-10 hit (not even close to his best song) Jimmy Buffett built a business empire around his collection of memorable characters and events. We should try to do the same.

What advice does Jamie have for marketers just getting started?

• Join communities where you can learn. (I recommend SAMPS) and

• Don’t be intimidated by people with advanced degrees. They may know a lot in a technical field that took years of study. And you know (and love) marketing! Learn what you can from them, but also show them how you can help them with what you know. Science doesn’t get sold without storytelling.

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Julie Garlikov is Chief Commercial officer at Sherlock Biosciences where they are developing over-the-counter diagnostics to put answers in the hands of consumers and empower them to make better health decisions.

Sherlock is developing two platforms - a disposable test and a reusable reader for home diagnostics. You can listen to the podcast for some details on the science. Let’s focus here on VOC in design.

Consumer-centric design for me is really all about embodying the methods of design thinking. Which is really making sure that you have a deep understanding and empathy for the user that you're designing for. And that you're solving a problem that they really have, and that you're doing it in a way that fits into their lifestyle or their needs.

This approach involves lots of research, qualitative and quantitative surveys, prototyping and ethnography.

Ethnography is more than observing how they use the product under development. One can learn from understanding how they use any product. Even the buying process is investigated. How do they shop for groceries?

When it comes to the product itself, do they understand the instructions for use?

More good stuff coming in future episodes. Don’t miss it.

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If you are developing a diagnostic for sexual wellness, you need to know not just the population dynamics of STIs but also people’s attitudes and beliefs around their sex lives. How do you reach people based on what you know about their behaviors? The results can be surprising.

… one thing that I uncovered in this attitudes and usage study that we did with almost 1300 people, young people in the U.S. was a group I'm calling, it's like a segment of the population, I would call frisky-riskies.

So frisky-riskies is a group that skews a little more male than female and they're a group that's engaging in behavior where they have more frequent casual partners, and they're not often using protection, and they know that they're not using protection, and they know that puts them at risk.

So, what's interesting is that they actually test more than other people because they use testing as a way to mitigate the things they're doing that they know are causing risk for them.

The ability to do home testing for all kinds of indications can certainly reduce the spread of infectious diseases and help move us forward to thinking about prevention and general wellness. In the case of STIs which can be asymptomatic in women, there are implications for fertility as well.

As I think about our conversation, it struck me that we all have an opportunity to make products that will improve people’s lives in some way. But what can we do to make the biggest impact possible with the products we make or the services we offer?

It seems like asking questions and observing the behaviors of our ideal customers offers a big return on a little extra effort.

I just realized last week’s episode reached a similar conclusion about how the early work in any project seems to have an outsized impact. It’s like painting a house. The quality of the outcome is all in the preparation.

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Cheri Walker and her colleagues started Rhinostics in the middle of the pandemic in response to the massive increase in testing volume required to keep faculty and students at Harvard safe from Covid. That’s a story in itself. The principals never met in person for the first nine months!

We had all of our calls virtually. It was all done telephonically, I mean in Zoom. I basically started the company out of my guest bedroom because we didn't need space for the first year. We now have a facility which you can see behind me and we have, you know, all the normal things that you would have as a company grows and expands.

Make sure you listen to get the details on that.

But those workflows I mentioned…

Remember the nasopharyngeal swabs that ticked your brain? No one likes those and processing those samples in that format is cumbersome.

Harvard developed a new type of polypropylene swab with an active end that interacts with a decapping robot. By developing and manufacturing this new type of nasal swab (no more brain tickling) Rhinostics was able to create:

• A better patient experience with a more comfortable, DIY swab.

• A smoother automated workflow with faster turnaround and

• Potentially reduce turnover of medtechs in the lab

I think that's been the flip side of starting a company in the pandemic is just the supply chains and labor and all those issues. And then when you actually talk about the problem that we're solving and the real pain point that exists in laboratories today. Not only are there the cost structures and things like that, it's just finding med techs and people to work in the lab.

And a lot of them got burned out. There was a small number before the pandemic, but a lot of them got burned out. And med tech now is making anywhere from 125, with 20, 000 signing bonuses. And, you know, retention turnover in the labs is something in the 25 to 30, 35%. So, it's a real issue, um, facing most of the laboratories right now.

The automated workflow removes the manual step of decapping swabs before analysis. Barcoding ties the sample to the patient through an app on their phone and allows for better sample tracking. Both of those make for a better experience for the user and the med tech.

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The insight here is that rethinking workflows and a small, unsexy device can have a huge impact on lab productivity, patient health and worker satisfaction. No medtech went to school thinking they would be uncapping tubes all day, rather than looking after equipment and solving problems.

I asked Cheri where sample collection is going in the future. There is definitely a move toward home testing. The pandemic proved that it can be done accurately. There is currently an epidemic of STIs (sexually transmitted infections) for which the option of buying a kit off the shelf at the pharmacy would seem to be a way to discreetly get individuals to seek treatment if necessary while maintaining some privacy.

Cheri also mentioned, for example, having a teenager on Accutane where blood lipids needed to be tested on a regular basis.

You could send our little VERIstic® blood collection device, do a finger prick, send them home with ten of them, and then they can just do it and send it back. They don't have to drag their teenager back to the clinic to stay and wait for a blood draw and keep them out of school…

…it's interesting because everyone, it's not just home health and kit providers that are interested, like the whole hospital health system is trying to figure out how can we use these tools to actually have better health care for people that's more convenient, but still just as accurate and maybe get more compliance.

More powerful analysis on the back end of testing is great, but across life science, I wonder if the real opportunities to make an impact are at the front end of how we do things.

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Hiring people is difficult, expensive and risky. It’s a skill in itself for which most of us get very little practice. I talked to Ken Schmitt about how hiring has changed and a few things to think about when filling a role on your team. Fun fact: Ken got his first job at a staffing agency by answering an ad in a newspaper!

Ken’s agency specializes in placing marketing and salespeople. I asked him about skills that drive hiring decisions:

…marketing especially needs to have that experience and understand the language of sales as well to be truly effective on the marketing side and be able to understand the broader business, not just marketing… is the center of the universe, but marketing is much less of a linear role, if you will, or a stop along the way. And it's much more circular.

You know, it used to be that marketing did this, this, and this, and then stopped, handed it off to sales, and now sales took it from there. But now it's again, a much more circular kind of collaboration and relationship. And so whenever we're talking to candidates about the senior level marketing searches that we're doing, we're asking them, tell us about your experience collaborating with sales.

How a candidate collaborates with sales is important. There are plenty of good marketers without it, but I’d say actual sales experience would be even better. Looking back at my own experience, it’s stunning how little marketing (marcom at least) was connected to sales in the life science companies where I worked. We could spend a few episodes on that…

When hiring, Ken recommends looking at your team as a whole. What skills do you already have and what gaps are you looking to fill? Are there people from outside the industry who can bring new ideas and new skills to the effort?

We discussed whether and when a college degree is necessary. This is an evolution I find fascinating. I think a fair amount about whether and how much we discount or overvalue our degrees based on many factors including how long ago we attended college or specific classes we took but no longer see how they might have been relevant.

I’ve known great marketers with no science background and we put scientists into marketing roles with no marketing background all the time. I’d love to see your comments about what you think is necessary and or optimal.

I have several interesting episodes in the can already. Don’t miss ‘em.

Thanks for being here.

My favorite part of the conversation was about employer branding. As a content marketer, this speaks to me. Every company has a brand in the eyes of its customers. There is also a brand in the eyes of its employees and potential hires.

Let’s look at it like a marketing funnel. At the top there is what your company does, but also what it stands for. What is the culture like? Does the actual culture reflect the aspirational statements or taglines one often hears?

At the middle of the funnel are job descriptions - another candidate for a full episode. My sense is that many employers aren’t thinking about whether a job description might turn away qualified candidates based on the way it’s written. I often see descriptions that seem to say, “Don’t be like the last person who had this job…” Hmmm. Something to think about.

I understand the description needs to be accurate. Can it be inspiring at the same time? I’d like to think so. Given that the job description is one of the first impressions for new hires, it’s a significant part of your brand. Why not show it to someone outside of your company and ask them what kind of impression it makes?

Of course, the bottom of the funnel is the interview and even the onboarding experience. From personal experience, I’d say these things matter a lot. A small investment of time and effort upfront will pay off many times in the long run.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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A new antimicrobial cured mice infected with bacteria deemed nearly “untreatable” in humans — and resistance to the drug was virtually undetectable.

The World Health Organization has identified antimicrobial resistance as a major threat to global health. Bacterial resistance to antibiotics only increases over time. The problem is made worse by the fact that the incentives to discover and develop new antibiotics aren’t aligned with the pharmaceutical industry model.

It takes billions of dollars to bring a drug to market and years to recover that investment. Sporadic 10-day prescriptions can’t compete with lifelong prescriptions for blood pressure reduction, cholesterol management etc. in terms of ROI. As a result, only one new class of antibiotic has been developed since the year 2000 and there are few new candidates on the horizon.

In a previous episode, I spoke to Dr. Randy Rohde about methicillin-resistant Staph aureus and the importance of science communication in public health.

In this episode, I talked to Mike Mahan, Professor in the Department of Molecular, Cellular and Developmental Biology at UC Santa Barbara. We talked about:

• The challenges of developing new antibiotics and the need for new business models or societal incentives to pay for them

• A supplement to the gold standard test for susceptibility that can lead to better patient outcomes

• A promising candidate for a new class of broad-spectrum antimicrobial for which resistance is virtually undetectable

Tackling the problem of antibiotic resistance will take effort on multiple fronts. As a society, we need to recognize the seriousness of the problem and decide to invest in the development of new drugs and models that can support that development. For example, a subscription model where companies are paid to develop and have antibiotics on hand whether or not they are used - a kind of strategic reserve. Jason Scharf and I discussed this in a previous episode.

Improved Predictive Susceptibility Test

First of all, are we using the antibiotics we have to our best advantage? Apparently not.

The gold standard test for antibiotic susceptibility is done in rich media (ideal conditions for bacterial growth). If the test more accurately reflected in vivo conditions, would the same results be observed? Mahan and his colleagues have done the test. Comparing the results of the susceptibility test done in either rich or minimal growth media (closer to the host environment) with the ability of an antibiotic to cure sepsis in mice, in ten percent of cases there was disagreement between the gold standard test and the new test in terms of a clinical threshold: Is the bacteria resistant or susceptible?

Using this test, we now check FDA-approved antibiotics that are dismissed by the gold standard test… there were several antibiotics that were highly effective in treating sepsis in mice that are never used by physicians because the gold standard test says it won't work. Consequently, our toolbox for antimicrobial infections is much larger than we once thought.

A promising new class of antimicrobial

In a separate line of inquiry, conjugated oligoelectrolytes (COEs) were being investigated by a colleague for charging cellphones on the battlefield - a bacterial battery if you will, using bacteria and an energy source to drive electron transport. It’s no surprise that pumping electrons out of the cell for this purpose, rather than inward, is harmful to the bacteria in the long run.

Because of this, it was hypothesized that COEs might be candidates as new antibiotics. Mike was skeptical. He thought that these compounds would be comparable to using bleach - great at killing bacteria, and very toxic for humans. “This is gonna be a really short collaboration,” he told his lab manager.

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They tested 17 different COE compounds for antimicrobial activity and toxicity in mammalian cells. All 17 had no problem killing bacteria. And most of them were highly toxic for mammalian cells, as predicted. But one of the 17, COE2-2hexyl, showed promise as being less toxic for mammalian cells.

The next thing they did was immediately test this compound for its effectiveness at curing sepsis in mice. Mice were infected with a range of pathogens, including an isolate from a patient that had succumbed to refractory bacteremia - a multiply-resistant strain of Klebsiella from a community-derived urinary tract infection.

They evaluated toxicity in mice via a blinded measurement of attitude scores (appearance/activity/clinical signs) as an outcome of drug treatment. The compound was well tolerated and able to cure sepsis in mice.

However, the most remarkable observation was that resistance to this compound is virtually undetectable and it is effective against both gram-positive and gram-negative bacteria, presumably because it interferes with multiple membrane-based functions.

Reflecting on this episode, beyond the obvious takeaways here about business models, improved testing and innovation, is the need to allow room for doing some things differently.

I just learned this week that RNA editing is a thing and might be tested as a therapy ( I don’t remember for what) in clinical trials. This is a long way from what I knew about RNA, even in graduate school. But I was not surprised because remarkable innovations pop up every week in our industry.

What is surprising is that a simple innovation that challenges a decades-old susceptibility test is met with resistance (no pun intended) because “that’s the way it’s always been done.” That resistance isn’t really a challenge about the science. It’s one of psychology - getting people to change their habits and ways of thinking.

This has been a summary of the technical highlights. If you want the entertaining story of the scientific journey, give the full episode a listen. I think you’ll enjoy our lively conversation.

Nature Medicine: How to Fight Antibiotic Resistance

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I enjoyed this conversation with Adrian Rubstein, founder of Ax3.bio, as he opened my eyes to different approaches to valuing startups. Make sure you listen to the full episode. I promise you will learn something valuable.

Adrian inspired me to do some research on my own. So any errors in this description are mine. (A little knowledge is a dangerous thing). But let’s try anyway…

Most biotech companies are destined to fail. That’s no secret. Biology is full of uncertainty.

Outcomes in biotech are binary. A device or a therapy is approved for use or it is not, making valuations challenging. Even after approval, there is the challenge of gaining market share. It’s fair to assume, that growing the market for most therapies is not possible except by encouraging unhealthy behavior which is probably not part of your brand strategy.

Adrian talked about understanding and evaluating the science in addition to assessing the size of a potential market. Ax3.bio employs a modified Real Option framework, modified for binary outcomes, for evaluating potential investments. This is way above my pay grade but I found this article from McKinsey helpful to get a sense of how this works. The article goes beyond using the framework for valuations to how it can be used strategically to understand the levers available to maximize value.

If you just want the TL;DR, industries that require a lot of R&D, manufacturing and marketing investment can benefit from this framework. The example they give is drilling for oil and gas in the North Sea. Once a company has the right to explore blocks of the sea bottom for oil, they still need to figure out which ones might have oil, how much, and what it will take to get it out. All while the price of oil fluctuates over time.

There is a lot of uncertainty at each step, not unlike developing new therapies. The model values the flexibility to make decisions about investment at each step while taking into account the possibility of changing market conditions.

…as my economist friend says, “Models, they don't work it out, but they give you a compass on what may happen.” That's why we do sensitivity analysis and we say those are the different scenarios, right? The first one is that, okay, you get approval from the FDA, and then what is the probability for you to get acquired?

The probability for you to hit a milestone? The probability that, okay, right now the KOLs like your product. What is the probability for you to get exponential sales? Or not. They're totally different scenarios and each scenario has a probability for it to happen. So that's a huge decision tree analysis.

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As in the McKinsey article, this analysis can also be used as a strategic guide for the things you can do to raise the probability of success or a higher evaluation at each step.

Many of these are familiar: Relationships with KOLs, publishing articles, letting people know about your progress and milestones through newsletters, podcasts etc. As has been mentioned several times on Life Science Marketing Radio, you can’t wait for approval to start telling your story. At that point, it’s too late.

This got me thinking about the relationship between uncertainty and stories about a company’s journey over time. Many stories are based on uncertainty. Every athletic competition is a story because of the uncertainty of the outcome. And the more uncertain, the better.

Presumably, each milestone on the company’s journey reduces uncertainty by some amount. This can be compared to a team’s progress toward a championship over the season. Just as you resolve one question, attention turns to the next victory (milestone) to be achieved.

There are also individual stories within a team story that can be captivating. Every one of these milestones and individual stories is an opportunity to get people interested in your company.

Would it be a stretch to say that stories themselves can increase the value of your business at any point? I don’t think so.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Visit Life Science Marketing Radio to learn more about how I help companies tell their stories.

Ax3.bio

Adrian’s Newsletter on LinkedIn, BioBusiness,

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It will come as no surprise that I have talked to a number of people in marketing and sales recently. (That’s literally half of my job.) Sometimes, those conversations all seem to point in the same direction. This month is one of those times.

The theme that has arisen spontaneously is how potential customers become customers. And the assumptions we make around that.

The assumptions are that:

• Potential customers know who we are.

• We have the product or service they need.

• Our product is demonstrably better (on some criteria) and will win the day.

We also assume that we know why our customers buy, and even that they would know, if we asked them, what got them on the path to purchase our product or service.

Some of the things I heard:

• Most people who could buy from us are not in-market at any given time. How do we get into their consideration set when the time comes?

• Our customers are only interested in specifications. Stories shared on social media have little value. (I disagree.)

• A very large, new customer found out about us through a podcast (dark social, I heartily endorse).

• Many companies have no process for leads (contacts?) to be systematically converted to sales. - I suspect many of you feel better about your efforts now, huh?

• Someone needs to set the frame to have a productive conversation. (Thank you Brian Morgan.)

That all leads me to corporate communications. Given all of the ambiguities, even after mapping out customer journeys and measuring every possible interaction, we need to start the conversation somewhere. And the earlier the better.

There is no way every potential customer, investor, etc. knows who you are, why you exist or what you do. Assuming otherwise is leaving money on the table. As is assuming that your specifications can overcome whatever rationale the customer already has in their mind at that very late stage in the buying process.

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Ryan Flinn is a corporate communications expert who knows what makes an interesting story. As a former Bloomberg reporter, his performance was measured on the ability to gather eyeballs.

The fact that people make decisions based on emotion is well established. Those emotional engagements can happen very early with good corporate communications. It happens by sharing memorable stories about how people use your products and services. For example, you could explain who designed them along with why and how.

Or show how the founder’s hobbies relate to the company. Ryan explained that Bloomberg had reporters covering large companies on a daily basis.

I had to find articles that they didn't deem important enough to cover for like a news beat, but that I could kind of twist into an interesting angle. So, like for one, I did a profile on Autodesk, the CAD software company because I found this angle of the CEO… He has the woodworking shop in Berkeley, and he carves tables and chairs and, you know, it's the analog to the digital version of what the software does.

…looking beyond just again, the bullet points of what makes a product interesting or important to consumers. What is the angle that will help the reporter write a story about it or somebody going, “Wow, what a cool example. I wanna learn more about that”?

Ryan shared his insights on what makes an interesting story, how they can create a competitive advantage and how to build relationships with reporters that can lead to earned media opportunities.

As I reflect on this episode and my recent conversations (you’ll hear from more of those folks soon), I think of how assumptions about our audience get in the way of our marketing at one stage or another. We need to do well at every stage. And just because we can’t measure something doesn’t mean it’s not worth doing.

What activities grab a person’s interest? If that person isn’t a potential customer, what might make them share it with someone else who could be?

Is our content memorable enough to get us into the consideration set when the customer has a need? Have we made an emotional connection that provides an advantage? Will we deliver a story and an experience that makes the customer confident in choosing our solution?

Marketing is kind of like hosting a cocktail party. It’s a conversation we are having simultaneously with a lot of people joining in over a long period of time. We are continuously inviting new people to that conversation while at the same time introducing some of them to our dear friends in sales.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.

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I’m not a healthcare expert by any stretch except as an occasional recipient of care that I’m generally happy with.

As an observer, however, our system, in the US at least, looks fractured. Many people don’t have access to care. At the same time, significant innovations are racing along, but many physicians are likely too overwhelmed to incorporate new technologies like genomic testing. It probably feels like jumping on a moving train. Does that further increase the disparities in the system? How can we lower the risk and make it easier for doctors and healthcare systems to adopt advances like precision medicine to deliver better care?

In this episode, I talked to Jeff Owen, VP of Marketing at Genomic Testing Cooperative about their business model and how they are trying to make comprehensive genomic testing routine and more accessible.

There has been an explosion in biomarker-driven therapeutics.

Yet, pathologists have expressed dissatisfaction with bringing genomic testing in-house, even with the best kits and equipment, seeing it as a moving target.

The co-op model helps them keep pace by acting as a reference lab for systems with low test volumes, while guiding internalization, providing shared resources and education for higher-volume users. GTC manages the bioinformatics pipeline to simplify things further.

This can help drive down costs and increase the consistency of testing and results. And drive a revenue opportunity.

And a lot of pathologists are scared of next-gen sequencing because they think it's gonna take their job. And our company was founded by pathologists who understand that fear. But we also wanna show 'em maybe a different way of thinking about it, right? Because the next-gen sequencing is coming, right?

