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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

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

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

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

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

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

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

I had the chance to speak with Petrina Kamiya, Global Head of AI Platforms and VP at Insilico Medicine, as well as President of Insilico Medicine Canada. Insilico Medicine is what Petrina calls a “tech bio”—developing both AI platforms and therapeutic assets, with a flexible model licensing both. Their pharma.ai platform was created to address challenges in drug discovery all the way from target identification to the clinic. In just a few years, they've gone from having two core products to a suite of about 12, all built with a heavy emphasis on validation.When I think about AI in drug development, I think about all the failures in clinical trials. I’ve always wondered: are the molecules themselves to blame, or is the reason for so many failures rooted in the aspects that surround their testing—like patient selection, procedures, or trial design? Petrina confirmed that the two biggest reasons for failure are safety and efficacy. Many failures are turn out to be preclinical issues—either the wrong target was selected, or the molecule causes unintended side effects. AI and machine learning are being used to better predict both, by identifying high-confidence disease targets and designing safer molecules.But predicting toxicity is still a major challenge. There are models at every stage—from in silico predictions to in vitro and animal models—but each layer adds complexity, and good data to train AI models is notoriously hard to come by. A lot of data around failed molecules never makes it into the public domain because it’s proprietary. That means valuable insights about toxicity are often lost, though some substructures known to be problematic are at least captured in public databases. I realize that companies need a return on their investment and even failure data has competitive value. But you have to wonder how much money is wasted chasing dead ends that could have been avoided.The other question I always have is about the mechanics of drug binding. Most approaches focus on the active site—the orthosteric site—where the protein normally interacts with its natural ligand. I asked about the possibility of other strategies like allosteric binding (where a drug binds somewhere else on the protein to inhibit function). Petrina validated that idea along with degraders, which are molecules designed to bring a protein into contact with the cellular machinery that destroys it. These newer modalities, including molecular glues, offer ways to selectively disable problem proteins without relying on traditional binding.Nothing is straightforward. Allosteric sites can offer greater selectivity, which could reduce toxicity. But finding those sites is incredibly difficult because proteins are dynamic and mobile. It’s not just about structure; it’s about motion within the protein itself and context.The body’s backup systems—redundant pathways, mutations, and rescue mechanisms—can undermine even well-designed drugs. This is especially relevant in oncology. Proteins like KRAS have so many variants that it’s not enough to design one effective inhibitor—you often need a panel of drugs to address different mutations. Petrina noted that the human body has many fallback mechanisms, which makes targeting disease pathways more difficult but also explains why drugs that seem perfect in vitro don’t always deliver in the clinic.Not subscribed? Let’s fix that. No spam, just good content wherever I find it.Getting back to clinical trials, AI is mostly being applied operationally right now—to optimize patient selection, identify clinical sites with the right patient profiles, and monitor for trial reporting issues. The big advantage is in stratifying patients to improve the signal-to-noise ratio. As Petrina noted, sometimes a drug works for a subset of patients, but that signal is lost in the broader trial data. That resonated with my previous interview with Kurt Mussina who used AI to identify ideal site locations based on logistics and patient demographics—a very practical, high-impact use of the technology.What if we could recover some therapies that have previously failed because it wasn’t tested on the right people? AI could help salvage and reposition those compounds by uncovering hidden signals in the data. You have to believe that improvements in AI will find a few lost nuggets—digging back through data with better tools to find value that’s already there.Developing therapies aren’t the only application for new molecule discovery. Insilico is also working with companies in the herbicide space, and as Petrina explained, discovering herbicides isn’t all that different from designing drugs for people. You still need target specificity, safety, and cost-efficiency—but at an even greater scale of production. If people or animals are exposed, or if the herbicide lingers in the environment, it has to meet a high safety bar.The unique challenge here is complexity and scale. It comes down to economics. We may spare no expense to extend a human life with doses in the milligram range. In agriculture, you’re looking for a simple compound that is cheap, can be produced in massive quantities, and can be stored in almost any conditions. It’s a new set of constraints.AI in discovery isn’t about magic. It’s about building better foundations—more accurate models, more validated data, and more thoughtful decision-making—to improve every step from discovery to clinical success.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website. 