cc: Life Science Podcast

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 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

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. 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

This episode is a double from my visit to the Advanced Lateral Flow Conference. Usability is Innovation: Atomo DiagnosticsAtomo 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: EAZEBIOI 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 HealthcareYing 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.” 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

The Future of Science Marketing: AI, Upskilling, and Human ConnectionI 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 activities2. Use structured assumption mapping to help R&D teams engage earlier without feeling they’re compromising standards3. Think of AI as augmentation rather than automation - it’s most powerful when amplifying human insight and creativity4. Focus on developing “power skills” that machines can’t replicate - deep listening, empathy, critical thinking, and pattern recognition5. Create regular “drumbeat” rhythms for market engagement rather than one-off initiativesThe 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. 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

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.” 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

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 needsNext 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.. 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

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 BiotechAnis 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 DevelopmentAfter 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 SupportHis 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 PersonalityThe 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. 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

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 OveramplificationNext-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 BreakthroughTraditional 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 AheadYann 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 ImpactBeyond 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. 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

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

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 MarketingTiffany’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 UpstanderTiffany 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 SeekersTiffany 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. 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