…you're trying to stop technology that's coming. It's kinda like maybe a lot of people with AI right now, they're afraid. But this is the new tc/pc (technical component/professional component with respect to billing) The reason pathologists like the tc/pc split is because it makes, it allows them to generate revenue for their hospital, which is oftentimes one of the things that is important for their employment, so to speak.

They have to generate a certain amount of money for their pathology department and the hospital to remain relevant… The margins are a lot better on next-gen sequencing than they are on some of the traditional routine pathology like immunohistochemistry.

The output of this testing is a recommendation to pathologists and oncologists on the best therapeutic options based on the specific genomics of a tumor. Ideally, by making this more accessible and implemented sooner for each patient, the right therapy can be prescribed earlier, improving outcomes.

Here is an example of how a business model can make a significant impact. I see a lot of life science or healthcare startups with innovative technologies or systems that are intended to improve patient care. But I see challenges around adoption and market penetration.

The co-op model gets around these by offering different paths based on volume and the benefit of a network effect. As more systems participate, more data can improve recommendations while each member of the co-op can share in new IP generated along the way.

GTC is conducting a Workshop, Chicago, September 23rd

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If you are a founder of a biotech or life science startup, you don’t want to miss this episode. If you’re not, you may still find it fascinating. I talked to Sal Buscemi about family offices and what kinds of assets they invest in.

Until recently, I didn’t know what a family office was. These are people or families with at least 100 million dollars of investible assets. They represent a unique source of funding for startups. They have different goals and timelines than a typical VC firm. As a result, you’ll need to take a different approach to communicating with them.

The takeaway here is the same as always for good marketing. Know your customer, and what they value. Craft your message/offer around that.

When you have that much money to invest, you certainly want a return but you also want to make an impact. And let your friends know about it. They are looking for statement-class assets. These are assets that are a conversation starter anywhere you go. Successful people want to be associated with successful people from other industries. Example: Be the first to show up with a million dollars and have a Nobel Prize winner join your family for lunch.

As I mention in the podcast, no one will shed a tear for the folks who have millions to invest to make more money. But there is a psychological burden on the 2nd and third generations. How do you demonstrate your own value, your skills, etc in the shadow of inherited wealth? Sal points out the scene in Ford vs Ferrari where Enzo Ferrari insults Henry Ford Jr by reminding him that he is not Henry Ford. He’s Henry Ford the 2nd.

So the question for them becomes, “What’s the best way I can make an impact?”

You can make an impact here by subscribing to the podcast wherever you listen and to my newsletter.

Thanks very much! You did subscribe, didn’t you?

Sal stressed the importance of relationships. Patience is your friend. No “quant-splaining.”

People today, if you were to do some research, they don't trust facts and figures anymore. They trust the stories, and that's really what it is. And they want to make sure that if they're sitting in front of someone, that person's gonna make the best decisions as a steward of their wealth and capital to go into it. Because at the end of the day, and everybody listening to this as a founder should really, really figure this out. Nobody is going to part with their life savings unless they give you their time first. And that's so important to remember.

And here’s a bonus, I think especially for life science and biotech companies. Some of these investors are looking at longer time horizons than a VC firm.

If you look at anything on LinkedIn or maybe on bloomberg.com, you'll see that, there is a bias right now where a lot of these families are going in and they're getting the same terms that, you know, any other fund would get, but they don't want to be alongside the fund because they don't wanna have someone that doesn't have at least a 10-year horizon with this. And I can tell you there's some families that say, Sal, don't even talk to us unless it fits our 40-year plan.

Finally, Sal noted the importance of media, going on podcasts! and having an online presence that your investors can point to that, again, make them look good. I have some ideas around that. See below and be sure to listen to the full episode.

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Free Book: Calling the Capital

Sal’s Firm: Harlem River Navy

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For a patient with sepsis (an infection in the blood), the chance of survival decreases by 7-10% every hour. It’s important to quickly identify what bacteria are present and which antibiotics might be effective.

Typically, there are very few bacteria in the blood. Culturing bacteria from a sample can take 12-24 hours and then one needs to test for drug susceptibility. Speeding up this process would save a lot of lives.

Jen Dionne and her collaborators at Stanford are working on this problem using Raman spectroscopy. Through a combination of nanophotonics, acoustic bioprinting, and machine learning, they are developing methods to quickly and sensitively identify bacteria and screen for antibiotic susceptibility.

What is Raman Spectroscopy?

Raman spectroscopy is basically inelastic photon scattering. So if you think about having a laser or some other monochromatic light source, you shine that onto your sample, say onto a cell, like a bacterial cell. And the molecular vibrations in that sample basically add to or subtract from the energy of the laser source.

You wind up with a fingerprint or a series of scattered wavelengths that are different from your incident wavelength. And you can use that spectrum to identify the constituents of what's in your sample.

Raman spectra of complex mixtures appear as a wavy line, more like a snapshot of an oscillating jump rope than a series of distinct peaks that you would get from a pure sample of a small molecule.

Here is what you need to know:

• It’s possible to do Raman spectroscopy on whole cells. By training machine learning models on thousands of bacterial samples, Raman can identify different bacterial species and determine which ones are resistant to specific antibiotics.

• Raman is typically not very sensitive but the efficiency goes up by the 4th power of the electric field strength. Surface Enhanced Raman Spectroscopy (SERS) using nanoparticles made of superconducting materials can focus light energy to a very small region without heating and destroying the sample, boosting the sensitivity. The added sensitivity allows the collection of more data (better resolution, more specificity).

• Spectra can be collected in flight as droplets (of blood for example) are acoustically ejected at kilohertz frequencies and printed on a substrate. The identification of bacteria by the spectra can be confirmed by electron microscopy of printed drops on the substrate.

Rapid diagnosis of sepsis is just one possible application. Analysis of environmental samples and wastewater epidemiology are also possible with this method.

The takeaway for me is that with a large enough data set of samples, machine learning algorithms can identify subtle features that would never be possible for a human being. Adding more data through nanophotonics opens up even more possibilities to tackle bigger problems.

More about SERS

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Cover Image Credit (energy states): Moxfyre, based on work of User:Pavlina2.0, CC BY-SA 3.0, via Wikimedia Commons

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Steve Harvey and his business partner managed to raise enough money to rent some lab space in Cambridge (UK) to get started on an idea they had for synthesizing template-free DNA.

The Start

They invited an investor to meet them at the lab where they sat on the garden furniture Steve brought with him because they had nothing else.

TL;DR They got more money. Camena Bioscience was getting started.

That was the first hurdle. There were more. Competitors had similar ideas around the IP. And evolution had a different idea, altogether.

Synthesizing DNA without a template means providing an enzyme with modified nucleotide bases so that only one can be added to the DNA chain at a time. After addition, a blocking group is removed, allowing the next base in the sequence to be added. That’s the only way to end up with the gene you intend to make.

The problem is that most enzymes are very good at what they do. In this case, the enzyme, terminal deoxynucleotidyl transferase, naturally prefers unmodified nucleotides (evolution). If there are any of those contaminating the mix, the enzyme will add a string of them even before you can spell “DNA”. The end result is likely a lot of DNA of the wrong sequence.

The Pivot

Steve decided it was time to take a different approach. (If you meet a founder who has never had to pivot, congratulate them.) It’s a hard thing to do after investing time and money and being (partially) successful.

The new approach seems to have worked out. Camena published a couple of application notes and they were picked up by Nature Biotechnology for a story about DNA synthesis technologies.

Now they were getting customers but awareness was still a challenge.

I had a couple of people that came to me and said, “We've looked at your website. We, don't really know what you do.” Okay. And so I decided that we need to get some kind of numerical value on brand awareness.

I announced the team, “We're gonna run some brand awareness surveys. We'll put it out via LinkedIn and Twitter as well. We'll understand, you know, do people really know what we do?”

And I put it out and I was quite excited about doing this. And then I think it was two weeks later, we'd had five responses. And I think one of the responses was from a family member. So, so it didn't go very well.

But Steve wasn’t deterred. He tried again with the offer of a $25 Amazon gift card.

I think it was within a week we had 2000 responses. So it was, the whole thing was really funny. But what came out of that was that, it was roughly kind of 75% of people that responded to the survey had only heard of us in the last six months, and we'd been going for nearly like six years!

Hey, that’s progress.

The Story

Steve decided to post regularly on LinkedIn about his journey, which is how I found him. He did a great job of posting a little bit of the story each day, (like Charles Dickens!) and teasing what was to come.

His followers have grown significantly and no doubt more people know about Camena Bio as a result.

In my own experience, authentic personal stories get the most traction. People are interested in people. Products are useful. People are fascinating. You may not think you are, but I’ve interviewed hundreds of people across several podcasts for myself and my clients. Only one was an absolute dud that left me with nothing to publish.

Find your channel. It might be LinkedIn, your blog, a podcast, someone else’s podcast or that thing that was Twitter yesterday, but is apparently “X” today.

Schedule a 15-minute chat with Chris about turning conversations into content for your life science company.

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Science is pretty cool. We can send astronauts to the moon, watch tv on a phone that fits in our pocket or rid the world of smallpox. It makes problems go away so well, it’s as if they no longer exist. That can be a problem in itself.

In this episode, I talked to Dr. Rodney Rhode (Doc R) about the role of science communication in public health. To get warmed up, we had a conversation about the state of infectious diseases like rabies and MRSA (Methicillin-resistant Staph aureus).

The incidence of rabies is on the way down (Yay, vaccines!) MRSA is on the way up (Yay, antibiotics?). Much of our current life expectancy can be attributed to the development of vaccines and antibiotics in the last century. These two examples show how, in some ways, we can become the victims of our own success and why science communication is still very important for public health.

When my daughter was about five years old, she was bitten by a dog at a little league baseball game. The dog was new to the owners who were uncertain of its vaccination status. It was a stressful time considering the possibility of putting Ellie through a painful series of shots to avoid rabies, which might otherwise be fatal.

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Fortunately because of our vaccination requirements, getting rabies from a dog bite is very rare in the US. One might assume that’s true elsewhere as well. One would be wrong. This is important information for travelers who might encounter an unvaccinated animal on the beach in another country.

There is still a risk of rabies in the US, where the primary carriers are bats. Surprisingly, one can be bitten by a bat and not realize it, reaching into a woodpile, for example. Doc R shared this:

And in many of these cases, you can look these up at CDC, there's some unfortunate ones, might have been a child… actually reported being bit by a bat. And the parents weren't aware of this rabies issue and they just kind of moved on. And then two, three weeks later, first symptoms… once symptoms start with rabies, you're pushing 98, 99% fatality.

That is an example where science communication can save lives.

Antibiotics present another success story that maybe we’ve learned too well. The overuse of antibiotics has led to resistant strains for which there are few or no effective antibiotics anymore.

Can’t we just make new antibiotics? Let’s hope so. There are scientific and even economic reasons why that is more of a challenge now - a subject for a different podcast. But chasing the next cure is a never-ending game. This brings me back to the value of science communication.

If you want to make an impact and save lives, you could look for the next cure for [fill in the blank]. Or you could help people avoid disease altogether. You might be able to develop a drug that will cure cancer. Maybe. And we should definitely try. But you can absolutely help someone understand and appreciate science. And that might actually save (many) lives someday.

We live in a time where it’s easy to take aspects of our health for granted. One can look around and say, “No one dies from “X” anymore, why do we even worry about that?” The answer is “Because it wasn’t always this way and may not stay this way forever.”

One might be able to say an antibiotic saved their life. They had a serious infection and the drug made it go away. Few people can say, “This vaccine saved my life.” Because they never got the disease and likely weren’t even exposed to it. But we know lives were saved. A lot of them. It’s just difficult to say whose exactly.

Many of us will enjoy the privilege of growing old because of a disease we didn’t get. Thanks to a vaccine. Or an antibiotic. Or now, cell and gene therapy.

I had the opportunity to interview Dr. Peter Hotez last fall at The Welch Conference where he spoke about the growing anti-science and anti-scientist movement. Every day on Twitter, people accuse him of being part of some huge conspiracy. I admire him for the example he sets. He calmly points out that all he has done is to create a patent-free Covid vaccine for distribution (nearly 100 million doses) in low-middle income countries. He is never rude or aggressive.

Peter has also been a mentor to Rodney Rhode. I asked Doc R about how we can talk about things like vaccines with people who have this extreme level of distrust in science. His suggestion was to engage them and ask questions about why they think the way they do and just listen. You may not change many minds but building trust is important.

We’re all on the same team and want to help each other. Let’s assume that much. Learning how to talk about science and have people understand is the first step and the best path is education.

If you are considering a career in science or are looking to make a change within science, know that you can make an impact outside of the laboratory. It’s not as sexy as finding a cure for cancer. It’s not CRISPR and cell therapy. It’s the hard work of learning, thinking, writing and speaking. But you can save lives with a pen as easily as with a pipette.

I really enjoyed this conversation and I’m pretty sure you will too. You’ll hear what a passionate and engaging science communicator sounds like. Make sure you give this one a listen.

SciComm:Bacteria aren’t the only drug-resistant pathogens. A recent article from Doc R. And Thank You to Lemar Ashar for connecting us!

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand.

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What is the cost to an employer of chronic presenteeism, where a person is well enough to go to work but isn’t really productive? What is the dollar value to a patient of being married in terms of health outcomes? How do you figure that out? There are so many factors to consider.

When we read that condition [fill in the blank] accounts for X dollars of lost productivity per year, I always wonder, “where does that number come from and who came up with it?” In this episode, we find out.

Lemar Ashar, a previous guest on Life Science Marketing Radio introduced me to Mark Gannott, to talk about pharmacoeconomics. We explored the cost and value of medical interventions, particularly drugs, from various stakeholders' perspectives (patients, healthcare providers, insurance companies, and healthcare systems). I was curious about the challenges of estimating disease costs and treatment impacts, where the data comes from and how it’s used to make decisions.

Genomics, including genome-wide association studies (GWAS), and polygenic risk scores also play a role, potentially improving health outcomes and reducing side effects.

We touched on a few specific use cases, such as the treatment of endometriosis and the use of polygenic risk scores in depression.

I found it fascinating to get a glimpse into how decisions around the development and use of different drugs are made.

Mark thinks that in the future, a field called precision pharmacoeconomics will incorporate personalized genomics data to assess the cost-effectiveness of drug therapies.

If you want a (sort of) quick intro into the topic, this is the episode for you.

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Before becoming the CEO of Diaago, a distributor of labware for life science, Jackson Hyde spent some time managing a staffing agency, placing day labor with companies filling short-term needs. That gave him an appreciation of flexibility and an understanding of the diverse needs of employers but also employees.

As the founder of Diaago, Jackson’s management approach emphasizes the importance of understanding the whole person and their individual requirements in the workplace.

I think that the first thing we have to look at is how, how diverse any workplace is, especially when you're dealing with a manufacturing type of facility. You know, you have people that make the product. You have people that design the product. You have people that sell the product or market it in whatever way.

So there's a lot of different processes happening and it's different people and different backgrounds that are gonna fulfill all of that. So at the end of the day, to be successful, you need to get the most out of people. And I think one of the ways that is underutilized, is taking a look at the whole person in that process. And seeing not only how they all fit together, of course, that's a whole other conversation. But looking at what each person needs to get out of their work.

He challenges the concept of work-life balance, suggesting that work is an integral part of our lives and should be meaningful and fulfilling.

It might be interesting to talk about the idea of a work-life balance for a second. It is an idea that could use some reflection. Right now, we're in an interesting place, kind of post-pandemic.

You know, people have gotten used to one way of working. We're pushing people back towards another way, depending on your take on it, but I think what’s outdated about that concept is that it never really existed to begin with. It's almost, counterintuitive to think about it because there are very few jobs or careers where you can come in in the morning and leave in the evening and never think about your work.

We're all gonna think about it no matter what we do. It is a part of our life. So the idea of the work-life balance that has been thrown out to us is, okay, you need to separate work and life. And, it's two separate things. But it's really not, it's a part of what defines us. It's part of what completes our human experience.

It's finding worthwhile and, and meaningful work.

On the other side of that, he recognizes the privilege associated with following one's passion. Not everyone has that opportunity. It’s the responsibility of leaders to bring passion and purpose to employees' work.

We can bring some passion to their work. We can bring in the outside influences to show them what makes their work important.

For example, on the manufacturing side, being able to tell people, “When the products leave our warehouse, they're going to a facility that's researching cancer and you're a part of that.”

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I went to SLAS this spring to talk to old friends, meet some new ones and learn whatever I could. I met Maggie Vantangoli, the Director of Marketing at Araceli Biosciences in their booth where we chatted about the use of artificial intelligence (AI) for high content analysis (HCA) in drug discovery and development.

She was kind enough to join me on this podcast and fill in the (large) holes in my knowledge of cell biology. HCA is basically automated microscopy and analysis of fluorescently-stained (or otherwise) cells to identify changes caused by various compounds. This rich phenotypic information can provide valuable insights into how a drug or compound might work or whether it could be toxic.

You can listen to the podcast to learn about how HCA is used to group compounds based on the morphological changes in cells exposed to them.

A few things stood out for me. In terms of AI, the most interesting application was that of unsupervised learning, where the AI can learn to detect patterns that a human might not look for or even see if they were looking. One can imagine that a lot of information about biology could be uncovered aside from evaluating potential therapies.

When I asked about where HCA might go in the future, Maggie talked about doing tests on organoids as a replacement for animal models. This is a topic that has come up in a few of my conversations lately on and off this podcast.

I also asked Maggie what she thought about the possibilities for combining HCA with DoE (Design of Experiments) that I featured a few episodes back. Thankfully, she listened to that episode. (You should too.)

I definitely think there are amazing applications here and you know, I think it's a massive amount of untapped potential, particularly in that high content space.

I know that different aspects of drug discovery are getting there, particularly like the structure-activity type relationships. But I think this is a completely untapped market for the DoE type of type of work and there's huge amounts of applications because high content's also, you know, per assay, like most assays in drug discovery, there's cost associated there and that's not... When you're scaling up, that is not in insignificant amounts of money. So running millions or even tens of thousands of compounds a day with staining and all the liquid handling and tips and all of that is, is quite expensive. The amount put into that one little plate is extremely expensive.

So you can kind of do your work ahead of time and, and utilize the Design of Experiments to stack the deck in your favor.

Sorry to interrupt here, but you are subscribed aren’t you?

I get a special joy out of when two episodes connect in that way. I’m going to see if we can get Maggie to come back with Markus to discuss the possibilities.

I’d love to hear what you think of this episode or the podcast overall. Feel free to drop a comment.

Also, if you want to talk about custom content for your life science brand, let’s chat.

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If you don’t know SAMPS, you’ve been missing out. It’s the only association for Sales And Marketing Professionals serving the Sciences. I’ve been a member since 2014 and it has been a huge boost for me in terms of networking with and learning from like-minded professionals in our business.

Live events are back and the European meeting takes place right after ESHG, June 12 (cocktails and appetizers) and 13 (full agenda), this year focused on the use of AI for sales and marketing. And as always, there will be a panel of customers (PIs post-docs, procurement…) who will be happy to tell you why your email didn’t work or your website is hard to navigate and whose site they go to for good information. You don’t want to miss that, do you?

In this episode, I talked to Laura Haldane from SciLeads and Paul Avery from BioStrata as a teaser for the event. Paul has been geeking out on all of the latest AI tools and can tell you what’s useful and what to look out for.

Laura says she’s not a social media influencer, but casually dropped that she has 15,000 followers on LinkedIn. (I want to know her secret!) There will be a session on the use of social media for marketing and how AI fits into that workflow.

Sign up at the link below. I wish I were going to be there to see the sunset at 10:02 pm but maybe I’ll catch you in Boston in December.

SAMPS Europe 2023 - Agenda and Registration

SAMPS North America 2023

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I’m a big fan of The Prof G Podcast. Scott Galloway is a thoughtful guy and I’ve learned a lot from him. One of his common phrases is “It’s hard to read the label from inside the bottle.”

By that, he means, whether looking at ourselves or our business, it’s very helpful to get some outside advice.

This definitely applies to companies pitching to investors. First of all, the story you tell is very important for getting their attention and also for the final valuation. If you think it’s just about science and the data speak for themselves, you’re leaving money on the table.