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 ran into Jackson Hyde, the CEO of Diaago, whom I had interviewed on Life Science Marketing Radio a few years ago at SLAS. Jackson showed me a new cold shipping unit and suggested I talk to Faizan Ahmed. That led to this conversation about his company, Invensify, and its innovative approach to cold chain logistics.With an electrical engineering background and experience in solid-state physics, he started his career in the defense industry, leading the development of a precision coordinate scanning system for night vision goggles, a project adopted by the U.S. Air Force. As you’ll hear, this experience shaped his entrepreneurial mindset, exposing him to various disciplines beyond engineering, including sales, marketing, and strategic planning, .Before Invensify, Faizan co-founded Genxsys, a company that developed a rain-deflector system for camera lenses based on centrifugal force. The product allowed photographers to take clear pictures in the rain or snow without interference. Within a short period, Genxsys secured a lot of orders and was rapidly acquired. This reinforced Faizan’s passion for identifying problems and developing innovative solutions.At this point, I’m struck by the difference of someone in life science workig on a single problem for years as opposed to an engineer who solves a problem and moves on. I know it’s not a fair comparison between trying to understand biology and applying existing knowledge, but I find it interesting. Are you subscribed yet? If not, let’s fix that.Faizan’s inspiration for tackling cold chain logistics came from a personal experience. Watching his diabetic dad struggle to keep insulin at the correct temperature while traveling, he realized there was a major gap in the market. The existing solutions relied heavily on ice packs, which required precise handling, refrigeration, and compliance with transportation regulations. TSA often discarded ice packs at security checkpoints, forcing travelers to find alternative cooling methods. This inconvenience and inefficiency led him to explore better solutions for cold chain shipping.As Faizan researched the industry, he learned that pharmaceutical companies still relied on Styrofoam boxes with ice packs to ship temperature-sensitive drugs. These solutions required significant manual effort, meticulous packing procedures, and real estate for refrigeration. The approach lacked reliability, with many shipments relying on overnight delivery to minimize temperature deviations. Additionally, the use of traditional compressor-based refrigeration was impractical due to power consumption and transportation restrictions on lithium-ion batteries.Recognizing these limitations, he and his team developed a thermoelectric cooling system that eliminates the need for ice packs, compressors, and refrigerant. Their solid-state cooling technology is far more efficient than conventional thermoelectric systems, thanks to advancements in material science. The Invensify system charges in five to six hours and maintains a stable temperature (2 to 8°C) for over 100 hours without an external power source. The battery is compact, fitting into a shirt pocket, solving the power and weight issues associated with traditional refrigeration methods.Beyond the cooling innovation, Invensify integrated smart tracking features. The system includes LTE, Bluetooth, and Wi-Fi connectivity, allowing users to monitor the shipment’s location and temperature in real-time. This level of tracking provides pharmaceutical companies with a level of assurance that was previously unavailable. Instead of relying on periodic temperature checks when a package changes hands, companies can now have continuous visibility into their shipments.The business case for Invensify extends beyond improving logistics efficiency. In addition to financial costs, there are broader environmental concerns, such as the non-recyclable nature of Styrofoam and the energy consumption of traditional cold storage methods. Invencify’s solution reduces labor costs, eliminates the need for large-scale refrigeration infrastructure, and minimizes waste, making it an attractive alternative.Faizan’s insights into the business side of innovation were particularly compelling. He emphasized that a great technological innovation alone is not enough—success comes from understanding and solving customer pain points. In this case, Invensify doesn’t just offer an efficient cooling system; it also simplifies logistics, enhances tracking, and provides a more sustainable option. The company’s approach streamlines operations by removing the complexity of handling ice packs and reduces liability for pharmaceutical companies by ensuring drugs are maintained at the correct temperature throughout transit.Finally we discussed funding and what it takes for a startup to secure investment. Faizan highlighted three key factors: the strength of the idea, the quality of the team, and the credibility of the founders. He credited his early career experiences for preparing him to navigate the startup world. Working at a small company allowed him to wear multiple hats and understand the full lifecycle of a product—from development to sales. By the time he launched Genxsys and later Invensify, he had built strong relationships with investors and strategic angels who believed in his vision. When he pitched Invensify, he was able to secure funding quickly, thanks to his track record and well-articulated business case.Of course, having a track record of success makes raising funds easier. For first-time founders, he stressed the importance of bootstrapping to develop a minimum viable product (MVP) and demonstrating a clear market opportunity. Investors look for disruptive solutions with large addressable markets, and startups must frame their innovation in terms of its business impact rather than just its technological novelty.He also underscored the importance of understanding not just the technology but the broader ecosystem in which it operates. Invensify technology has the potential to reshape multiple industries. Beyond pharmaceutical logistics, there are applications in vaccine distribution, particularly in regions with unreliable power grids. It could also be a game-changer for individuals who rely on refrigerated medications, ensuring they have a reliable solution when traveling or facing power outages. The broader implications of a solid-state, highly efficient cooling system extend far beyond what we discussed.Innovation happens at the intersection of technology, business, and human needs. It’s not just about inventing something new—it’s about making it viable, scalable, and impactful. Our conversation underscored the importance of thinking beyond the immediate function of a technology and considering all the elements that contribute to its success, from logistics and compliance to user experience and market fit.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it too. Please share it with them. 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

