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. 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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
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 ProcessTraditional 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 customerYou 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. 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 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
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.Not subscribed? Let’s fix that. No spam, just good content wherever I find it.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. 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
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. 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
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
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 CodeGudrun 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.Not subscribed? Let’s fix that. No spam, just good content wherever I find it.The Tools Are Just Now Catching Up to the BiologyOne 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 DiscoveryThere 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 CompanyGudrun 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. 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
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 evolveFinally, 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 NoticingWild Card The Peregrine by J.A. Baker 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 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. 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
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.Not subscribed? Let’s fix that. No spam, just good content wherever I find it.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. 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
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.BTW, I hope you’ll consider joining me here: 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
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.Not subscribed? Let’s fix that. No spam, just good content wherever I find it.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. 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 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 SalespeopleMax 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 ProcessMaybe 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 EarlyOn 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.Not subscribed? Let’s fix that, shall we? Subscribe for free to receive new posts by email. (No spam. I promise.)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 PersonI 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 WayWe 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.I hope you’ll consider joining me here: 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