I talked to Oksana Bovt from Theoria Creative. They help life science companies craft stories for investors. Your science may be exciting and innovative, but that’s not enough. You may have an opportunity to tell a better story that you aren’t even thinking about.

And you don’t have to be first to market to succeed. Oksana shared an example of a company going after the same target as a company that had already been bought. But because the new company approached the problem based on entirely different science, they were able to make the case that they weren’t just a little better, but significantly different.

In terms of the actual presentation, Oksana recommends, never letting the investor fill in the blanks. It’s important to keep their attention and connect all the dots. If they feel like they’ve seen something before, their mind can wander and make assumptions. Don’t let that happen.

Don’t miss an edition of this newsletter either.

And subscribe to the podcast to get the full story. Links at the bottom of the page.

What happens after you successfully raise money? Get ready to start raising again, right away. The fun never stops in biotech. You need to be constantly telling your story, laying out milestones on your website and making noise as you reach them.

Finally, what do you do when things go differently from what you had envisioned for your product or company? First, be assured that you are not the first company nor the hundredth that this has happened to.

When it’s time to pivot, lay out what you’ve learned (both scientifically and commercially) and the vision for what’s next. No investor wants to throw good money after bad. But neither do they want to walk away from a project that still has potential. Finding new opportunities has costs also, so if you can make a case for the pivot, gather your data and tell a new story.

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According to their website, IQVIA holds over 60 petabytes (60 million gigabytes) of proprietary data used to provide insights and inform decisions across the healthcare industry. Think market dynamics around a disease, demographics and site selection for clinical trials or pricing for a new therapeutic.

How does one pull the insights out of that mountain of data? Chris Steel was brought on board to drive AI and machine learning into all their products, standardize on platforms and unify the message.

Our conversation went from things AI can do to how to manage AI projects across the enterprise. We talked about creating synthetic data to help diagnose rare diseases, wrangling multiple AI projects, and of course, the potential of ChatGPT.

As I reflect on our conversation, it strikes me that AI broadly is very much like a child. (Keep in mind that I am very much a noob in this world and know just enough to be dangerous.) When you first get one, you have high hopes for its potential. You also have a responsibility to train it well.

Diagnosing rare disease

Children learn a lot about people by observation. Similarly, a deep learning model can figure out on its own what relationships exist in a collection of data.

Rare diseases are often difficult to diagnose (partly because they are rare). How can we identify patients with a rare disease whose diagnosis is currently uncertain?

Training a model on a limited number of positive diagnoses is problematic. AI can be used to generate a set of synthetic data based on known positive cases. That data along with normal data is used to train a model that can then be tested. Finally, the model is used to identify patients with the disease that have been undiagnosed up to this point.

That is pretty remarkable.

Sorry to interrupt here, but you are subscribed aren’t you?

ChatGPT

If you’ve been paying attention, you know that ChatGPT has also delivered some pretty remarkable results and its performance on professional medical and legal exams is stunning. At the same time, it can be a confident liar. In my own experience, I have seen it deliver scientific references that would be completely convincing if I didn’t bother to look them up and find out that they don’t actually exist.

Chris agreed ChatGPT has a lot of potential. He also offered some important caveats. It can record your questions and whatever else you feed it - like your data. Don’t do that. Remember: if it’s free, you are the product. It could share that info with someone you wouldn’t want to have it. Again just like a child!

Beyond testing the free version, get your own instance, be aware of the cost and have a business case because that computing power is not cheap. Chris kindly explained the difference in computing power between Google looking up the information it has indexed and ChatGPT delivering complex answers almost instantly on the fly, (and not paid for by advertising (yet?)

How many projects?

Avoiding duplication of effort across teams in a company as large as IQVIA is a challenge. Chris needed to know who was doing what with AI when he came on board. He asked people to share their projects but didn’t get a lot of response. So he took what he got, put it in a spreadsheet…

And then in the virtual team that I've mentioned where we have all these leaders… I plopped up the spreadsheet and I said, “Here’s what people are doing.

And look, you know this team is doing this and this team is doing that. You know, these guys are the leaders.” And suddenly right after that, as you can imagine, everybody starts dumping all of their projects on me. A lot of them we had to sort of weed out because they actually weren't really AI/ML related, but yeah, turn it into competition and then they are willing to share.

There is your management tip for the day. When you want people to share projects across teams, make it a competition.

This all has me thinking about what the data ecosystem of the future will look like. Where is the dividing line between companies that collect and analyze data for themselves and large repositories that sell the insights to multiple customers? Let me know what you think in the comments.

Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand.

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David Enloe is an organizational culture architect. I found him on LinkedIn and had to find out what that was besides damn good personal branding. I’m always interested in company culture, its value, and how it’s established and sustained.

He was hired as the CEO of Societal CDMO in the midst of the pandemic, coming on board without even an onsite visit, to work with people he had never met. His only contact up to that point was the board, none of the executives.

I asked him about how he drives culture through the organization, and about how to merge cultures when bringing two companies together through an acquisition. His answers got me thinking about what culture really means.

If you had asked me before this interview, I would have said that culture is “the way we do things or how we interact with each other.” These things are still true. As David points out in our conversation, it starts with why we do what we do. In this case serving customers and ultimately patients. But what I learned from talking to him is that culture reaches us on a deeper level. Culture is about trust. Whether in a company, a community or a country, it’s the comfort and the freedom that comes from knowing what to expect from the people around you.

I love doing these podcasts for you. (This is episode 181). How about showing some love in return? Please subscribe and share.

Thank you.

How do you measure the value of culture? Start with employee retention. Finding a job that fits your skills might be the easy part. Finding one where you are valued and feel like part of the team is a little more difficult.

Culture also affects productivity and scalability. As a company grows, you can’t scale people along with revenue. The way things are done might have to change. Although most people are resistant to change, David says people just need to know they’ll be supported.

We acquired this smaller company in San Diego, August of ‘21. It was a small, very entrepreneurial company.

Everybody had their finger in every pie at all times…

But when somebody's doing everything there, there can be a sense of loss as they start to let go. And so at the bottom of all of this is the T word, isn't it? Trust. You know, they've gotta trust that, that the other people are not gonna let 'em down. And again, that's something we have to bake into our cultural values.

And so if you’ve ever wondered why “culture eats strategy for breakfast”, you might have a better idea after listening to this episode.

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Early in our education about science, we learn that to understand what is happening in a system, we can only change one variable at a time. That seems reasonable. By doing that, we can see which variables matter.

It turns out that this is not only slow, but in biology, possibly incomplete. If there is a two-factor interaction (not uncommon) you will miss it. The good news is that it’s possible to analyze many variables at the same time and understand which ones matter. One can also see the interdependence of multiple factors.

Markus Gershater and Claes Gustafson joined me to talk about Design of Experiments and how it can be used to understand and optimize processes with multiple variables.

…particularly with biological systems, often the best setting for a particular factor will depend on the level of another factor, right?

This is called the two-factor interaction. And when you are only investigating one, each factor in the isolation of all of the others, you'll never see those. … a fundamental feature of biology is this kind of interaction and you'll just never see that doing one factor at a time. - Markus Gershater

As I think about it based on my own experience, a long time ago in a galaxy far away, a lot of academic science was focused on understanding one narrow slice of biology. (Is this gene important for pathogenesis?) Scale and automation had not yet entered the picture. I’m not sure I even imagined it.

But in this galaxy now, there are all kinds of biology being done at scale. Science can be done faster, but scale can also be more expensive. It makes sense to optimize processes, not only to produce a better product but also to reduce the cost. Design of Experiments can do both. You can use it to make a better antibody, enhance the yield of an enzyme and/or reduce the cost of the media used in either of those.

The magic of DoE is how we can get the most information from the least data.

Sorry to interrupt here, but you are subscribed aren’t you?

Interestingly, we don’t need to test every value of every variable. If you have two values for six variables, 26 is 64 but you don’t need to test 64 combinations. Sixteen may be enough to see what’s important (because math) and then you iterate to hone in on a solution from there.

In some (many?) cases, you don’t need the best solution, you need one good enough to commercialize, e.g. an antibody with a ridiculously low Kd .

…if you just take the simple example of an antibody, you wanna make sure it's, it, it certainly binds to your target at the Kd that makes it relevant. And you wanted to make sure that it can be produced at a titer that is high enough in your CHO system and you wanna make sure it has a melting temperature that is above a certain degree and you wanna make sure it doesn't aggregate at a concentration of x… I mean, who cares if it binds? What you truly care about is, does it shrink the tumor? - Claes Gustafson

While much of this may be new to biologists (who don’t like math), this is chemical engineering 101. It can be used to optimize microwave popcorn or your route to work. (Listen to the interview). My marketing friends could use it to optimize variables in an email or on a landing page.

Believe it or not, this concept is close to 90 years old. Now would be a good time for more biologists (and popcorn lovers) to take advantage of it.

It’s also an awesome time to share this podcast with your colleagues. Thanks.

Markus Gersahter is the CSO and Co-Founder of Synthace.

Claes Gustafson is CCO and Co-Founder of ATUM.

Conversations are fun and your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand.

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“Give a man a fish and he eats for a day. Sell him the hook, line and rod and get a higher valuation.” - Unknown ;-)

KromaTiD™ is in the business of helping researchers working on cell and gene therapies make sure, for example, that their CRISPR edits are going to the right places and not causing unwanted structural variations. Those cells ultimately go back into patients and safety is a top concern. KromaTiD had been a service business. Customers sent their cells for analysis and KromaTiD sent back a report.

They have transitioned to a product (and service) business, selling kits to allow scientists to do more of their own analyses. I was curious about what this change would look like and what it means for the business in terms of not only processes but also valuation and future opportunities.

Nathan Wood is the CEO of KromaTiD and he was kind enough to share their story with me.

The valuation part is the easiest to understand. A service business is labor intensive, making it difficult to scale efficiently, although easier to get started. The customers in this case are often in a facility with access to the specialized microscopes that are the key piece of equipment for these analyses. Given the right reagents and good instructions, much of this can be done self-serve at a significantly lower cost.

That also means that researchers can afford to screen many more candidates much earlier in their work, which likely means finding better results faster (additional savings).

When assessing value:

…if you think about an exit for an organization like KromaTiD or others, it's much easier for a large strategic company in the marketplace to purchase a company that has grown to over 10 million or higher and has a mixture of services and products because the products can become just a product line for them, if you will, and they don't have to go build that out, and then they can decide how they want to grow the service business.

Lowering the cost of the analysis also opens up the market for academic scientists who likely can’t pay for the more expensive service option.

That all sounds great, but making the switch isn’t easy. You might think, “Hey, pack up the reagents with the protocol and send them out.” To which Nathan might reply, “Send them in what? By whom? And how?” Up to this point, the deliverable was a PDF.

There were no boxes, no containers, no labels. And believe it or not, getting those things right is important. This is the nitty-gritty of a small biotech beyond the sexy science. You need processes for taking orders, filling them, packaging and shipping. Quality systems… The list goes on. That means new employees. And lots of change for the existing staff.

The marketing message and the audience changes as well.

Once it gets going though, things get smoother, including revenue. As a service business, the revenue can be lumpy. A customer may order a report and be silent for a while. With easy-to-use products, they just reorder. Service takes time and is billed on completion. Product is billed on its way out the door. Revenue becomes more predictable which makes it easier to think about where to invest the money that is coming in.

In the end, there is the opportunity to leverage your service business as your R&D. What else can they do for customers that might eventually become a new product line?

If you went to business school, this might be marketing and finance 101 for you. For me, I just enjoy following and sharing the stories of people solving problems. It never gets old.

Nathan on LinkedIn

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Because most of us have likely had a Covid test done in the last few years, you might think that getting diagnostics to market is a straightforward proposition. But you’d be wrong. The reason is that even if you have a clinically proven test, there are no guarantees that someone will pay for that test. Further, there is no standard by which diagnostics are evaluated that leads to reimbursement.

Hannah Mamuszka is the CEO at Alva10. She explained to me the market dynamics around developing new diagnostic tests and how she and her team are working to make it easier to get new ones developed.

When Covid tests were first approved, the reimbursement was less than the cost of making them, accounting for some of the delay in accessing them.

Just because a test is approved by FDA or CLIA, doesn’t mean it will be paid for.

In order to get payment, you have to go through the American Medical Association to get a code, which is essentially an alphanumeric set of numbers and letters that identify your test, and then you have to go and apply for what's called coverage which is determining who's gonna pay for your test. And there is no standard of how much evidence, what kind of data you have to present with your test in order to get it covered. It's just submitted and it's kind of a crapshoot which ultimately means that it usually takes on average diagnostic tests about seven years before they're paid for.

And most companies can't survive for seven years without getting paid. As most companies can't survive. I mean, it's not limited to healthcare. You know, if you don't get paid for seven years, you probably don't exist anymore.

Every modern drug is rationally designed. We know the pathways and the intended targets. But without diagnostics, for example, to determine whether a treatment can work, a lot of time and money is wasted.

The overall success rate for approved drugs is about 36%. That means not only do we waste money on prescribed therapies that don’t always work, but in the meantime, patients may also be declining, adding costs.

I am no expert on the US healthcare system. Far from it. But while many are trying to innovate, for now, we play the hand we’re dealt. I wanted to know how would diagnostics improve overall care and what is the path to making that happen?

Pharma companies want to claim as big a market as possible to make money for shareholders. Segmenting the population based on a diagnostic that can predict success is a tradeoff between market size and efficacy. You can see that the incentives are misaligned.

The leverage would seem to be with payors. They don’t want to waste money. If they had economics and science in front of them, they could drive coverage toward more effective treatments, couldn’t they?

It takes time and effort to bring these insights to you. Would you be willing to bring a subscription to me?

Hannah’s experience here is informative as well as an interesting study in psychology.

We take all of those clinical changes and we, we translate them all into numbers and then figure out how the payors are gonna see it, how much they're gonna value it, and then we show it to them strictly from an economic perspective first.

And when we show them the economic perspective, the first thing they ask for is, “Oh, well, you know, we need to see the clinical evidence”, which we immediately give to them. But I can tell you from a lot of experience trying to go the other way and showing them clinical evidence and then wanting to talk about economics, I mean, I essentially got nowhere.

So the best approach to aligning incentives seems to be economics first, science second.

I asked Hannah if there were healthcare systems in other countries that we could learn from. The US FDA approves drugs based on safety even if they might only benefit a few patients. Here again, the incentives are misaligned. Other countries would like to identify those few patients before approving the drug for use. But a diagnostic to find those few might exclude a large number of patients, making the economics of that drug unfavorable on the whole.

Economics has been called the dismal science. But understanding and aligning incentives for all the parties in our healthcare system may be more challenging than the science of bringing new diagnostics to market.

Conversations are fun and your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand.

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Just as scientists are curious about the “how” of the world, Lee Jay Lowenstein was curious about the “why”. That led to his becoming an ordained Orthodox rabbi. He was also a high school teacher and principal before spending some time in a non-profit as a fundraiser. At that point, he must have had some sales skills, but wanted something more.

With no real background in life science other than studying as a pre-med for a short while, he joined a partner and decided to sell laboratory supplies.

I was curious about how that happened. Why life science? And how do you sell supplies to people when you have little idea of what they are doing?

To answer the why part, what stands out to me from our conversation is the respect and admiration he has for the scientists doing research, hoping to benefit humanity. As to how he does it, relationships and curiosity. He never stopped asking questions about how and why a researcher does their work the way they do and how he could help make it easier for them.

I’m more of a marketer than a salesperson (I find sales difficult) but that seems like a pretty good lesson either way. Ask questions. Make the customer’s life easier.

I had been working for another company and just feeling. I can do better. I can do better than this. These people deserve better. They deserve to be treated like royalty, and the opportunity presented itself to join hands with a partner and jump in with both feet, and I did.

As I reflect on what it takes to be successful, it seems that there is an advantage to being somewhat ignorant, yet bold. (I have no doubt that discipline and hustle are important as well.) Some call it the curse of knowledge. When we think we know what someone needs (even if we’re right) we miss the opportunity to discover what else they might need that we could help them with.

Lee is never afraid to ask a question and ask again if he needs to. In my experience, when you ask a scientist a question about how or why they do something a particular way, they can’t not answer. Their purpose in life (and how they are paid) is to share what they’ve learned.

…people in the lab are extremely generous with their time and understanding. I learned so much about the business, just sitting and talking to people. Tell me what you do. You know, tell me, why do you do it this way? Why don't you do it that way? And people were more than happy.

I don't think their PIs were happy that they were wasting their time talking to me, but they, you know, they're very generous and they want to wanna share their science.

Today there's fewer and fewer things that people can say that I don't know something about. But honesty and being willing to say, “I don't know”… I've never had a lab manager say, “Well, you're an idiot. Get outta my lab.”

I’ve said it before. Curiosity is a superpower. Combine that with helpfulness and see where it takes you.

Lee Jay on LinkedIn

Stellar Scientific

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Imagine a capsule whizzing by some 200 miles overhead. It’s just big enough to hold a medium size dog (curled up and sleeping) but there is no life onboard. Instead, there is an automated laboratory designed for manufacturing pharmaceuticals. That is the vision of Varda Space Industries.

Do they really envision a future where drugs are manufactured in space at scale? Yes. I talked to Mark Herbert, VP of Biopharma Business Development at Varda, about their plans. My two big questions were 1. What is special about microgravity for this application? and 2. Why does pharmaceutical manufacturing makes sense economically?

Lifting payloads into space isn’t cheap, although the price/kilogram is coming down. On a per-gram basis, pharmaceuticals are one of the more valuable things you could make, so at some point, that can become profitable. And the reason microgravity matters is that in the vacuum of space there is no convection. That affects how crystals are formed. Experiments on the international space station with Merck’s cancer immunotherapy, pembrolizumab (Keytruda), show a more uniform particle size distribution and reduced viscosity. That has implications for how it can be delivered to patients.

Pardon the interruption. You are subscribed aren’t you?

The science is pretty cool. But when I reflect on a project like this, I wonder how a project like this comes together? Sixty-five years of space exploration is part of the foundation, of course. That inspires the next generation in terms of rockets, working in microgravity etc.

What stands out is the vision it takes to make it a reality. First, there is the imagination of the end state. What do we want to achieve? What brings that to fruition is the ability to imagine and execute all the steps in between. It’s a special skill to be able to put all of that together, convince others that it’s worth doing and meet the rigid timelines of a launch schedule. Because they’re not delaying the launch just because you forgot to pack a key item for the trip.

Epic projects like this one and the de-extinction of the wooly mammoth we talked about last week are not only inspiring, they are both essential and inevitable. At some point, we can’t not try. And when that happens, human beings find themselves capable of achieving what was once thought to be impossible.

Gordon Cooper knows what that feels like:

The interviews with my guests are the highlight of my week. Listeners seem to enjoy them too.

Conversations are fun and your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand.

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My first reaction when I heard that George Church wanted to bring back the wooly mammoth was, “Uh, why don’t we stop trashing the environment and save the species we have left?” Later on, I learned that I may have missed the point. It turns out that as engineers of the environment, wooly mammoths might enhance the carbon storage capacity of the tundra and help us all chill out a bit (slow climate change). That covers part of the why question but not all of it. This is a BIG science project so there is a lot more to it.

I talked to Alexander Titus (he goes by Titus) from Colossal Biosciences to learn what it will take to de-extinct the mammoth, what we’ll learn along the way, how you fund a project like this when the final product is not for sale.

You’ll have to listen to the pod to get all the details but here is the TL:DR.

Mammoths from elephants

The Asian elephant is the closest living relative of the mammoth. There is some ancient mammoth DNA available but it’s incomplete. It’s not a matter of injecting it into an elephant egg and hoping you get some hybrid. This is a massive genome engineering project that starts with figuring out which genes contribute, for example, to the wooliness and cold tolerance of the mammoth and engineering those into an elephant to produce a mammoth.

How does that happen? So many technical challenges! Can CRISPR technology be used to make multiple (hundreds?) genome changes in one cell? Then there is the challenge of somatic nuclear transfer, etc. etc. Probably a couple more things….

And if you successfully get a mammoth after all of that, what kind of environment will they need to thrive and expand the population, enough to be eventually reintroduced into the arctic? After that, it’s a question for science and society of accepting and protecting them.

Not subscribed yet? Really? Let’s fix that. Next week we’re talking about manufacturing drugs in space. After that, who knows?