In this conversation with Elizabeth Chabe, CEO of High Touch Group and author of The Giant's Ladder: The Science Professional’s Blueprint for Marketing Success, we discussed a possible convergence between science communication and marketing. Reflecting on how few living scientists are household names, she talked about the importance of storytelling in transforming scientists into figures society admires even positioning them as rockstars or cultural icons. Their lack of visibility isn’t because scientists aren't engaging but because the traditional academic outlets they utilize don’t effectively reach the wider public. She sees an opportunity for scientists to break free from academic journals and allow their work to inspire future scientists and communicate value to society. Elizabeth noted the healthcare sector's medical affairs professionals, who engage deeply with scientific education yet seldom achieve fame comparable to cultural figures like Neil deGrasse Tyson or Bill Nye. The challenge, she says, lies in leveraging modern marketing tools to amplify these efforts effectively. We talked about how platforms, including YouTube, offer avenues for better engagement with the public and how scientists, through storytelling and proper marketing strategies, can expand their reach. Not subscribed? Let’s fix that, shall we? Subscribe for free to receive new posts and support my work.What does this mean for companies? You might say that science is a little bit on the back foot lately. There is a definite issue of trust even as more and more of our daily lives are made better and more convenient by the discoveries of scientists. This is a topic that has been on my mind a lot lately.Companies have an opportunity, and I would argue an obligation, to elevate both their brand and society’s perception of science. Elizabeth provided examples of organizations like Moderna. During the COVID-19 pandemic, Moderna focused on its broader mission of advancing RNA-based medicine. This strategic focus not only strengthened their brand but also helped reinforce trust in RNA-based therapeutics. That has likely opened up a whole new world of possible therapies but without trust, will they make it to market? Finally, where are the lines between science communication, education, and marketing and how can companies think about these activities to grow their business and, if you will, the market for science and scientific advances?Elizabeth has a framework for thinking about the nuances that I really appreciate. This segmentation—communication explains, education equips, and marketing connects—provides a foundational strategy for life science companies to build trust and competence and ultimately motivate action. Science communication is about making information digestible for non-experts, education builds understanding and competence, while marketing’s goal is to foster an emotional connection and drive action. Thinking long term, science communication not only helps the public to appreciate the work you do now, but feeds a pipeline to solve problems, possibly at your company, in the future. Education naturally follows to make that happen. As marketers we should take advantage of all of the above to create those connections, build our brands and create a public that accepts science, not blindly, but with real understanding.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