Bioinformatics, AI and the business model

Figuring out which genetic variations matter and aren’t just neutral changes along with understanding the elephant genome including regulatory sequences no doubt, is an enormous bioinformatics project.

That brings me to the business model.

Titus says that analogies to the space program may be overused, but in this case, it seems appropriate. There are many technologies and capabilities to be developed along the way that could be commercialized to support the core mission. One example: Colossal recently spun out a company, Form Bio, based on their bioinformatics technology that will help the cell and gene therapy industry.

We chatted briefly about an AI component of this project. How do you identify all the elements of the target environment? One way is by listening and identifying specific sounds. That’s tedious and time-consuming for a human being but…

My team in particular developed an interesting way to use machine learning, unsupervised, and actually read through and listen through audio. And instead of having a manual annotator, someone who goes through and listens to something and puts a little mark in their digital notebook, we can actually have an algorithm go through and say, there is a point of interest.

Then a human can go directly to the annotations and try to identify the source of those sounds in the environment.

Given all the tech needed to make these projects happen and the biology learned as a result, more spinoffs seem likely.

But wait! There’s more.

The mammoth isn’t the only animal on the bring-back list. Scientists at Colossal are also working on the dodo (not long extinct) and the Tasmanian tiger, which I learned is not actually a cat. The thylacine, although it has stripes that make it somewhat resemble a tiger, looks more like a dog and is actually a carnivorous marsupial, as is (fun fact) the Tasmanian devil. The last one in captivity died in 1936. Each of these is significant for restoring their native ecosystems.

As you can tell, while there are lots of questions to be answered yet, I’ve become a fan of this project for its sheer boldness and the joy of discovery. We’ll cover another bold project in the next episode: manufacturing drugs in space. More why and how questions. Make sure you subscribe and share.

And let me know what you think about all of this in the comments.

The interviews with my guests are the highlight of my week. Listeners seem to enjoy them too.

Conversations are fun and your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand.

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Growing primary cells in 2D on plastic surfaces is not a good representation of the 3D environment of the body, regardless of your purpose. Cells grown in a dish eventually run out of room. They need to be disrupted and seeded onto new plates at a lower density. Then they run out of time. They just get tired and stop dividing. TBH, some days, I feel the same way.

If these challenges can be overcome, we can, in addition to growing larger quantities of cells for investigation or production, learn a lot more biology. I talked to A.J. Mellott, CEO and co-founder of Ronawk, about the technology they have developed that uses hydrogels to allow cells to grow in 3D microenvironments and interact with each other more like they would in the body. The hydrogel blocks - they call them bioblocks - contain microchannels that provide a large surface area, but they also fit together like LEGOs allowing the expansion of a culture by simply adding more blocks to the matrix.

It's really fascinating because now we're starting to see things that happen inside our hydrogels that we can point to the body and look and say, “Oh, this is similar. I see this happening in the body, and we can get more information out of, uh, what's going on.

And we can even start looking at the signaling between the cells and how they talk to each other. So from a scientific perspective, it's really fun. But then also from a business perspective, we now have this really easy-to-use technology that can help others scale, help others try new experiments and test new medicines that weren't easy to test before this.

As much as I enjoyed hearing about the scaling up of cell populations (and scaling down the labor involved), for me the chance to study some biology was equally exciting. One can embed the material with growing cells in paraffin and section it with a microtome to investigate what’s going as cells are migrating and laying down extracellular matrix. What will we learn about cell communication and extracellular matrix production? What are cells putting into exosomes and why? Can we engineer useful therapies from those processes?

Now add a level of complexity. Imagine the possibilities for studying the interactions between different cell types such as joining two blocks, one with tumor cells and another with immune cells to see what happens. For some reason, I can’t get the image of gladiators doing battle in a massive arena out of my head. That’s a ticket I’ll get in line for.

I really enjoy these interviews with my guests. The deepest insights are the best branding. I’d love to help you with that. Chat with me about custom content for your life science brand.

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When will we get to a place of reliable protein biomarkers as predictors or indicators of disease? Ole Vorm is a founder and director at Evosep, producing separation products between the patient sample and a mass spectrometer.

What is the state of those analyses and what are the obstacles yet to be overcome?

The first obstacle in terms of the proteome itself is that in any sample - urine, blood etc.- there are a few abundant proteins that represent the bulk of the material. It’s likely that the proteins of interest (if we can find them) are a small portion of the total and any changes in quantity or relevant modifications may be subtle.

But of the currently FDA approved biomarkers typically analyzed by ELISA assays, about 50 can be detected by simple injection of a protein digest into a mass spec. That’s good but not a lot.

From a physician’s perspective in the clinic,

…they never start out, uh, from a blank sheet of paper. They have an idea what they're looking for and asking for quantitation of say, two or three biomarkers, I mean, proteins basically,would typically suffice to say, okay, we're in this direction, versus going in that direction. And that is very cheaply, automatically done with ELISAs running on a fully automated, robotic platform in the clinical biochemistry labs.

The current ability to detect 300 proteins out of the mix is way more than a physician could use right now, but probably does not go deep enough to uniquely detect a disease. In many sports, this is called no man’s land.

Nevertheless between improvements in detection, robustness and AI to help analyze the data, Ole sees the field moving dramatically over the next few years.

In terms of analysis, we may find that the changes we see in a patient’s proteome, may not directly identify targets for therapy. Rather they might reflect secondary effects of a disease. In this case, where treatments can be found, those biomarkers may serve to monitor progress during treatment as opposed to being used for diagnosis.

Beyond the need for improved robustness (a clinical analyzer needs to run hundreds of samples per day without human intervention), there aren’t enough mass spectrometers to analyze the possible volume of samples. Using proteomics on top of genomic or metabolic analysis seems to be a more likely strategy.

Ole closed with this idea:

I do think things are progressing and, and I think, you know, what is really, really needed in our field would be sort of like the first success story. I mean that, from my perspective, that's what we really need to somebody, some group coming out and saying, so now we have this, this protein pattern is the detection of this and this. Whatever the success story basically is, I think it is just important that we begin to see some success stories and that will fuel the fire and get, more things going.

I’m interested in your thoughts. Do you know of any success stories already? Where do you see proteomics taking off?

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Cole Yancey was unsatisfied being a bench scientist. So much so, he asked the freezer repair guy about how to get out of the lab. “Maybe I can do what you’re doing.” The freezer guy was not helpful. It reminds me of a scene from Top Gun.

1st Lesson in Networking

Cole started chatting up sales reps who came by the lab. One took him under his wing and soon Cole was having lots of conversations with his new network and eventually found himself as an application specialist at Hamilton Robotics. It’s the perfect role to transition from the bench to sales.

Eventually, he gets a job in sales “with his back against the wall” trying to generate some interest in what he’s doing. Looking on LinkedIn, he noticed there are a lot of salespeople teaching others about sales. He also saw a gap. No one was talking to scientists about robots and what they could do for them. What was a business necessity became a great creative outlet as well.

He started out by writing down all his ideas and all the questions people had about laboratory robots. Then he would spend some time every week to map out his plan for the next week or two. Those two activities make it easier to sustain the process. He was learning by jumping in and doing it - both in terms of sales and creating content to generate interest.

Like these podcasts? There are more life science stories coming every week.

Setting Internal Goals Pays Off

Because LinkedIn is global and his sales territory is not, some of the leads he generated were passed to his colleagues. That’s good for the company but can (understandably) be demoralizing when you are trying to hit a number. At that point, he shifted to more of a 50/50 company/personal approach. That turned out to be a good move. After a recent layoff, he had calls within hours from interested companies.

It's incredible, the power of networking and the power of having some sort of… and I really am like reluctant to use this, but like to have some sort of brand on LinkedIn, like personal brand. It's incredibly powerful. And just to kind of give you an idea, I was laid off in December and, you know, my current role…. Basically, they reached out like hours after I got laid off. I hadn't told anyone. Through the grapevine someone had reached out to them and let them know, and they reached out to me and said, “Hey, we'd love to, to chat and kind of, you know, this is what we're doing. Let's talk.” And that's where I am. Right. That's, that's it was, it was a quick layoff and it was, it was incredible to see like the outpouring of the community come out and support me. You know, people that you don't think are watching are watching, so they see… they never interact and then all of a sudden, they're in your DMs like saying, “Hey, love what you're doing on LinkedIn.”

Advice for Companies

Cole is a big believer in having a growth mindset. Clearly, he has one himself, but companies can too. How do you think bigger and work toward the future? You should want to get as many eyeballs on your company (not just your company page but the people that make up your company) as possible. Not only is it good for demand generation when people ask about your business, it’s great employer branding when potential recruits see smart, happy employees posting regularly.

Beyond that, it’s outsourcing some learning and development. Cole is learning by putting stuff out every day while serving customers at the same time.

Follow Cole on LinkedIn

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It turns out, you can do quite a lot.

Jud Schneider is the CTO of Nashville Biosciences. I reached out to him to talk about their collaboration with Amgen and Illumina to sequence 35,000 African-American genomes. How is that possible?

Nash Bio (owned by Vanderbilt University Medical Center) has about three and a half million de-identified health records. About 10% of those have consented DNA tied to those records. This is a treasure trove of data for pharma and AI companies to uncover patterns and develop new therapies.

The number of genomes in that project blew me away from the start. But among genome data sets, African Americans are underrepresented. This is an opportunity to make important discoveries for a significant part of the population as well as the population as a whole.

The genome data by itself isn’t enough. The real value is tying the genetic data to health records to find and understand patterns that associate genetic variation with disease or simply biology.

Our conversation evolved into the possibilities with such a massive data set for training AI, including imaging data, and how to get them most out of it. With the help of their clinical team, they can build very specific cohorts for training AI models. Jud says they can think of about a hundred ways to use the data, but customers can think of a thousand.

Let's just say we're looking at chest CTs. And you're looking for your, I'm just making something up, but we're developing a product that looks for lung nodules. right? Well, we've got lots of chest CTs that have diagnosed certain types of lung cancers, and you can actually get very specific on the type of lung cancer.

And we've also got lots of, you know, just kind of blank chest CTs, you know, and ones with artifacts that are important, like there's a pacemaker in there. There's other types of medical devices that may be implanted or, you know, there's some different anatomies that you need to take into account.

We just got quite a diversity of information that you can really end up with an extremely powerful and well-trained model you know is really starting from a place of grounded in the actual diagnosis and not necessarily just CPT codes.

Pardon the interruption. You are subscribed aren’t you?

It’s not enough to have a lot of data. You need to understand the protocols under which it was generated and factors that might not be immediately apparent. It would be easy to hand over a bucket of data based on an ICD code and let the customer have at it. (I learned that ICD codes might be what I would describe as “squishy”. Sometimes an initial diagnosis might be uncertain or inaccurate. But some thoughtful analysis can make the data much more useful. That’s the role of the clinical team who are working with the data on a regular basis.

We find ourselves in a situation all the time where we're really able to disambiguate the, uh, the nuances of the ICD coding system and the billing data to really find the patients that actually have the diagnosis and actually have the data, you know, within routine clinical care that's necessary.

The big takeaway for me is that while we generate and capture ridiculous amounts of data every day (in healthcare and elsewhere) it’s still important to understand the limitations of how the data is gathered (ICD codes for example) and be thoughtful about what you are looking for to get the most value out of it.

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Fun fact: I first interviewed Jud on Flip Turns, my podcast about people whose lives were changed by swimming.

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David Nathan wrote a children’s book in the carpool line at his kids’ school. ChatGPT delivered the text and he used Midjourney to illustrate the main character.

Generative AI applications like ChatGPT and Midjourney are dominating conversations in the marketing world recently. The last episode of cc: Life Science covered possible uses and concerns around Chat GPT which generates text responses to user prompts. Midjourney is a tool that will generate images based on your prompt, having been trained on a gazillion JPEGs from who knows where.

David is an agency owner diving into Midjourney to explore it’s potential uses in marketing. We talked about where he sees value as well as some of the limitations.

As an agency working with designers and clients, presenting concepts and getting feedback can be expensive even before you get to the deliverables. And not everyone is gifted with the ability to express an idea through a rough sketch, let alone words. David sees a benefit in being able to present a basic idea of a trade show booth, for example, and get feedback from the client before giving the task of detailed design to a professional.

I'm always finding myself in a situation where I have ideas and then I have to try to translate those ideas into, like understandable language for design. to have them then create the ideas. So not only can I now create some things myself at a pretty high level… you would have to be really, really talented digital renderer to create some of these images. But I can also use that as a starting point to help me communicate my ideas to the artists now too, right?

One of my (many) concerns is that, while you can prompt for images in a certain style, everything I’ve seen has a similar vibe to it. I don’t know if that’s because I know it came from an AI or what. David says that each platform has a certain “lean” to it. Will we become numb to seeing a universe of media that all feels like it was generated by a machine has no soul?

What does this do to artists and creators? One consideration is whether they should be compensated for the use of their work in training the algorithm. The other is simply their continued employment. Having said that, photography didn’t eliminate the art of painting. One could argue that it opened up new possibilities for painters to explore different ideas as opposed to reproducing reality for royalty.

Finally, we talked about the children’s book he made in the carpool line. David noted that ChatGPT came up with a reasonably good effort based on his prompt. And Midjourney was able to present a character that satisfied the imaginations of the five kids in the back seat (a monster like something you might find in a Pixar movie.)

What was interesting to me is that you couldn’t illustrate the whole book this way. For example, “Now show the same monster doing X.” Although the AI creates a “monster” image based on its training from other monster images, it doesn’t really know what part of the image is a monster. I found this fascinating and, honestly, inspiring in another way. Human beings are still amazing.

My hope is that we can use AI thoughtfully while conscious of not losing our humanity.

What are your thoughts? Have you tried Midjourney or Chat GPT? Leave a comment below.

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ChatGPT has become the AI that is impossible to ignore. As I wrote in my first post a little more than a year ago, I would be neither a cheerleader nor a detractor, but rather a curious observer. So here we are.

My main concern with respect to many technologies is the dilution of our humanity. In response to all the posts I was seeing where people were asking ChatGPT to create content, I wrote on LinkedIn that the value of your voice, even better with your face attached to it, would increase. The more AI-generated content is available, the more you will stand out, not to mention the benefits of a human interaction.

Declan Dunn commented:

AI is part of the game, and while some will use it instead of writing, most are using it to get a starting point, to brainstorm ideas when they don't have folks.Agree with putting a voice or visual on it, especially short snippets - you have to earn attention today, and while AI can sort of mimic your voice, it can't replace the inflections, passion, and unique humanity your voice delivers...

Declan and I had not chatted in quite some time so he DM’d me to propose a conversation on this topic which I thought (correctly) would be fun. This episode is a freestyle exploration of our thoughts about the possibilities - good and bad - for ChatGPT.

As he mentioned above, brainstorming and outlining may be great uses of ChatGPT. A quick first look at current thinking around a topic can get the juices flowing. And if the answers aren’t satisfying, we will slowly learn to ask better questions, provide better prompts.

I also wondered about how future versions will be trained when so much of the information it is trained on was generated by a previous version. Will it know when it’s looking at something that was AI generated?

In this Wired article, Phil Libin, former CEO of Evernote was said to be enthusiastic about AI in general but shared my concerns:

“All of these models are about to st all over their own training data,” he says. “We’re about to be flooded with a tsunami of b****t.” -Phil Libin

Listening back to our conversation, Declan mentions some interesting uses for life science researchers in terms of improving both the inputs and the outputs (presentation) of their work. He also raised the question of does an AI understand the audience? As humans, we tailor our message for the audience. Are their hints of the audience in the questions we ask? Maybe, but not always.

There is no shortage of opinions on this new tool. I found this podcast from Scott Galloway enlightening:

Prof G and the AI Hype Cycle

And in the next episode of Life Science Marketing Radio, I’ll talk to David Nathan who used ChatGPT to write a children’s book in the carpool lane and generated an illustration through Midjourney a generative AI for images.

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Have you been considering creating a podcast for your company? You may be wondering about gear, recording and editing software, structuring interviews etc… Long-time listeners will recognize my buddy David Shifrin. He and I started podcasting at about the same time and have shared our discoveries and methods with each other as they evolve over time. He currently works as the Senior Manager for Content Marketing at Jarrard Phillips Cate & Hancock (opinions expressed are his own) where he produces the High Stakes podcast.

In this episode, David and I will share all we have learned with you to simplify the process of publishing a great sounding podcast. We’ll cover:

• Microphones

• Recording tools (Riverside.fm)

• Editing software (Descript.com)

• How we structure interviews

• Best places to record

• Hosting platforms

and the one secret button that will level up your sound significantly even when the neighbor is using his leaf blower. (You’ll hear the difference!)

If you still have questions contact me using the link below.

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Mark Fortner, Founder and CEO of Aspen Biosciences joined to explain the concept of FAIR data. The idea around FAIR data is to ensure that data is available and labeled consistently to allow people AND machines to correctly interpret, for example, what the label on a column of data means. The benefit for all is to enable more effective data sharing in collaborations or over time from one study to another.

Mark provided the following summary for me.

We can take the FAIR acronym as a laundry list of specific problems:

Findable

• Data has to have a unique, persistent address. Often data in an academic environment has a brief shelf life before disappearing into a bitbucket, never to be found again.

• It has to be well described.

• It has to be registered and indexed so that people (or machines) can search through it.

Accessible

• Data & Metadata has to be retrievable by that unique address using open standards and protocols.

• Metadata has to be accessible even when the data are not. Even if the data has disappeared you should be able to find the people, institutions or publications where the data were presented.

Interoperable

• Data & metadata need to be represented in a standard broadly acceptable language.

• It has to use a common vocabulary.

• It may include references to other data sets, and those references need to be as specific as possible. Instead of gene X is associated with disease Y, the reference should indicate that a specific mutation in gene X is responsible for disease Y.

Reusable

In order for data & metadata to be reusable, we have to understand the provenance of it. Who generated it? how was it done? What instruments and materials were used? What was the protocol that was followed to generate the data?

You want to give the people who follow the trail you blazed enough information to allow them to reproduce those results.

You want them to know whether they can combine the data they've generated with the data you've generated. Are those data sets comparable? Or were there too many differences in the protocol to make that possible?

Example

Imagine a large pharma company investing in a project at a small biotech that is developing a novel therapy. Being novel, there is no expertise in this area at PharmaCo.

Biotech is going to hand over a package of assay data for evaluation. If it’s not clear how the data was created and what it means, it will take time and effort (money) to sort out. Having FAIR data helps smooth out the process.

The alternative is that PharmaCo risks a lot of money or Biotech spends a lot of time educating their pharma partners on methods etc. Both companies benefit from this process but the burden is on the smaller company producing the data.

Spreading and embedding

Ideally, where possible, tools like mass spec or other analytical equipment would output FAIR data by default.

What is surprising to me is that academic research is where the idea of FAIR data is taking hold because of its collaborative nature. Mark mentioned to me after the call that it’s not just for corporations and goes beyond biology and chemistry. Archeologists are adopting this and some European funding agencies are requiring it. This makes total sense to me. The agencies are paying people to produce data of all kinds. They want it to be persistent and accessible for studies later on.

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Buy both of these Limited Availability recordings for a penny!

and I’ll send you two more interviews with outstanding life science marketers every month! If you aren’t happy with what I send, well it’s actually free ;-)

This double box set includes 2 individual winners from the 2022 SAMPS Awards, presented at Neuroscience in December.

Olivier (Ollie) Welaratne is the General Manager at Red Box Direct. He is the recipient of the 2022 Young Person of the Year Award from SAMPS.

Red Box Direct is outsourced sales, operations and support. in the European market. At 27, Ollie is the GM with 5 sales people across four units. He hires trains and manages those people in addition to doing business planning. The ultimate goal is that the people he hires and trains become self-sufficient.

I found Ollie’s path to his current position as well as the business model of Red Box Direct interesting. Whether you are a young scientist or marketer figuring out your career path or more experienced and thinking about different business models, you don’t want to miss this.

It’s my privilege to do these interviews. If you enjoy them, please subscribe and share.

Thanks!

Aishwarya (Aish) Vishwanathan is a Product Manager at Stoelting and the winner of Support Person of the Year from SAMPS.

Stoelting sells neuroscience research equipment and software in the pre-clinical space. Aish is responsible for stereotaxic products and ANY-maze software in addition to being the support person for Europe.

Being a product manager is a great way to get started and prepare for other roles because she gets to really understand customer needs, translate those for product R&D and keep that cycle going.

Although she trained as a microbiologist, the multidisciplinary nature of science these days allows her to be comfortable managing products in a very different area f life science.

Life Science Marketing Radio is proud to sponsor SAMPS and the Young Person of the Year Award.

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I talked to Jason Scharf about new business models and digital health to get a glimpse of where the world of life science and healthcare are going. Jason is the host of the Austin Next Podcast. He has been an operator at companies like Illumina and Keen Health. Below is a taste of the topics we discussed.

It seems timely to start with a discussion about business models for anti-infectives - therapies for illnesses that aren’t typically chronic conditions. There is a gap in the market because regardless of how many people use a drug and for how long, the cost of development is high.

What about a subscription model based on creation vs usage? This would provide an incentive to develop and produce a drug regardless of usage so it’s available when needed. There is a free rider problem here. What happens in health systems that didn’t pay for the subscription? Do they pay a late fee? Or is this therapy unavailable to members?

We are witnessing the consumerization of health. This would seem to make access for some situations more convenient whether online or at a small space at the local mall. But how to integrate all my health records? Ideally at some point, one person is tracking my overall situation.

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I’m also very curious about digital health from a preventative point of view. How is that paid for and where are the incentives? We live in a culture where we only pay for things when they're to be fixed after they're broken. I’m all for developing new drugs, but it feels a bit like a dog chasing its tail. How can we prevent obesity, diabetes etc?

One challenge is the immediacy of feedback. Jason described a 2x2 matrix of complexity vs feedback proposed by Clayton Christensen in The Innovator’s Prescription. There are apps that will help you fall asleep. The feedback is immediate. Falling asleep is fast. (Do you fall asleep more easily?) Weight loss is slow. It takes months of consistent effort in the face of a gazillion distractions. This is the key to everything right? Complexity of the solution vs feedback. How do you get behavior change over the long term? The opportunity for reducing obesity is to make feedback more immediate or decrease the complexity of care (which takes us back to a pill).

Jason is excited about the possibilites forAustin. He says they need to find their unique sauce. This is interesting for a region to be competitive and different from Silicon Valley, Boston, RTP etc. Not just having capabilities, but a unique mix that draws the right people. Tech convergence is one possibility he sees. There is a lot of tech infrastructure in Texas. There are opportunities like AI for drug development, e-commerce and lab testing. What would it take for a Mom and Pop doctor’s office to offer remote visits? What about AI driven clinical decision support software?

We covered a lot of ground and this episode is sure to prompt some ideas for whatever you are working on.

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Developing a new product for launch involves a lot of effort and expense. To maximize your return, it’s important to know 1.) the size of the market for your offering to determine your potential return and 2.) how to prioritize your target customers for a successful launch to build momentum. From your addressable market, how do you find the early adopters?

I had a fun conversation with Mehdi Farzanehpour, CEO of Scitodate, about this topic, which he refers to as central market intelligence.

Typically one would do a lot of research to determine the size of your market. Reports are available, but they are rarely an exact fit. If your product is truly new, how could they be? So there is a bit of estimation and interpretation involved.

Lucky for you, the the interwebs contain all kinds of information available about who is doing what, how much money they have, when they will get more, who do they collaborate with and how long they have been using their current products.

If you are dealing with millions, like if you're selling shoes or Nike shoes, 2% is a very good conversion. But now the question is how can I get start getting 35% conversion? That I can just talk to the right people? I know what they're doing. So now the question is, who can I talk to? What their problems are? What is their need? How can I address that need?

That data can be helpful not only in evaluating the size of the market, but also in discovering the likely early adopters. Which researchers are working at the edge capability of their current technology? Those are your first customers.

We covered a lot of ground in this episode from maximizing lead generation to optimizing for conversion and how to help a sales team be relevant and helpful to their prospects.

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Mehdi on LinkedIn

Scitodate

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I’ve been thinking a bit lately about preventative health. We focus a lot in this podcast on therapeutics, some of which I’m personally grateful for. We should keep developing new ones to help people live longer and healthier. But that seems a never-ending game. I don’t see curing all diseases as realistic, nor the only strategy when many diseases can be avoided by changes in behavior.

Paying for prevention seems a tricky business. How do you pay for something that doesn’t happen? And who would pay it? I’m not paying to fix my roof until the old one leaks (every November). Insurance companies can give discounts for safe driving or not smoking, but other examples are more difficult. Will someone watch what I eat? Will a discount next year stop me from driving to 7-11 when the urge for a box of Oreos hits?

In the context of digital, there are wearables that can send data by the truckload to our physicians. But those are essentially diagnostics that are looking backward on an already-defined problem. (If you have examples that show otherwise, please share them in the comments. I’m here to learn.)

In this episode, I talked to Ramin Rafiei, Founder and CEO of Unleash where he is advocating prevention as a service, “augmenting science, digital biomarkers, advanced behavioral economic theory and cutting-edge AI with brands in order to scale preventive health.”

I recommend the full episode for the details but here is a brief summary:

It has been known for a while that your zip code is your health code. Where you live is a good predictor of your health. Beyond that, now your digital footprint is your health code. Your smartphone is a directory of your behavior but also a tool that can be used to influence your behavior toward better health.

Digital health so far has been designed around existing healthcare infrastructure that is not focused on the consumer. Healthier people are better off financially and have more purchasing power. And the brands you love have more influence than your doctor.

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The model Ramin and Unleash are proposing is not transactional (discounts etc.) He proposes a shift to the aspirational. How do we make a pair of Nikes more effective in helping with weight loss, blood pressure etc with accompanying behavior change? The shift is to inspire better day-to-day decisions that are better for your health. The approach isn’t limited to consumer brands. The same approach can work in conjunction with therapeutics as well.

Ramin on LinkedIn

Unleash

Prevention as a Service

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Everyone wants to be patient-centric these days. Betsy Bennett is a health psychologist and behavior change strategist. And, as you’ll discover in this episode, she has been a patient with a serious disease- twice. She has some thoughts about how companies can be helpful to patients over the course of their illness.

There are so many good nuggets in this conversation, I’ll summarize a few of them here, but you should really listen to the whole thing. It’s very powerful to hear from someone who has actual experience and is trained to help people in similar situations.

Missing pieces

A symptom tracker can be useful. What’s missing is helping patients know how to give useful information to their physicians.

…there are ways that you can distill that data and put it into sort of snackable chunks for your doctor so that you can get some of the answers that you're looking for. But what I don't see is anyone really teaching patients how to do that, or even more important. That might be something that I could do, but it might not be something that my elderly aunt could do.

So in that case, I need to teach her how to identify people in her environment who could do that for you, help you prepare for this appointment, and who do you need to have with you to provide these snackable chunks to your physician.

Gratitude - Read the Room

No one with cancer, while there are probably things to be grateful for, wants to be told to embrace gratitude. Not helpful.

Unbranded Content

Here is a real opportunity.

…in my experience, one of the most successful things that I've been involved in, and not just once, but multiple times, basically, unbranded campaigns where, if you really connect with a group of patients and really give them something that they're not getting anywhere else…if you can provide that kind of education and even support for patients, and then you follow up with eventually a link to, or some sort of connection to branded content, you at a minimum have their eyeballs.

She’s not talking here about healthy eating, fun recipes, and gentle exercise. Those can be found anywhere.

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The Emotional Journey

There is a huge emotional burden that comes with a diagnosis. The opportunity is to let patients know what they might expect around this.

There is something that causes many patients to say to themselves, “I don't even know who I am anymore. You know, I used to be so upbeat. I used to be, you know, this or that, and now I'm, I'm weepy, I'm grumpy.” And so even being able to teach patients about this…

All of that is on top of having even close relationships change because some people will be unprepared to deal with someone else’s illness.

Advice for Agencies

Hire older writers. The young folks may be clever, work all night and be less expensive but unless they’ve grown up with a sick parent or grandparent, they probably lack some perspective. Find people who understand what even a minor health challenge means for how one lives their life.

Listen to the full episode. I promise it will change the way you think about some things.

Connect with Betsy on Linkedin

and check out her YouTube channel.

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Designing new compounds to be used as therapeutics is a challenge regardless of the approach. Artificial intelligence shows promise for solving some of those challenges, whether it’s identifying a hit, lead optimization or something else.

Ashwini Ghogare is the intrapreneur CEO of Artificial Intelligence and Automation in Drug Discovery at Millipore Sigma. She was kind enough (and patient enough) to educate me on how AI can be used to help with figuring out the synthesis of new compounds and even predicting ADME or physical chemical properties.

When I look at complex molecules, I’m overwhelmed just imagining how they are synthesized, given that some groups may be cross-reactive etc. How do ensure that you get (mostly) what you intend to make? I learned a little bit about the possibilities in this conversation, for example, synthesizing component groups as opposed to a linear process from start to finish. (The only real synthesis I’ve ever done was a 13-base oligonucleotide -in a fume hood!- long before that were done by machine.)

In the early stages, you just want to see if a molecule can be made and will it do what you want. Someone else gets the job of figuring out how to make it efficiently at scale.

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Back to predicting ADME properties: Making drugs is expensive. Most will fail. But if we knew in advance a little more about the ADME properties we might expect, we might at least reduce the cost of development a bit.

The big challenge here is that, compared to finance or my YouTube habits, the amount of data available for training models is limited to none. The publicly available data is all from published studies. But to train a model well, it would be really valuable to have negative data in the training set.

Merch KGAa are leading the way for their peers in the industry to take advantage of sharing datasets for training without actually sharing or compromising the actual underlying data.

Data can be negative or drugs can fail for many reasons. Ashwini points out that one step in the right direction to address this is automation, removing at least some sources of error. When I asked her what the future of drug development looks like I was blown away by her answer. She envisions a world where compounds are not just synthesized by automation, but where those machines are autonomous! The machines analyze the data from the synthesized compounds and iterate independently from there.

I’m essentially going to school on this podcast. If you are learning also or know someone else who would benefit, please subscribe and share.

Ashwini on LinkedIn

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While launching a new product is exciting, especially in the sciences, it’s not the only way to grow a business. We can change our business models or how we go to market.

Dave Brock shared with me some of the things that he has seen in terms of companies thinking more broadly about how to do things.

There is typically a cycle that companies go through. First is, “How do we do more?” A volume and velocity strategy. Next is “How do we do better?” Eventually, you need to do something different. Then maybe the whole cycle starts over.

If you are not subscribed yet, now would be a good time. You’re welcome to hang out but do you really want to risk missing the next episode? I promise it will be good.

Where do the ideas for doing things differently come from? Dave’s recommendation is to not look at your competitors. First of all, they probably aren’t different enough and copying what they do doesn’t deliver an advantage.

He described an extreme sports company he worked with that was struggling with creativity and growth. At the same time, he was working with a semiconductor business win a similar situation. Imagine the scene when he brings them together for an innovation session: Powder blue shirts on one side of the table. Sleeveless vests and tattoos on the other.

Once they started sharing what they had been doing, each side saw ideas and opportunities that would be novel to their own industry.

Another way to be inspired without the intermediation of a consultant is to go to a trade show from a very different industry to see what they are doing. Talk to the people there about their business and see if you get some new ideas.

If you’ve been around this podcast for a while, you know I’m a big fan of bringing in marketing talent from outside. This is the same idea.

Dave Brock on LinkedIn

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Your company runs on information to a large degree. But not all of it is accessible to the people who need to make decisions which slows things down, making you less competitive.

Seth Earley is the CEO of Earley Information Science. We had a conversation about using artificial intelligence to make information flow faster within companies. The key concept was the use of ontologies in the information architecture.

You may be familiar with taxonomies, how we name categories of information. Ontologies takes that one step further to produce a web of relationships. That web helps you slice the information or data in many ways to help you navigate to answers or information you are looking for.

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In some ways it’s like a highway map. Or better yet the maps on your phone. You can ask, how do I get from San Francisco to San Jose? But you can also ask for restaurants in San Jose. “Oh, here’s an Indian restaurant that looks interesting. I wonder what other Indian attractions might be nearby.” And so on.

Seth describes examples of how ontologies help with speed to market and make it difficult for competitors to ever catch up.

Seth’s Website

The AI Powered Enterprise

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Can you really make serious progress with an intern? The answer is a definite yes and it can work out for the intern, the host company and a vendor.

Bob Lempke is the Chief Commercial Officer at Mobile Locker. He’s been on the podcast before. On a catch-up call, he told me this great story about working with an intern at one of their customers, Allergan Aesthetics, and AbbVie company.

Sunethra Kannan was the intern. Her assignment was to help set up the Mobile Locker user accounts as they were rolling out inside the company. Long story short every internship comes to an end, but in the meantime, she becomes an expert at this for Mobile Locker.

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When she goes back to school at the University of Illinois, Bob decides why shouldn’t they hire her part-time (fitting with her schedule) to continue the work and do more of the same for other customers.

This becomes the win-win-win for all parties involved. They both agree this is a model that work in a lot of places. Let me know in the comments if it can work for you.

Bob Lempke on LinkedIn

Mobile Locker

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Erica Sosnowski, the Managing Partner at Sosna + Co. recently posted on LinkedIn a list of things that life science executives struggle with the most in the context of finding and executing deals.

From her post:

• A limited network due to time spent in academia or in the “science” of their business- Lack of understanding (despite best efforts) on how to move your business beyond the small-to-medium stage- Uncertainty of what goes into business/IP valuation- Lack of awareness of where to find the ideal target company (for M&A, licensing, partnering)- Unsure how to negotiate and secure a lucrative deal

Maybe you struggle with similar challenges. So I asked her about all of those things in our interview.

Many founders may have a scientific network but not a business network where they can find people to help turn their science into a product. How do you find the right partners? You need to know where you are trying to go. Erica’s job is to help with the process.

…it also starts with strategy, right? It starts with, “What do you wanna be when you grow up? How do you wanna get this drug over the finish line? What is the amount of money that you need to get it there? Because we all know that developing a drug or a technology, it takes millions of dollars in multiple years.

Most interesting to me was the art of valuation. Understanding the market for your therapeutic area is key, of course. I hadn’t realized that markets can be very different geographically for cultural as well as other reasons.

And every market is different, right? I mean, the North American market is vastly different from the European market, which is different from the Japanese market. So, um, looking at the dynamics of each of the markets is, is also critical to understanding the IP position and the valuation…

How drugs are paid for. Culturally, right? Reimbursement systems are different in different areas. Therapeutically, you have different diseases that affect different countries. There's a lot of obesity in North America, not as much in some of the European or Asian countries.

This was a fun and informative interview. If you are looking to do a deal in the future, you’ll want to listen and subscribe.

Erica on LinkedIn

Sosna + Co.

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So you want to be a thought leader? I talked to Brian Morgan, President of Think Deeply, Write Clearly about effective thought leadership communication.

Thought leadership can be used to attract an audience who may need your product or service. Or you may want to influence decision-making in a particular direction. You can see the overlap with content marketing.

In our conversation, Brian brought out a few points that may be helpful.

Thought leadership is about building trust. People need to trust you before they do business with you or take your advice. Being an expert is the first requirement in most cases. But that may not be enough. You have to know your topic AND add something new to the conversation. Otherwise it’s not leadership, right?

A significant mistake Brian sees often is not sharing your assumptions. It’s important for readers (or listeners) to understand your point of reference. Transparency builds trust and credibility but also makes you vulnerable. (People will find out whether you know what you are doing or not.)

What if you are not an expert? Maybe you want to stimulate a discussion to learn more. Brian’s advice is to detail your observations. You might say, “so I've been thinking about… or I've been wondering about...” The job of the writer is to make his or her reference point useful to you. (Personal aside, I think I fall into this category. I don’t consider myself a marketing expert. I think I’m pretty good at storytelling and creating marketing content. But I’m very curious about marketing and the people who do it.)

People care not only about what you think (your conclusions) but how you came to them. Even when someone has a different point of view, you can build trust by “showing your work”, as your math teacher used to say. Brian refers to factors and weights. What are the factors you are considering in your argument and how do you weigh each in your decision-making process? Make these clear to your readers and you’ll be off to a good start.

I’m learning a lot more in his course and have a long way to go. DM Brian on LinkedIn for a free trial.

Brian on LinkedIn

Think Deeply, Write Clearly

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PharmExec.com published a study in 2020 of 25 first commercial launches. 48% of them missed their first year forecast for sales (<70% of forecast).

Almost a third of them outperformed (>130% of forecast). Outperformers started commercial planning more than 2 years ahead of approval and typically spent more on SG&A.

It has to be difficult for a CEO or CFO to devote resources to commercializing a therapy when approval is still uncertain and far away. I invited Maureen Franco and Mike Hodgson to talk about the activities that make these launches successful and who is brought on to make it happen.

Key takeaways:

• Understanding the market, customers and market access is important. If it’s misunderstood or unappreciated, even the best product will struggle to get traction.

• Positioning your drug, the disease and your company is key. Those things have to fit together. And when they do, it becomes easier to make decisions and attract the right employees to carry your vision through. Strong positioning is the beginning of establishing a culture.

• Your first commercial hire will do a lot of educating the founder and others on the value of commercial planning. It can be a lonely position.

As an example of shaping the market and positioning a disease, Mike shared the story of how Pfizer repositioned impotence into erectile dysfunction which made a huge impact on the success of Viagra.

In essence, Pfizer launched two products, right? They relaunched the disease with a totally new name and then they launched their drug…We think that's applicable to just about any condition in any therapy you're launching. You've really gotta… you don't necessarily have to rebrand the disease, but you should understand its perception and its relationship to your product.

PRE Commercial

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Paul Simms describes himself as a noisy introvert. Does that mean he’s a troublemaker? He’s definitely trying to stir things up in the pharma/ life science world as CEO of Impatient Health. You should take a look at his blog to get an idea of what he’s up to. I wanted to talk about some things I saw there and on LinkedIn.

The world for the last fifty (seventy?) years has been pretty predictable. That seems no longer to be the case. Being successful will mean being adaptable. One of the challenges he sees is that outside of R&D, there is little innovation. He described a curve (up and to the right) signifying advances in science and a shallower curve below it signifying the innovations that make it to the patient. Paul believes the gap is people who could have been treated but weren’t.

He also sees the possibility of innovations outside the lab that could improve the patient experience better than medicine alone. This requires a culture of experimentation that doesn’t exist outside the lab. Many ideas never leave the flip chart. Why don’t we build them and test them with simple approximations?

Paul admires the practice of building concept cars in the auto industry. They spend millions building ridiculous models that no one will or could ever drive. Yet they are valuable because the provoke a reaction. We learn what is attractive and what fails to spark joy. And he says they make the car industry a little bit cooler. He asks, “What would make health cooler?”

People might shout at me if I say that health should be cool and that maybe it shouldn't, but it should certainly be something we get more passionate about.

I often argue marketers are working in the most emotive industry of all. Yet, somehow managed to make the most bland advertising materials of all as well. …Elon Musk can get people excited about batteries for crying out loud. We should be able to get people excited about health. But we just don't think about it in an imaginative way.

So I would like to create a new relationship with not just HCPs, but patients as well by opening their eyes as to what is possible, what the future could look like and becoming better storytellers in our industry.

That question has had me thinking more than any other bit of conversation I’ve had on this podcast. First of all, is it the right question? Regardless, it has my brain going many places to imagine new business models that would help people stay healthy and be profitable.

What if we remove the constraints just for the purpose of imagination? No budgets. No compliance restrictions.

We do it when we dream. All of us do it every day. We dream. We wake up in the morning and we think, “What in the hell was that I just dreamt about? But you know, we do it.

And unfortunately, we discover in the morning that we cannot fly, but we've just spent the last few hours imagining a world where we could. And that's almost something we want to embrace as opposed to push away…

As it often does, it comes down to culture. Some companies celebrate boldness and give awards for trying something bold and failing. He suggests implementing some “innovation accounting” where learning is accounted for in the way we track dollars. And learning is distributed the same way as dollars. It goes back to the culture of experimentation, building prototypes that can be tested and iterated quickly.

Leadership also needs to recognize that there may be someone in the company that always has the crazy idea and may have been derided for it in the past. That person is worth paying attention to:

…because they're the ones that are willing to unlearn. To go down the hill to deoptimize. I spoke earlier about how we've optimized to a world that we thought we knew. But now we want to be over on another peak, another peak of a different mountain that we want to be on.