Last month, I went to Stanford and did four years of college in four hours. Jennifer Dionne has been on the podcast before. After showing me some amazing technology in her lab (nanoparticles - I’ll share some clips on LinkedIn later) we wandered over to the Polynesian Garden to talk about her class, the Science of the Impossible. I avoided the waitlist and got the Cliff Notes version, which was enough to fill my brain for the day.Our conversation started with her path to becoming a scientist (inspired by The X-Files) and ended with discussion of deploying remote sensors in the environment to understand shark populations around Palau based on detecting their DNA in ocean water.In between, we talked about the role media plays in sparking scientific interest, how she encourages students to think about big, difficult problems and the value of “curiosity-driven” research that can lead to unexpected discoveries, such as Faraday’s work with semiconductors and the accidental origins of chemotherapy. Oh yeah, teleportation was in there as well. Watch the video.In the class, they discuss scientific breakthroughs that were once thought impossible but also how to approach scientific problems that seem impossible now. What are the mindsets and the approaches that lead to progress on significant challenges?Jen suggests thinking of a conversation with future grandchildren. What do you want to say you contributed to the world they live in?So here I’ll follow her model and maybe take a step forward. We start by thinking of the problem we want to solve and then the aspects of that problem that make it difficult to address now. These are not all technical challenges. It often comes down to policy and infrastructure.Are you subscribed yet? If not, let’s fix that.I’d like to help build an infrastructure of public understanding for tackling long-term threats like climate change. This has been on my mind, especially since reading Fire Weather: A True Story from a Hotter World.As early as the 1970s scientists understood the challenge of global warming caused by CO2 emissions. It was neither polarizing nor controversial. But then, as now the perception was that there are more immediate threats - economic threats like inflation or unemployment, or physical threats of disease or geo-political conflicts that demand immediate attention.Humans are very good at identifying near-term threats and dealing with them as best we can. Long-term opportunities provide plenty of motivation (usually money) and don’t need much help. Long-term threats, not so much. Can we reframe those threats to become opportunities in a tangible and meaningful way?These opportunities are often called moonshots now, not just because of their lofty goals, but because of the inspiration they provide and the possibility of developing important and useful technologies on the way. One advantage for the Apollo program, besides national security considerations, was that every human being that ever lived has looked at the moon and wondered what it was like up there. The problem was relateable and easily visualized.Reversing climate change is certainly a lofty goal. But success is not easily visualized. Rather than spinning off multiple technologies that can serve other purposes, it will instead require the development of many new independent solutions that each contribute to the goal. Based on the work that Jen’s lab is doing on carbon capture and environmental sensing as well as the work of others, I have no doubt the technical challenges can be solved. That leaves policy and infrastructure.Solving climate change requires not just agreement within, but also between nations. Public understanding and trust in science comes back around to the media and storytelling.The stories we tell as science marketers and communicators, like Fire Weather, are an essential component of driving the policies that will enable the infrastructure required for success. We must continue to highlight the scientific advancements and give more visibility to the people that are doing that work. Let’s inspire the next generation and restore trust in science.In case you didn’t catch this on LinkedIn, here is some bonus content where Jen is talking about some mind-blowing uses for nanoparticles.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it too. Please share it with them. 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