We can't just step from one mountain to another, in a single step. We have to go down that valley and unlearn and be willing to make a fool of ourselves sometimes in that process. So that is the attitude I would love to see us have. It's not necessarily one of being courageous ourselves. It's one of being tolerant.

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Kristin Apple is the President of LINUS. We talked about the future of healthcare specifically for seniors 60-79 and how they think about it based on a recent survey (Link below).

This is worth paying attention to because this age group is the fastest growing segment of the population. How they think about aging and what innovators can do to meet the needs of this group represents a big opportunity.

They did a quantitative survey of 1000 people and followed up with a qualitative conversation style study.

First of all this group doesn’t see itself as old.

We found out that, no matter what, how unhealthy they get, two in three want to stay in their home, even if they can no longer properly take care of themselves or have to be dependent on others.

The same percentage haven’t done anything to ensure that happens. So what would they give up in order to enable aging in place?

It's okay to be tracked… We thought, nobody's going to want to be tracked. They're definitely not going to want to have their gen-X daughter like myself, knowing when they're opening the refrigerator or whatever it might be. But the answer is. That's okay. So they're willing to give up some sort of privacy to be able to be at home.

Where they put their trust is in traditional brands involved in healthcare. Think Mayo Clinic and Walgreens. Google, Apple and Peloton - not so much.

This means there are opportunities for remote monitoring and other products that allow seniors to stay in their home as they age.

I’ll call out three areas where innovation is needed:

Usability - “Am I seeing a pink line or not? How do I decide?” Develop products for at-home use that give clear, easy-to-interpret answers.

Education - Following from above, “Can I take a test or collect data and communicate clearly with my doctor about the results or know what to do on my own?”

Reduce physician burden - This comes up in every conversation I have about health tech. Doctors have plenty to keep them busy with the patients they currently see face to face. How do we avoid overwhelm and eventually burnout when we throw a constant stream of data their way? There have to be thresholds or other mechanisms to flag what’s important while holding on to all the collected data.

Beyond all that, it will be important to align the patient and physician experience. A doctor can’t be expected to become an expert at every device or test available on the pharmacy shelf.

Kristin on LinkedIn

Report: Home is the Center of Health

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I saw this LinkedIn post from Erasmus Holm, Chief Marketing Officer for the Nordics at MSD, and was curious to learn more. He mentions that the pandemic, although demanding a lot of change, hasn’t necessarily had the lasting effect we expected. He sees companies reverting to the old ways of doing things.

I asked him about how he sees digital transformation, a term I hear a lot, but whose definition has seemed squishy to me. The light bulb came on for me partway through our conversation. It’s not a transformation of just how we do things (interacting digitally, webinars, etc.). It’s a transformation of what we can actually do. What new life science products and services are possible in the digital world?

He makes the point that the human element is as important as the technology.

So technology and buying, you know, software and implementing those kinds of stuff, which is sometimes easy, and often where companies start it's often the mistake, because you underestimate the human transformation that goes into it.

But specifically, it is this critical need for both companies and people, that are really born in the digital age, to understand that we live in a time where digital and real world experiences… are expected just to seamlessly blend into each other.

Amazon, Google and Netflix have raised the expectation for every interaction we have with a company. We should be thinking bigger about ways to serve our customers. Everything revolves around people. Not just our customers, but our colleagues.

…How do you embed innovation? And that comes down to the sort of human aspect of things as well. That if you set up the right teams, you create the environment for people, you start innovation to happen.

And then if you have technology embedded in a company, suddenly you start seeing services and solutions that can actually both do something for the customer and do something for the company in the long run, besides the core product, because we're still a manufacturer of a pharmaceutical. And we're really good at that.

I wondered if a real digital transformation meant not just evolving how customers hear from us, but actually offering new services, possibly changing the business model or expanding it. It’s eye-opening when people talk about what their companies do beyond their core:

It's three phases for us, right? It’s almost like the research development of a product. That's the same for us in the evolution. The first and foremost, we know that we are a research company. The next step, then that's what many pharmaceutical companies end up realizing: Okay. We are also a communication and information company. And thirdly, we are also a technology service data company.

For me, the takeaway is for everyone to think more broadly about the businesses within their business to look for transformation opportunities.

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One of my goals for this podcast series is to cover the use of AI in everything from drug development to the clinic. This episode sits at the trailhead for that journey. I met Nicolas Tilmans, Founder of Anagenex on Twitter. Anagenex is “building a directed evolution platform to develop new small molecules by combining massively parallel biochemical experiments and machine learning.”

Specifically, they are using DNA Encoded Libraries (DELs) to identify small molecules that will bind to targets of interest and use machine learning to refine the pool of candidates and eventually make strong predictions about what compounds to pursue.

Nicolas first laid out some of the challenges in drug discovery. For example, some diseases are still poorly understood. We have identified many mutations and proteins involved in cancer formation, but the target proteins for other diseases have yet to be identified. And I just learned that years of Alzheimer’s research may be based on fraudulent data.

In terms of therapeutics, antibody therapies are becoming common for certain diseases. The also have limitations. While being very specific with regard to targets, they are large, expensive, hard to make and hard to distribute (globally and internally). On the other hand small molecules can be easy to make once identified but can be less specific. The objective is to find small molecules that aren’t destroyed before they work and don’t interfere with things they shouldn’t (two very real challenges).

Algorithms

There are two halves to the DEL approach to drug development. Algorithms and chemistry. We didn’t talk a lot about the algorithms except for this key idea. Many ML algorithms are trained on data sets containing billions of data points (like photos on the internet). Biology doesn’t have a lot of those. Anagenex is addressing the problem by building larger data sets on which to train the algorithms. Making chemicals through DELs allows the testing of billions of possible compounds. Training on larger datasets should result in the algorithms’ ability to make predictions better over time.

Chemistry

On the chemistry side, what comes out of the binding experiments is a mixture of chemicals that bind their target with different affinities. Sequencing the DNA tags tells you what building blocks were used and in what order, but reactions are never complete and those “lego blocks” can assemble in many ways. What the algorithms are doing is making their best guess of the compounds that are in that mix. Those predictions are used to make the next pool to test.

People

The other interesting challenge that Nicolas mentioned is managing bench scientists, whose work moves slowly relative to the speed at which computational scientists can make predictions to test. This is the answer that impressed me the most.

What we do is we try to have people work in the lab. So we'll have people come computational people sit side by side with one of our bench scientists and watch how it happens. I want them to know that every data point that they use was bled for like, it was a real effort to get that data point. And then it means that when you come back and you turn around and you say, here are my predictions or whatever that you understand what you're asking…

…One of our evaluations when we screen is can this computational person explain some of what they're doing to the biochemist, to the biologist, and vice versa? Can the biologist explain what they're doing to the computational folks? That is a thing we hire for.

It’s exciting to see so many fields of science come together. I’m still learning about AI, and continue to be fascinated by how something that is mathematics at its core can be used in so many ways from chemistry to language.

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This week I talked to Don Davis of 5280 Life Sciences Consulting. Don helps companies scale up through leadership development, project and process improvements. He is also the host of the Life Science Success podcast.

The challenge comes when a small company of about ten employees becomes successful and gets an influx of cash and all of a sudden is becoming a company of one or two hundred.

Interestingly, the first thing he mentioned were mission, vision and values. It’s important to know where you are going and those things support the right decisions and behaviors. He also pointed out that when you get to 200 employees, most of the managers weren’t there at the start. If they are not dialed into the direction you are going, things can unravel.

Beyond those basics, we talked about how companies of any size should evaluate the tools they will invest in, beginning with requirements and working from there.

At some point, that small company may be acquired by a bigger company and that brings another set of challenges with integration. It’s not always a case of migrating data. Often small companies will use a tool in ways other than intended. Valuable assets can be lost if those systems are shut down following the acquisition without knowing what information is kept there.

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I highly recommend this episode to anyone who is growing their business either by investment or acquisition.

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What is the path to success in sales when you are selling both direct and through a distributor? What is the best approach for you and your company? Even though it’s sales, I think it looks a lot like marketing based on my conversation with Drew Hamilton. He is the Southeast regional manager at VistaLab technologies.

He is playing the long game by building relationships with his reps (he has 200 from Washington, D.C. to Texas and everything below that line) that pay off in a win-win-win for Drew, his reps and their customers. He was kind enough to share his experience with me and some tips for anyone following this path.

Drew is pushing everything through distribution but describes his activity as 50% managing distribution and 50% “taking it to the people”, walking the halls and knocking on doors.

He has been at it for 11 years and admits the first few were tough. It takes a while to build those relationships. The reps need to check you out before they put you in front of their customers “because their customers are gold.” But after about three years, the investment in those relationships pays off “if you get that snowball effect and business just gets better and better. The job gets easier and more fun.”

I will say as a little tip, the number one thing any new rep needs to do is build a database of all their distributors.

I've got an Excel spreadsheet listed with everybody's email in there. And then I email or call everybody a once or twice a month, whether it's a stock report or a promo just to get myself on their radar, you know, whether they read it or not, and to get my company and my products on their radar. And it kind of builds from there.

That’s the logistics of the relationship, but the secret sauce is the human connection - “just be a real dude.” He’ll talk with customers about Star Wars, Harry Potter (see photo) and sports. And then he makes sure to keep his reps up to date with info they need. Staying in touch is key. He learned early on that bad news is better than no news.

Finally, about five years ago, he started sending Christmas cards. No mention of VistaLab, just pictures of him (dressed as a Jedi) and his family.

Be human. Keep in touch. Share valuable information. Looks a lot like marketing, doesn’t it?

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Darcy Bevalacqua is a career coach and executive recruiter for senior marketing executives over 50. Nevertheless, this episode has good advice for anyone looking to change jobs and even companies that are competing for talent.

Challenges for companies

I asked Darcy about the state of the job market. Companies are having a hard time attracting talent right now. She verified what I have seen a lot on LinkedIn and that is that companies have a hard time “getting candidates through the pipeline in any reasonable period of time. And so many times they lose great candidates because they take too long to make a decision about who they wanna hire.”

The second challenge is compensation. Companies are giving small raises but job switchers are getting 15% raises. Expectations for flexibility and other factors have changes during the pandemic.

Meet the new boss…

Even with those large raises however, more than a third of people who switched jobs last year are looking to move again. Darcy explained that if you don’t understand what motivates you and what you are looking for you can trade bosses and still end up hating the job because it isn’t any different that what you had before.

One thing you, as a job seeker, need to do is really start to think through what is it that I really want in a job?

What is making me unhappy now? Is it the scope of the job? Is it the culture? Is it the lack of flexibility? Is it not enough collaboration or teamwork? Not enough creativity? You need to really look inside and figure out what are your important skills and what motivates you to keep happy in a job.

And once you know those things and you set your career path, it's much easier to look for those in the new opportunity.

In the current environment, she notes that balance is more important than ever and given all that’s going on in the world, people want to work where they feel they are making a difference and making the world a better place.

Getting yourself through the pipeline

As marketers, I hope you’ll all appreciate this. You need to be able to sell your unique skills and do whatever it takes to find that ideal job. Darcy gave an example of a candidate that was not hired but was the 2nd choice. She felt she could really help the company. Darcy encouraged her to talk to the CEO and offer to help as a consultant to demonstrate what she could do. She ended up being hired as the VP of Marketing and got a (ka-ching!) $100,000 raise.

If you’re an older worker, you undoubtedly have skills. But you might have to think about how you frame those to be relevant in today’s market. This is where some coaching could definitely help.

What about imposter syndrome? I personally believe that most people who have it, shouldn’t worry and some of those that don’t probably should. In any case, Darcy laid out some ideas about how to overcome it and focus on what you know you are good at. You should also trust that anyone who invited you to an interview hasn’t made some awful mistake or been somehow fooled by you.

Finally it’s important to keep up a positive routine. It’s easy to start feeling down when the job search is a string of no’s followed by a yes. Volunteering, exercise and a regular get-together with friends are all good options. You’ve got this.

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This episode is not about strategy or tactics or building your marketing team, This week, it's about capabilities.

We're going way back to basics, to do a mindset reset on what marketing actually means. How can marketers know their customers better than they know themselves and solve problems for those customers all along their journey, not just with the products or services they sell?

Michele Benton has extensive experience in marketing leadership and transformational change at global pharma companies. She is now the founder and CEO at Lime where she is on a mission to put the “life” back into life sciences with skill-building programs, leadership and culture-shifting initiatives. What follows is a summary of our conversation mixed with my own thoughts.

Why are marketers 2nd class citizens?

It may be historical. In healthcare, it was sales-driven and I imagine probably the same for scientific equipment and services until the 2000s.

It's not that marketing isn't seen as central, but the reality is your leaders have been in this industry for decades, and most of them have grown up in sales themselves. Very few, have grown up in a very classic marketing environment and there are still biases and implicit things that drive instinct. And so I think that's a lot of what’s behind where marketing is perceived as sort of situated in companies.

What we mean by marketing

Marketing is more than content, campaigns and attribution metrics. It’s making sense of customers, and context. It’s identifying opportunities to solve problems and deliver value.

I think the biggest issue that life science companies have is they're not customer-oriented. And I know everyone will stop and say no, no.

Let me kind of unpack that a little bit. I say they're not customer-oriented. I believe that most companies care about customers, but they work from the inside out. Right? So they start with the company. They start with their products. They start with their therapy areas and then figure out how to, you know, from the inside out to the marketplace.

And when you see what great marketing is, it's just the opposite. They work from the outside in. They start with what the customer needs and brings that inward into the company.

…One of our big cornerstones is around customer obsession. It's being able to remove yourself from your stance and be able to shift and see the world from another. I mean, a lot of my early days, especially in marketing, you go to Walmart and you hang out and you see what people are doing and what are they shopping for.

What is the line like in the pharmacy and how are they talking and what conversations…. really being a student of popular culture, I'm a student of how everyday people are dealing with things and imagining the world where you don't have some of those options.

Why is marketing training so rare?

Many companies will invest a lot in sales training, but not marketing training. You might think it’s because you can get a degree in marketing, but not sales. Yet in the life science industry, few marketers come from a marketing background. They come from sales or R&D and maybe later get an MBA which may or may not emphasize marketing.

We would never dream of putting a sales representative in front of a customer without them going through weeks of mandatory training assessments, and skill validation, and then we'll let you go do your job.

…they take seasoned people and they put them through training and certify them before they go out in front of customers.

And we put marketers in front of million-dollar decisions about resources and messaging and strategy with no training. And if there's training, it's like it's optional.

Value propositions and moments that matter

I asked Michele about skills that she thought were missing. She thought it boiled down to relevant value props. To illustrate, she talked about YETI coolers.

They actually reframed the entire industry, for kind of sports gear and coolers and all of that. And what they did is they said, “Rather than get caught up on the cooler, let me look at the outcome that my customer segment wants to achieve.” And I think in this case, my take on it is, if you look at Yeti advertising, it's about reconnecting your soul with nature, right?

More importantly, Michele talked about her mom’s patient journey and the opportunities for improving the experience of going for treatment. She gave several examples of (theses are my words) poor ideas, executed well. Lots of good intentions but not really appropriate to the specific patient experience.

What can a marketer do within a large system?

The same way you eat an elephant. One bite at a time.

Michele encourages marketers to be an entrepreneur within your company. Look for solutions to those problems one at a time. That’s the outside-in, customer-obsessed approach.

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Lime

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I met Charles Baldridge, CEO of Sol Analytica on a Zoom call. In an eclectic group of filmmakers, artists, music publishers (and data scientists), Charles mentioned that his company helps others with their data strategy. That set off my curiosity and I invited him to this podcast.

I hadn’t really thought about data strategy and didn’t know what it was, but it certainly sounded like something many life science businesses should have.

It will be no surprise to anyone that we are awash in data. And we leave a trail of it everywhere we go. (Charles calls it digital exhaust.) The question is how can we take advantage of it in our business?

Data Strategy- What is it?

…having a data strategy as a company means that kind of from the top down from CEO, all the way down through your kind of frontline workers, when somebody has a question or somebody has a, a problem that's in front of them, if they have a strong data strategy, they're thinking for.

What does the history look like? What do I have available to me to show what that is? And that's data, that's the information that is available to you. And so I think of a data strategy from that perspective, as it's the first thing that people go to. When they're thinking about making a decision as what does the data say, what information do we have available to us so that we can do a good clean job of making that decision and defending it?

It used to be expensive but it’s not any more. CEOs know in the back of their heads that they should do something. Of course, the most important thing is knowing what would you like to improve? What problem would you like to solve? Do you have data that can help? The process is iterative. With each answer you might have another question that makes you dig deeper. And of course if you can’t answer that, you may have to figure out how to get the data you need. Which brings us to the idea of having a data culture.

I’m always curious about company culture so the idea of a data culture captured my attention.

Data Culture

Building a data culture is about collecting and storing data “in a way that gets everybody speaking the same language within your cohort or your people that you're talking with.” It means actively thinking about what data you may want in the future. What should you capture? How should it be stored so you can use it when you need it?

I can’t help but picture a garage full of stuff that has been stored without a lot of organization. It can be overwhelming. Data is like that. Too much of it can keep you from doing anything because you don’t know where to start. I may take a shot at the garage this weekend. Pizza and beer if you show up.

Your data has value to others

Having a data culture is also recognizing that your data may have value outside of your own organization. Charles gave an example of medical billing. A company with a large data set could see which insurance companies paid the fastest and the highest percentage of what was billed. That data may would have value to others to forecast their own accounts receivable, for example, and even to prioritize their own billing to optimize cash flow.

Distilling data into wisdom

There are many levels to the value in the data. There is data itself which can be useful for someone else to answer questions that may be different from what you are interested in. Then there are analytics that provide insight that may be valuable to others. At some point, you might be able to create a data visualization that has value because of patterns it reveals that provides insight to anther group. Companies pay for access to that kind of information.

Using (and supplementing) your data for AI

Eventually we got around to artificial intelligence. Just as for analytics, you need to know what you are looking for. What is the problem you are trying to solve? The next step is data wrangling - apt metaphor for getting your data together, making sure you know what’s there and what’s missing. More on that in a moment.

Finally Charles suggests care in selecting the people who will help you with the right algorithms for your project.

A lot of this ties together. In some cases you might not have all the information you need. There is a good chance that someone else might have an overlapping data set that can help. You can get these through a data exchange.

…the exchange is the place where you go out and either provide that data or purchase that data.

And so in the context of AI, we mentioned, you want to know what your questions are. Well, it's iterative. You're not going to know every question. And in fact, if you're doing science appropriately, when you get the answers to questions, that actually makes more questions. And when you do those more questions, you may realize that there's additional data that you need to answer those questions and you don't have it.

So you might go to a data exchange to collect and find that information and pull it in bring it into your data infrastructure into your warehouse or your data lake. And then expose it again to your analytics tools and to your artificial intelligence tools. And then, you might be able to go and answer that question and it makes some more questions.

Think of it as a way to add columns to your spreadsheet. For example, you have a name and an address. Someone else might have name and place of birth. Now you have an extra column on your table for understanding how far people migrate over the course of their lives. Once you understand that, it may bring up other questions. How does that relate to income, for example?

I could use some data

I’d be interested to hear in the comments if data strategy is obvious to everyone or if this is something new to think about. I’m still learning. More importantly, I ‘m interested in what you would like to learn from this podcast in the future.

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Machines have been helping us with physical work for a long time. Now with AI, machines are helping with the knowledge work. At the outset, AI was working with numbers. Now it’s working with images, words and language. And I’m discovering it’s everywhere with still great potential ahead.

Sidd Bhattacharya, Director of Healthcare Analytics and Artificial Intelligence at PWC gave me a lesson on the history and current state of AI with some thoughts about the future.

The reason why you see a huge explosion or like a buzz around AI now is the fact that the applications have moved into the realm that you and I can understand… language models. People talk, Everybody has a language that we talk in. Now we are having AI help us create that language, fine tune that language. So that's the other thing. That's what makes me more comfortable that, you know, we're not going to go into an AI winter anymore because the applications of AI have become so commonplace. Now everybody is using it without actually knowing about it. So that that's what makes it so cool.

Winter came and went

What is this AI winter Sidd is talking about? The dark side of my brain pictured some Game of Thrones-like drama (haven’t seen it), but Sidd explained that the AI winter refers to a drop in funding when AI was, shall we say going through a bit of a rough patch.

Two groups of academics had (surprise) different approaches to developing artificial intelligence. On one side of the debate were the symbolists. They took a rules based approach to training machines to solve problems. Think of rules like rules for addition e.g., 1+1=2. The rules of the operation determine the outcome: 1-1=0.

On the other side were the connectionists. Their approach was to let the system figure out the rules based on inputs and outputs. In a neural network, it’s more like 1 ? 1=2. What rule (?) is needed to make that work? For a given set of inputs and outputs what do the rules need to be? Eventually with training, the neural net knows what to do with the input and can “show you” the output, which is what we really want, right?

After a period of decent funding, the rules folks’ approach didn’t pan out completely and the money spigot dried up. Eventually though, Geoff Hinton at the University of Toronto proved that a neural net could match or do better than a human at recognizing images. Spring had arrived and the next AI boom was on.

I’m getting less worried about this

Wouldn’t we like to know the rules that a model has decided on? That might make us more comfortable and help us think about potential problems. For now though, the neural network can’t always show you the rules it has come up with. This is the black box or transparency problem, about which I’ve had concerns or at least curiosity. Sidd’s response is we don’t always know the exact mechanism of action of a drug, but we take it because it can deliver the outcome we are looking for. Having said that, Sidd believes that there will be more transparency around the inner workings of AI in the next couple of years based on the volume of research going on. And in a future episode, you’ll hear about an AI technology where the rules are entirely transparent.

What about ethical AI?

Along with transparency, this is a concern people share. Bias in the models can result in discrimination or other undesirable outcomes. Sidd Points out that the AI isn’t biased. Bias is a result of the data used to train the model. In fact, the AI can sometimes reveal bias in the data when the outputs are analyzed. Companies are investing heavily in making sure their data is clean and fair. No one wants a surprise in this regard.

It's a real topic. People are talking about it and making investments on making sure the data sets are clean, making sure they have independent bodies reviewing the data. Making sure that every project that you're doing an AI, people think about the risks and document it from an bias, fairness point of view.

That's also very important, right? Like if you can document it and put it in writing and said, yes, I thought about this risk and here's how I'm going to mitigate it. That'd be helpful.

But looking at the data for bias isn’t always a simple task.

The issue is it's very complex. It's very difficult to understand it by just looking at the dataset. We are getting better at it. So that's the challenge. You'll have to understand the data, work with it, see the outputs and test in the real world before you can launch it in production.

Life sci lagging but catching up

As we heard on a previous episode, life science and healthcare are lagging behind financial services in terms of implementing AI. But they are catching up. We’ll always be more cautious when a patient is involved. Covid has been an accelerator, as it has for everything. There is promise across the value chain from drug discovery, to regulatory (authoring documents?) to clinical trials and commercial. A few episodes further down the queue, we’ll hear some amazing stories of AI in life science and healthcare.

Things like helping with like omni-channel marketing, helping medical call centers, helping with training for sales forces, help augment some of your existing sales force with the right tools, recommendation engines...That would be a huge area of focus in the next few years. So throughout and you know, supply chain, manufacturing.

That's another big area. One cool story. And I worked with that company that, that, that uses AI or computer vision to look at defects on their production line. So anytime there's a vial or there's a pill missing, you have a computer camera that alerts the person saying, “There's something wrong. You might want to come and check.”

Future trends

What does Sidd see for the near term future of artificial intelligence?

…over the next couple of years, there are two key trends I'll call out. One is in the data domain… People talk about data and every time you start talking about AI, cloud, they talk about how data is messy. I see this problem getting solved with the use of advanced or something called synthetic data.

These synthetic data sets can be used to train and run AI models, avoiding altogether issues of patient privacy, HIPAA compliance, etc.

The other trend on the horizon is using AI at scale.

…over the last few years, every company, every life sciences company I've worked with, they have dabbled in AI. Some of them have done more. Some of them have less, but have not, except for maybe a couple, there haven't been a lot of success stories of deploying an AI model, deploying an AI product at scale and getting benefits from it…

People are now at a stage where they feel comfortable. They understand that, that they understand the limitations of the tech. They understand what it can do, what it cannot do, how to manage people around it and get to get over their anxiety. And the next step is to scale it up.

Scaling up requires getting started. In my short time learning about this topic, I keep hearing two rules for implementing AI:

Define the business problem you are trying to solve.

Get started, even if your data isn’t perfect. Because it never will be.

Obviously we should do our best to clean up the data we have. I was still curious about the risk of significant errors even with synthetic datasets. Sidd went back to the analogy of employing an AI model as you would a human being. You wouldn’t turn a new employee loose the first week on the job. AI should be treated exactly the same way. Train, test and supervise until you are confident in its ability to do what you hired it to do.

Connect with Sidd on LinkedIn

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Failure

66% of AI projects fail. That’s the bad news. The good news is that in life science we’re not really investing enough or working on the important problems yet. The opportunities are still there. So we’ve got that going for us.

Severence McLaughlin is the CEO of DeLorean Artificial Intelligence. He has some thoughts about what is actually AI, how it’s being deployed, and the impact it could make if companies stopped doing science experiments (investing in little test projects here and there) and had a vision for achieving business objectives at scale.

We’re pretty good at RPA (robotic process automation) but are we helping doctors and patients yet?

The value of AI (as opposed to advanced analytics) is the ability to make a prediction with a probability assigned to it: When will a patient going from diabetes to chronic kidney disease as her primary diagnostic code? When a physician sees that, what are the next best steps for that individual patient?

Opportunities

We have enough data on individuals to move beyond the one size fits all approach.

Not… “Hey, we're going to take this data and it says this, and we're going to apply it to everybody. One size fits all. Another colleague would call that primitive AI, which means analytics. But now the ability is to say, okay, you're a diabetic, but you're eating a rabbit diet, you're doing yoga...Maybe we can get your A1C down by going through lifestyle.”

Sev, I'm one cheeseburger away from a heart attack, man. We need to have some heavy medication. So it actually goes out to the individual person and has that capability. So hyper personalization.

Sev extended that idea to the sales opportunity. How do pharma reps build relationships with doctors? AI can inform the next best action to take based on what a doctor is likely to respond to.

I have wondered whether pushing info to doctors will lead to prescriptions based on… (I don’t know what.) I challenged him on that and he pointed out that many doctors are too busy to keep up with the latest and greatest. Wouldn’t you want your doctor to have that info? To know about the therapy that is most likely to work for you?

In the case of a rare disease, how do you find the one doctor that can help the 1200 patients in the US that have it? Or help a doctor correctly diagnose the patient in front of her?

What about clinical trials? Could AI help select the patients most likely to respond to your therapy? That seems a bit of a chicken and egg scenario, but if that were possible, it would make marketing the drug a lot more cost effective following approval.

Getting Started

My last question was about data readiness. The data is never perfect and never will be. Again, the vision needs to be driven from the top by the CEO to get all the parties involved working together. For applications around marketing and sales, Sev thinks 60-70% clean is good enough. Of course, you’ll want to do better than that for clinical applications. The way to get better is to get started.

If you have thoughts on any of this, please share them in the comments. I’m here to learn. If nothing else, tell me what you think about my intro music.

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Susanna Harris talks about her communications role in the biotech venture capital world.

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Color Science and Digital Imaging

I don't think many people paid too much attention to the sort of miracle that produces color technology in a digital device, because we were so used to using color film, which itself is a technological masterpiece to balance the various photo-sensitive pigments that would result in images that we perceive with our human visual system to look the same as the scene we took a picture of.

This week’s conversation is with Jeff Carmichael. An expert on imaging systems particularly around the use of filter technology for looking at light from different parts of the spectrum.

Color sensors don’t see color, they detect light and have either a red, blue or green filter over each pixel (a Bayer filter array) which blows my mind in terms of manufacturing, not to mention integrating all the data it captures across millions of pixels.

Then all that data (voltages counting photons) is turned into numbers that can be delivered to a screen that somehow reverses the whole process and presents us with an image that looks very much like the original scene.

Jeff described for me how light of different wavelengths were associated with our actual perception of those colors based on a couple of experiments by the Commission Internationale de l'éclairage (CIE) involving 17 people in the early 20th century.

You may have seen one of these chromaticity diagrams in relation to calibrating a computer screen.

Now imagine your camera collecting light in three different buckets, just red, blue and green, each of those somewhat arbitrary and imprecise, and still making an image you would hang on your wall, watch on Netflix or further manipulate before you post on Instagram. It’s all just math, right?

Microscopes with digital cameras are an obvious application. But what else can we do inside the imaging world in life science?

Remote Sensing

How about remote sensing of environmental features where by looking at specific parts of the spectrum through various filters, you can make some determinations as to what is going on? Think about things like assessing the growth or health of crops, or the biomass of plants in the rainforest. Pour yourself a glass of wine, look up at the night sky and appreciate the fact that the satellite you see whizzing by may have helped determine the maturation of grapes in your glass.

The Normalized Differential Vegetation Index (NDVI) is a measure of vegetation based on comparisons between the red and near infrared light reflected from them (NIR - R) / (NIR + R) = (math again). I asked if that was a form of machine vision.

Machine Vision

It turns out machine vision is a little different from remote sensing.

While remote sensing is at the mercy of ambient light for the most part (we talked about LIDAR as an exception) machine vision is more like studio photography -highly dependent on consistent light sources. It’s used primarily for repetitive analyses like looking for defects or sorting pistachios.

In life science, machine vision may currently be limited to routine applications ensuring that sample tubes have adequate sample, caps are on, the right tubes in place, etc. for high volume automated analyses.

What Jeff is interested in is following a developmental or disease model e.g. an embryology experiment where one might be watching for a long time without interacting with the subject.

Now, perhaps someone out there is hearing us and thinking, Jeff, you idiot. We do this all the time and maybe someone does. But it's not widespread like it is in industrial automation.

If that someone is you, leave a comment. I’d love to chat with you. As would Jeff, I’m sure.

Two separate paths

One interesting thing that Jeff has observed is that the machine vision space and the life science space seem to be on parallel tracks seemingly invisible to each other.

For example, both sectors have companies developing similar light sources, LED light engines he calls them, that can be controlled by software to get the lighting you want. But he’s not aware of any interaction between companies in different sectors.

LEDs have become, they have been for a long time now the dominant type of light source used for lighting and machine vision applications. They don't get hot, they use little energy. They can pump out a lot of light in a very small wavelength range. You can, overdrive them so that they cycle really fast and can do very fast imaging.

The same seems to be true in artificial intelligence (we had to get there, right?)

For example, Landing AI and Path AI are both in the life science space, focused on machine vision and pathology respectively. Jeff is curious whether each segment (ML and LS) has something to be learned from the other.

Because usually things mix and sorta come out in the wash in the end. So one resolution, I don't know, it could be that they borrow from each other on their particular AI approaches, right? And machine vision, they might be using a certain way of approaching AI that they hadn't thought of in the life science and vice versa. That could be the way that they merge. Like in music, you borrow from each other.

We’ll be listening to see what happens.

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Economist Joey Von Nessen talks about the growth and the impact of life science on the South Carolina economy.

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At the beginning of the year, I said I would follow my curiosity. One of the things I was curious about was 3D bioprinting. What does that even mean? I talked to Dr. Mohammad Albanna, CEO and founder of Humabiologics to learn more.

Imagine creating 3D structures from living cells and a biological matrix. Then imagine depositing the materials for that structure with an injet printer. I promise, I didn’t get this watching Netflix.

Dr. Albanna described for me the story of Dr. Tony Atala who grew a replacement bladder for a boy from that boy’s own cells back in 2001. And that boy, Luke Massella is now a grown man with a lab-grown bladder that is working to this day.

Indeed, early experiments involved cleaning out injet cartridges, replacing the ink with biological materials and loading them into a printer.

Now there are a handful of people with a bladder like Luke’s. Creating organs, though, is complicated. Kidneys, for example, have 20 different types of cells within them. They all have a job to do and they need to be in the right place in the right numbers to function. Similarly for a heart, or a liver, you need to get nutrients and oxygen in and waste out, not to mention assemble structures that can withstand the force of pumping blood.

Transplantation is the exception. There are more immediate uses of 3D bioprinting. One is creating tissue models to better understand disease. Another is for testing drugs in development for both toxicity and efficacy. What if we could test a panel of drugs against a patient’s tumor to see which works best? Combined with genomic analysis, we might be able to find the right therapies faster (and probably learn a lot in the process).

Listen to the full episode to learn more about the mechanics of 3D bioprinting, the need for allogeneic off the shelf materials and what Dr. Albanna sees for the future.

Thank you for reading cc: Life Science. This post is public so feel free to share it.

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You may have a lot of quantitative data. But it’s what you don’t know that you don’t know that will hurt your marketing. Wayne Cerullo explains what it takes to get around the data delusion.

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Karen Kilroy is the founder of Kilroy Blockchain as well as an O’Reilly Media author.

Karen’s company develops blockchain workflows to be implemented for companies. Our podcast conversation meandered far from my notes because, as blockchain is new to me, everything is interesting. We actually started off talking about artificial intelligence and how blockchain has the potential to make AI less scary.

For this article, I’ll stick to understanding what it is, presenting some use cases and Karen’s thoughts on how dip your toes in the blockchain pool as a way to get comfortable and see the potential.

What is Blockchain?

Blockchain, as you may know, is the technology behind cryptocurrencies like Bitcoin and Ethereum. Those are open unpermissioned networks.

A blockchain is a database spread (mirrored) across multiple computers, often referred to as a distributed ledger. That ledger is a record of transactions. When a transaction (currency transfer, receipt of a product, whatever you like) is validated, a “block” is added to the chain and given a hash reflecting the contents of that block. The hash is a long alphanumeric based on the content such that if the content (the transaction is changed) the hash will change. That is what makes the record immutable, or more accurately, tamper evident. Because the ledger is distributed, everyone will see that a change has been made.

Smart Contracts

The Ethereum blockchain supports the use of smart contracts, code written into the blockchain such that transactions can be automatically executed when the agreed upon criteria are met. For example, we could devise a smart contract where you send me a dozen chocolate cookies every Monday and my next newsletter includes a shoutout to you. No shoutout, no more cookies.

Use cases

Supply Chain

This seems, as in my example, to be the most commonly suggested use case. It goes beyond shipping and payment, however. Imagine, that sensors keep track of the temperature, humidity and travel time of the cookies. I don’t have to accept stale or melted cookies. By now you can see the value to life science products where the cold chain is important.

Compliance

While companies spend a lot of effort to make agreements and put them into contracts on paper, in the real world those may end up in a drawer with people doing their best to follow those agreements, but possibly creating unnecessary risk by not following exactly what was intended. You can imagine that having conditions written into a blockchain on top of whatever system you like could ensure compliance or deliver prompts when some aspect of a transaction is missing.

Silos and Security

Data is power and data is also money… Everything is all about data. So, you know, going way back, you have siloed data and departments that won't talk to each other and departments that won’t work with each other because that takes away their power and there's no new advantage to it. So what you can do with blockchain systems is you can, you can anonymize the data in such a way where you can share it with the larger group for the greater good, without giving away all your secrets.

Karen gave the example of a foodborne illness outbreak. In this case, it could be possible for a grocery chain to identify which lots of lettuce were contaminated for example without revealing who all of its suppliers are.

Implementing Blockchain

Nevermind crypto this and NFT that, blockchain can be overwhelming. I wanted to know how can a company get started to see what the possibilities are for implementing it on some systems without throwing in the towel because it was too much right off the bat. What does the path to adoption look like?

First of all, recognize that we’re talking about closed, permissioned systems where different groups may have different levels of access to look at or add records (just like you are used to).

Cake Analogy

Karen made a good analogy to wanting a cake. You can make it from scratch, buy a mix in a box, or buy the whole cake.

You can build your system using Hyperledger fabric or Ethereum.

…in that case, you're going to need to do all your own upgrades. You're going to need to watch for security holes. There's really a lot of of work… There's a lot of maintenance etc...

The cake in a box equivalent is tapping into an already built platform that can be implemented to meet your needs. And finally, buying the cake is a purpose built application, just like any other application.

Do you see applications for your business beyond supply chain and compliance? Is your company starting to talk about implementing blockchain for any systems? I’d be interested to hear how it’s going.

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Lily Elsner talks about the path to her job as Head of Strategy at Arctoris, a startup working on small molecule drug development.

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Lily Elsner talks about her job as Head of Strategy at Arcturus, a startup working on small molecule drug development.

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If you haven’t already, I imagine many of you are currently or will soon be dealing with aging parents and their desire to stay in their home for as long as possible. And why wouldn’t they? That’s what we would want for ourselves. So how to balance that with knowing when assistance might be necessary? A daily phone call to check in might be annoying for the parent and take the joy out of a genuine conversation for anyone.

Alfred Poor is the editor and publisher of HealthTech Insider. We had a conversation about what the future might look like for fulfilling those wishes and feeling confident about being able to help when necessary.

An Alexa device can already be handy for reminding people to take their medication or exercise. Alfred is interested in technology that might be able to make assessments based on changes in someone’s voice or the sound of a cough to, if not diagnose, raise an alert. Imagine if the device could detect anxiety or depression. What if that could send a prompt to have you check in with your parent?

Loneliness can be a big challenge for anyone, but especially the elderly. The pandemic has affected half to two thirds of adults in terms of mental health. There aren’t enough therapists or health care workers to deal with those numbers. But an app that can suggest breathing exercises, help with a guided meditation or a prompt to get out and go for a walk may reduce the burden for the individual, saving in-person visits for more urgent cases.

As with any technology, I worry about the downside. Does relying on digital assistants to help our parents make it easier to forget to call and just say hello? Is that a trend we want to enable, or end up as a “beneficiary” of?

What about assistance in the case of a fall? We talked about the wearable pendant with a red button on it. It turns out that no one wants to wear that. And only in 7% of cases where it could be used does the wearer actually press the button. The biggest reason to not push the button? “I don’t want my kids to move me out of my home.”

What if Alexa could identify a fall and ask if you need help? Alfred described to me how he manages to keep track of his 100-year old mother who lives alone 6 miles from the nearest neighbor. He installed a Smart Water Assistant called Phyn designed to notify you in the case of a water leak. Because it knows which faucet or toilets water is going to, he can “see” that his mom is up in the morning, making dinner, getting ready for bed. etc. Without being invasive, they are both comfortable with the level of monitoring it gives them.

When I asked about privacy, Alfred suggested that having all of our health data in one place would be beneficial in terms of individual treatment but also in terms of the opportunity to look at the data and learn from it on a population level. You can listen to the podcast for a detailed example using AI to identify distinct groups of diabetics for whom the outcomes with respect to exercise were significantly different. He makes the point that your credit information can be equally damaging as your health data. But we allow access to it (with qualification) through credit bureaus. It’s an example where the individual owns their data, but it is held somewhere else.

What are your thoughts on remote monitoring for keeping track of loved ones’ health? Let me know in the comments.

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Raman Sehgal shared his journey to becoming an agency owner, the value of a niche and what good clients look like.

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Tom Fox thinks podcasts are a great way to teach people about compliance. And he's right.

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Bonni Scepkowski wants you to build relationships, not look at spreadsheets. Here's how to keep your attendees engaged.

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Jennifer Andrews explains the importance of personal branding for scientists and offers a strategy for developing your personal brand.

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Sandy Donaldson described Impiricus's platform where physicians can request support for patients such as samples or prior authorization via SMS messaging. This removes the friction of digging through a website to find the resources needed.

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Adrienne Leussa is the host of Africa Biotech Conversations. We chatted about podcasting and what's happening in the African biotech community.

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Chris Cullman shares his thoughts on customer experience, data and attribution, and opportunities to have physicians reach out to you.

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Renee Connolly describes some best practices in corporate communications in the context of Diversity, Equity and Inclusion at Merck KGAa, Darmstadt, Germany.

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Hemal Somaiya describes using AI to message physicians at the right moment for their patients.

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Frank Dolan talks about the value of disease state education for a company pre-launch in terms of providers, patients and payors.

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Justine Dees talks about sharing her knowledge and love of science to become a blogger and content marketer for life science companies.

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Dan Chichester talks about transitioning from comic book writer to healthcare marketer, building trust with partners and creating a positive vision for the future.

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Bob Lempke talks about ways sales people can engage and build relationships with customers in a world changed by Covid.

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Maaria Ginai describes her transition from scientist to agency owner via YouTube and tech transfer.

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Mark Stiving talks about optimizing pricing by knowing the value of your products and different pricing models that may increase profits.

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Susan Nemetz talk about the benefits of reverse mentoring (learning from younger employees).

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Jason Scharf talks about how planning for long tail events can present opportunities for competitive advantage even in the absence of the event.

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Mark talks about the value props for buyers and sellers as well as tailoring them for resistant customers.

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Max Paluszynski talks about the challenges of creating a unified campaign and managing groups that are not direct reports.

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Rachel shares tips on optimizing your profile, connecting and what type of content to share.

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Darren Alvares discusses the results of a ResearchGate survey of scientist purchasing behavior and the impact of COVID 19.

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Steve Kulisch describes the steps he took from undergraduate science degree to GM at Fluidigm.

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Lori Dowd explains that successful virtual events require a different mix of content to keep the audience engaged.

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Amy Duncan explains the purpose of a competitive audit for your marketing and what goes into it.

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Matt Benson describes how content marketing is differentiating his company in an industry (lab furnishings) where relationships, dealer networks and trade shows have dominated.

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Frank Dolan talks about the challenges of launching your first product at the same time you are launching your company as a commercial entity. There is an opportunity to establish relationships and build a brand before that happens.

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Matthew Ray Scott talks about how marketers and doctors can take advantage of LinkedIn to grow their business.

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Dodi Axelson explains how Cytiva (formerly GE Healthcare Life Sciences) thinks about heir podcast.

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Owen Swift explains what a sales agent is and the advantages for both the company and the individual. He also describes the scenarios where this model makes the most sense.

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Kelly Grover talks about when marketing to scientists is different from marketing to consumers and when it's not.

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Hamish Mackenzie talks about positioning strategies and the one position that is often overlooked because it seems obvious.

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Hans Kaspersetz describes a data driven approach to creating content that Google sees as authoritative and meets your audience needs.

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Frank Dolan talks about driving innovation in how products are brought to market in the life sciences along with restoring trust in the biotech/pharma industry.

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Lemar Ashhar describes how he finds prospects and develops relationships on LinkedIn using content.

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Leslie Loveless describes what life science companies are looking for and how it has changed in the last few years.

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David and I discuss what content is appropriate and how to produce it.

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Andy Bertera describes the culture at NEB and how it influences their marketing tactics.

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Liz Ingle Explains how to make sure your marketing strategy matches your business strategy and how to avoid or overcome a disconnect.

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I met Chris Walker, CEO of Refine Labs, through this LinkedIn post. I liked his take on long form content (surprise!) and asked him to join me on the podcast. He advocates an audience first …

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For most life science companies, I'm pretty sure the event budget makes up the biggest fraction of the total marcom budget. Sometimes it's over half. If you are producing or hosting the event, such as …

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Successful marketing is based on strong branding and positioning. Then your creative communications must tie back to your strategy. Patricia Malone of Freshblood Group explains why it's important …

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Sondra Hadden describes the tactics C&EN uses to promote content to grow it's audience and help advertisers get a return on investment.

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A new business has a lot of things to think about and choices of where to put their resources so it can start making sales and gaining traction. Lisa Thurston helps companies put some structure …

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We hear a lot about voice of customer in marketing. But we don't hear a lot about "feeling of customer". Kris Barnette joins me on this episode to describe two campaigns he worked on at Thermo Fisher. …

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Your customers are experiencing moments of pain. Sometimes those are nagging little problems. Others may be more urgent or even life changing. Each of those moments is an opportunity to apply …

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Big announcements around product launches or other news are opportunities to drive significant interest in your company and traffic to your website. But sometimes search volume goes up and traffic to …

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How are you really going to describe what you're talking about? Whether it's the company, the technology, or the product. What lexicon are you using? What words are you choosing? What phrases are …

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In large companies, product management is an important part of the marketing function, a bridge to R&D and many other functions. Smaller companies can also benefit from having an individual who …

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I'm pretty sure your organization has a story to tell, whether about your brand, your mission, or a new technology. How those things came about can make for a powerful story, particularly in an audio …

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Many life science brands are struggling to make the most of social media. There are however notable exceptions. We've talked about some of those before on this podcast. In this episode, Mary Canady … [

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If you happen to be in the middle of a job search, this episode is for you. Mauri Schwartz was a key person in getting me to where I am today. After having worked in a lab for about 20 years, I …

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A listener asked me to do an episode on benchmarking campaigns. I happened to be at the ACP-LS meeting with Jim Breault and Alan Abery from Springer Nature publishing right at that moment so I asked …

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How is your executive presence? The way you speak has an impact whether you are an executive in a high stakes conversation or a manager leading your team. Scott Stiefvater is a public speaking …

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2019 is the year of video marketing - again! It has been important and continues to be. But just making product or "About Us" videos and posting them to YouTube is unlikely to get the results you want …

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How is your executive presence? The way you speak has an impact whether you are an executive in a high stakes conversation or a manager leading your team. Scott Stiefvater is a public speaking …

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I think this is the first time we've ever talked about media strategy on this podcast. I met Keith Betz at Digital Pharma West earlier this year and thought it was about time we covered it. Keith …

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Cell Signaling Technology (CST) recently won a Life Science Industry Award for Best Digital Advertising. I asked Rebecca Reppucci, Director of Marketing Communications, how they achieved that. When …

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Mike Collins started CEM Corporation in a garage, took it public and then bought it back. And the garage wasn't even his... Most companies talk to their customers as some part of their product …

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You know that person who never understands what you are trying to get across? For somebody out there, you are that person. I'm that person. Jessica Pettitt and I had a light-hearted conversation …

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I recently moderated a panel on media relations at a Chemical and Engineering News (C&EN) event for scientific marketers following the recent ACS fall meeting in Boston. I was lucky to have two …

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think we can all agree sustainability is important. But how does it contribute to ROI? How do you incorporate it into your business? And is there a competitive advantage to be gained from doing …

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Google cares about more than what it sees on the page or the number of backlinks you have from other sites. Those are important, but technical SEO (search engine optimization) can be easier to …

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Sarah Osteen is a leadership coach and works with organizations frequently around communication issues. A common topic is the concept of persuasion and how to use your power and influence to change …

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This is a special episode with Jeremiah Worth, VP of Client Strategy at CG Life and guest host Hilary Graham, Director of Scientific Marketing and Applications at Luminex Corporation. You may have …

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...we set out to become a more approachable company and in the end, it helped us also to fill the sales funnel in a really, really massive way. Social media can be overwhelming, but you can get a …

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Large companies frequently bounce between two approaches to marketing communications. Should each unit do its own marketing or should there be one central "agency" responsible for serving all the …

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We've talked about narrative storytelling on the podcast before, usually in the context of video. In this episode, I'm sharing an example of what it sounds like in a podcast. Or rather, what it feels …

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Is your brand ready to respond in a crisis? And could you come out of it stronger than ever? If so, then you have an invincible brand. Melissa Agnes is a crisis management expert and she passed …

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Do you ever wonder if the document or presentation you've been using for marketing or sales is the most up to date version available? Would you even know where to look to be sure? A Digital Asset …

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You've got to understand your customer. That sounds like marketing 101. But we may overlook why that is so important for your business. Paul Orange, GM of eCommerce at GE, explains what you may be …

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The practice of marketing is changing quickly with new technologies and channels. But using those effectively requires deep understanding of typical human behavior. As human beings, scientists …

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I saw this article from Jennifer Oladipo that she shared on LinkedIn. Jennifer has been on the pod before and I like the topic so I asked her to come on again and talk about transparency and …

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How do you tie your investment of money and effort in content marketing to actual revenue? In this episode, I talk to Chuck Miller of the Market Element about the specifics of measuring content …

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Google Analytics is a handy tool right out of the box for understanding your website performance. But if you spend a little more time inside the application you can get some very useful information …

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How can you spot trends in research to be more effective with your marketing efforts? What type of publicly available data will let you do that? And once you've spotted a trend, what then? These …

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...we set out to become a more approachable company and in the end, it helped us also to fill the sales funnel in a really, really massive way. Social media can be overwhelming, but you can get a …

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Illumina has significant market share in genomics. How would they reach beyond their current users to grow the market for genomics analysis? A podcast of course! Paul Bromann is a Scientific …

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Ian Lurie knows how to make content marketing work. I interviewed him after his presentation at the ACP-LS Annual Meeting last October. He shared a lot of ideas and resources to help all of us make …

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...conversations lead to relationships, relationships create opportunities, opportunities lead to sales...-Phil M Jones I find a conversations challenging in some situations. Hosting this podcast has …

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Tamsen Webster told me " Most organizations don't know why they act the way that they do." That's a big problem for branding, because the gap between what is likely your aspirational brand (how you …

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Ethan Kopit assures me that artificial intelligence is going to make our jobs easier and more interesting. Rather than replacing us, it's going to automate the routine tasks we shouldn't be spending …

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It's becoming easier than ever to personalize every bit of a customer's digital experience with your company, from the web to the products they have in their lab. This is good news in many …

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Companies with significant market share have a huge advantage over the competition. It's a form of social proof that has a big impact on a customer's buying decision. Mike Cammarata returned to …

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It's here. The future, that is. I got to experience virtual reality at the ACP-LS annual meeting in Boston last month. Then I sat down with Chris Bybee, the president of Raindrop, to talk about …

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Knowing your audience is essential for any type of successful communication. If you are doing content marketing, you probably have a few different types of people in your audience, even for the same …

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Many life science companies are shifting from a focus on technologies to be more focused on their customers. I asked Jeff Mazzeo, VP of Marketing at Waters Corporation, "What's driving that …

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Many life science companies are shifting from a focus on technologies to be more focused on their customers. I asked Jeff Mazzeo, VP of Marketing at Waters Corporation, "What's driving that …

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Do you ever wonder about all the clicks you pay for that aren't relevant to your offering? Even if you have built a pretty good exclusion list, you could still be wasting money. It's not reasonable …

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ESPN is in the storytelling business. Sports are nothing but stories in which we imagine ourselves as players in some way. "What does it feel like to..." The Trials of Dan and Dave is a …

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Not just great. Exceptional. You know someone who fits this description. It's someone you admire. He or she has a seemingly magical ability to drive a vision and make things happen. If you'd …

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You've probably heard me say, "The most effective marketing you can do is to keep an existing customer happy." In this episode, I spoke with Bonni Scepkowski of Stellar Meetings and Events about how …

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I pulled together some highlights from the last year, all related to the topic of content marketing in the life sciences. 1:30 Andy Bertera - How NEB Owns the Buyer's Journey How NEB sees …

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We've talked frequently on this podcast and on my blog about developing a content strategy. This episode looks at it from a different angle. It's about how to coordinate and execute your strategy …

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Joan Boyce knows the publishing business. So who better to talk to about how an editorial calendar is really used by a media company and how to make one for your life science content marketing …

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Account Based Marketing is a popular topic right now. What does it look like in the life sciences market? Ethan Kopit, a co-founder of Acenna Data explained it to me very well. Although it has a …

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This episode is primarily aimed at life science marketing agencies but in-house marketers will learn a few things about how to build better relationships with agencies and improve the selection …

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Life Science marketers have lost the link between strategy and execution. The goals they are looking to achieve are often replaced with activities they think they should do. As a result, according …

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A life science startup that isn't thinking so much about branding and is focused only on technology, might be missing an opportunity. Echo Laboratories manufactures a revolutionary microscope that …

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Google's objective is to rank content that either helps somebody complete a task or answer a question. Life science marketers have an opportunity to both learn from Google and help draw the roadmap …

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Have you ever been "gifted" a product from R&D and then expected to figure out who wants it and why? Surprisingly, this isn't uncommon. This episode is all about avoiding that problem and even …

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Well yes, of course you can. In this short solo episode I explain why an online workshop is ideal for both small and large companies. The reasons are different, but there are benefits for both. I …

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The American Chemical Society uses content marketing to attract scientists to their products - journals, which contain more content. How do they do it? How do they persuade scientists to publish in …

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Steve Jobs said hiring is one of the most important skills a manager can have. Bob Penney is passionate about building teams. Not in the sense of "Let's all go rock climbing." Rather it's assembling a …

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After 55 episodes of Life Science Marketing Radio, my good friend and colleague, David Shifrin, decided it was time to flip things around and interview me. We talked about the vision for both my …

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New England BioLabs has been ranked at the top of life science companies for its Customer Experience. How they do that? And how they think about elements of the customer journey as contributing to …

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A life science startup with a narrow portfolio needs to ensure that its sales team is only pursuing highly qualified leads. With a broader portfolio, you might be able to go after more leads …

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According to Content Marketing Institute's Seventh Annual Content Marketing: Benchmarks, Budgets and Trends Survey, 70% of companies are going to create more original content next year, even though …

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Marc Andreesen said "Software is eating the world." Software has created markets that were previously unimaginable or impractical. AirBnB is the largest provider of rooms and Uber is the largest taxi …

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I honestly don't know why this wouldn't be top of your list, looking at, you know, in the spirit of not looking at where the puck is, but where the puck's going, you have such an incredible …

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David Shifrin of Filament Life Science Communications is helping me by repurposing content I have generated over the last four years on my blog and podcast. I was lamenting to him that I had to …

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Audio holds unique advantages over other content types. This podcast is taken from a webinar where I discussed those advantages including the ability of audio to create exceptional engagement with …

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Earned media (coverage in a 3rd party publication) can be a valuable element in the overall marketing strategy for a life science company. And it may not require the services of a dedicated PR agency …

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You can use a survey to find out what fraction of your customers have a certain problem or prefer a particular solution. But if you want to know why they feel that way, you need to do some qualitative …

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The American Chemical Society uses content marketing to attract scientists to their products - journals, which contain more content. How do they do it? How do they persuade scientists to publish in …

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When you are hiring someone for your life science marketing team, do you want the best talent currently available (looking), or the best talent possible? Because the top performers aren't always …

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Can you recall your company's mission statement? Does it help you make decisions and guide your marketing efforts? Probably not. David Chapin, chief strategist and CEO at Forma Life Science …

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This is a replay of an episode from last year. I'll be back with a new episode and some very interesting guests in two weeks. You have an opportunity. It's in front of you every day. As a life …

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I pulled together these highlights from the last 7 months because they tell a story of how companies are marketing to scientists differently, from the skills they want on a team all they way through …

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Offering customers a lot of choices is a double edged sword. You almost certainly can provide the solution they are looking for - if the are confident about choosing the right one. If not, they might …

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How can you get your marketing message in front of a niche audience of scientists? How can you find them early in the buyer's journey before they even recognize a need? Contextual advertising lets …

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Innovation is an essential element of the life science industry. It can also be important for your career. Adrian Pencak shares examples of how adopting innovations has helped his career and how he …

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Many small contract research organizations (CROs) don't have a full time marketing person. But they might want one after they listen to this podcast. Olga Torres is the Director of Marketing at …

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A life science startup with a narrow portfolio needs to ensure that its sales team is only pursuing highly qualified leads. With a broader portfolio, you might be able to go after more leads …

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"Lots of good things can happen when you treat a customer right," says Alan Gerstein. While we'd all like to minimize customer problems, they are a natural part of doing business. You can't …

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Innovation is an essential element of the life science industry. It can also be important for your career. Adrian Pencak shares examples of how adopting innovations has helped his career and how he …

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Life science customers are evolving faster than we are as marketers. Hrissi Samartzidou is working to fix that. She is VP of Marketing in the Biosciences Division of Thermo Fisher Scientific. She …

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Do you need funding to move your life science startup to the next stage? Are you considering venture capital? If so, there are a few things those investors would like you to know before you make your …

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How do you establish a brand for a life science startup even before it has a product or customers? I was curious about this process so I talked to Karan Cushman, an expert in the branding of …

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Joe Whittaker is a marketing specialist at Horizon Discovery, but he's also the author of his own life science blog, personalizedgenes.com, for which he's grown an audience of over 14,000 people in …

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Are you a looking for a new job in life science marketing? Are you a life science marketing or sales manager seeking to hire someone for your team? What do you need to know about finding the best …

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When a customer does a search on your site, can she quickly narrow down the answers or will she have to sort through hundreds of documents to find the answer she is looking for? The challenge is too …

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Theral Timpson figured it out early and created a media channel after reading a book. Then he built a business on it. The book is Six Pixels of Separation: Everyone Is Connected. Connect Your …

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Storytelling is a word that gets thrown around a lot in marketing circles these days. But from a company perspective, what does that really mean? Why do we tell stories? And, as marketers, why do …

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This episode features highlights from my most popular and favorite episodes of Life Science Marketing Radio from the last year. I include short clips from: How to Change an Organization Through …

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Dale Yuzuki started his career as a high school teacher but discovered that the technology of life science was his true passion. Having had a variety of marketing and sales roles in the life sciences…

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Jeremy Schoales has an unusual background for a marketer in life sciences. He came to life science marketing after a career in automotive consumer electronics. In this podcast, he shares what he …

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In this podcast, Marilyn Cox of the Oracle Marketing Cloud shares a case study of how PerkinElmer used marketing automation in conjunction with their events to provide a better customer experience …

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In the first part of this series, I spoke with Guy Page of Pacific Biomarketing about how life science companies can take advantage of marketing automation to improve the buying experience for their …

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Maybe you are already using marketing automation and would like to use it better. Or you are just looking into how it might be helpful to your business and want to know how to get …

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When you have a life science startup based on a new technology, your marketing might begin with educating customers and investors about the biology behind your product. Static diagrams may not be …

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Are you marketing or selling large capital equipment like refrigerators, freezers, fume hoods where the operational expense, in terms of energy consumption, can be significant over the long term? If …

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Many life science companies are creating smartphone apps. Most of the those apps provide resources for scientists in the lab with the goal of keeping a brand top of mind or making it easy to find and …

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Social media can be overwhelming. Even if you are just keeping up with friends, right? Understanding how to take advantage of it as part of your life science marketing strategy is an even bigger …

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Imagine you are hosting a lunchtime seminar or workshop at an exclusive conference. Of course you'll record the session for on demand viewing at a later date. But what if you could stream the event …

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Is your life science company blog drawing the loyal audience you were hoping for? Do you want to write remarkable posts that raving fans share with their colleagues? Do you wish you had a proven …

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A digital transformation is not simply doing the same things that we've always done, except delivering messages digitally. It's about doing new things that weren't previously possible. And it's not …

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Smartphone and mobile apps can be found in everyone's pocket these days. I recently surveyed a number of life science companies about how they are using smartphone apps for marketing and sales. Among …

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How do you go about selecting a system? It could be adopting a marketing automation system, a CRM or even a new platform like LinkedIn as part of your marketing. There are a few basics that apply …

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There are few life science marketing tactics that can be considered a "must do". Remarketing or "behavioral retargeting" may be the exception. In this episode, Carlton Hoyt explains what it is …

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Are you neglecting an important part of your marketing funnel? You may be under pressure to to create content that will help close more sales immediately, but there is huge value to investing in …

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I'm always encouraging life science marketers to think about how they can get more people to share the load and contribute content for marketing. Eventually, without some guidance, that leads to …

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You have an opportunity. It's in front of you every day. As a life science marketer, written content is a part of almost everything you do. Brochures, advertisements, presentations, and video …

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Hamid Ghanadan wrote the book on marketing to scientists. Persuading Scientists: Marketing to the World's Most Skeptical Audience lays out his vision of content-centric marketing and provides a primer …

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Improving your marketing content or tactics isn't the only way to generate more leads and increase sales. The people on your team are likely to have the biggest impact on your success. Developing …

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Thinking about creating an infographic? Visual content is more engaging than straight text, and providing helpful information to your audience can be more valuable than an advertisement. I …

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I was recently a part of a spirited discussion between some scientists and marketers in the Analytical Instruments Professional Network Group on LinkedIn. It came about as a result of sharing this …

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A marketing communications team is often thought of as a service provider within a larger organization. MarCom tells the company's stories to the outside world. But it has the potential to do much …

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A marketing communications team is often thought of as a service provider within a larger organization. MarCom tells the company's stories to the outside world. But it has the potential to do much …

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If you are using video or considering it as part of your marketing mix and want to make sure you generate as many leads as possible, you'll want to listen to the podcast below. I sat down with …

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