Unlocking the Secrets of the Six-Base GenomeEpigenetics was somewhat vague when I was an undergraduate ( a long time ago). So I was curious to get an update on how we can investigate it more closely and what we are learning. I talked to Tom Charlesworth, Director of Market Strategy and Corporate Development at biomodal, a sequencing technology company focused on epigenetics. Tom explained how modifications beyond the traditional four DNA bases impact gene expression, development, and disease. What is the Six-Base Genome?Tom introduced biomodal as a sequencing technology company spun out of the University of Cambridge, focused on the interface between genetics and epigenetics. Their technology goes beyond the traditional four-base genome (A, T, G, and C) by adding two epigenetically modified bases: methylcytosine (5-MC) and hydroxymethylcytosine (5-HMC). This “six-base” approach captures critical modifications that play distinct roles in gene regulation.5-MC is associated with repressing gene expression, often keeping certain genes “turned off,” while 5-HMC is linked to opening chromatin and activating gene expression. Understanding these modifications provides a more dynamic picture of how our genes are regulated—not just by the sequence of DNA but also by chemical marks that change over time.Bridging the Gap Between Genetics and FunctionThe traditional four-base genome gives us an invaluable map of our genetic code, but it falls short of explaining how the same genetic sequence could lead to such diverse outcomes—from development to disease. Epigenetic modifications, like 5-MC and 5-HMC, offer another layer of regulation that’s essential for gene expression. Tom highlighted research that illustrates the value of this additional information. He mentioned the work of developmental biologist Emily Hodges, who uses the six-base data to study chromatin accessibility during neuronal stem cell differentiation. Emily found that early changes in 5-HMC could predict chromatin opening, an insight that would be invisible if one only looked at 5-MC. This kind of nuanced view helps us understand the precise moments when genes are primed for activation, offering a clearer picture of developmental biology.Applications From Oncology to NeurologyTom described three main areas where their customers are leveraging the six-base genome: fundamental research, oncology, and neurology.In oncology, there’s a growing recognition that multi-omic data—integrating genetic and epigenetic information—can improve cancer detection and treatment response. Tom shared examples of ongoing projects in Canada and Australia, where researchers are using six-base sequencing to better understand the complex dynamics of tumor evolution. By distinguishing between 5-MC and 5-HMC in circulating tumor DNA, they hope to pinpoint which DNA fragments originate from cancer cells, providing a more accurate snapshot of the disease’s state and progression.The six-base genome also shows promise in neurology. Tom explained that the brain is unique because it has an unusually high level of 5-HMC compared to other tissues, yet we still don’t fully understand why. Early research is exploring this epigenetic landscape to uncover new biomarkers for diseases like Parkinson’s, Alzheimer’s, and various brain tumors. The ability to profile these epigenetic marks could lead to breakthroughs in diagnosing and potentially treating neurological disorders.Are you subscribed yet? If not, let’s fix that.Epigenetics as a “Life Record”: The Developmental and Environmental ContextHere’s another way think about the six-base genome—as a record of a cell’s developmental journey and its responses to the environment. During early development, epigenetic marks guide cells down specific paths, setting up the blueprint for tissues and organs. But later in life, these marks are influenced by external factors like diet, aging, and environmental exposures. This can lead to changes in gene expression that contribute to disease, aging, or even resilience against external stressors.We also touched on how this concept applies to reprogramming cells, such as in induced pluripotent stem cells (IPSCs). When cells are reprogrammed, they don’t just revert to a blank slate; their epigenetic history still influences how they behave. Tom described work showing that successful reprogramming often involves restoring specific epigenetic marks, essentially rewinding the “epigenetic clock” to a more youthful state.Rethinking DNA as the Sole BlueprintTraditionally, DNA has been viewed as the ultimate blueprint for life. But the static genome represents only a portion of the story—it’s the interaction with the adaptable epigenome that truly dictates how our genetic potential is realized. The six-base genome isn’t just a scientific curiosity; it’s another tool for decoding the complexities of life.Tom describes DNA as the “possibility space” of an organism, but it’s the epigenetic modifications that trim and shape this space into the reality we observe. This nuanced view challenges us to look beyond the sequence and consider the rich layers of regulation that determine who we are and how we function.I am most excited to learn how environmental conditions like diet and maybe even experience influence the epigenome. As a bacterial geneticist, my basic model is substance A interacts with some regulatory protein to turn a gene on or off. I want to know how the epigenome records my environment. Do the conversations I have had leave detectable marks on the chromosomes in my brain? What would be the mechanism for that? Regardless of the outcome, it’s fun to see the ever increasing depth of our understanding of biology.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it too. Please share it with them. 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

A year ago, Mark Herbert, VP of Biopharma Business Development at Varda Space Industries, joined me on one of the most popular episodes of this podcast. Today, he’s back with some exciting updates on Varda's latest mission, which involved launching a satellite and conducting pioneering drug manufacturing experiments in space. From overcoming regulatory hurdles to making groundbreaking discoveries, Varda’s journey is a glimpse into the future of pharmaceuticals—and it’s happening above our heads.Launching and Landing: The Mission to SpaceMark began by describing Varda’s June 2023 launch, where they became the first company to send a satellite with re-entry capabilities on a SpaceX Falcon 9 rocket. Varda was one of 35 satellites on the launch, but the only one designed to return to Earth. After orbiting for eight months, the spacecraft re-entered the atmosphere and landed at the Utah Testing and Training Range. The mission took longer than expected due to the complexities of obtaining a re-entry license from the FAA—a groundbreaking process as they were the first to go through it.While in orbit, they reproduced terrestrial experiments using their custom-designed hardware. One of the key achievements was rediscovering a new form of ritonavir, a widely studied HIV drug, which had experienced stability issues in the past. This discovery and the successful replication of these results in orbit demonstrated Varda’s ability to conduct controlled pharmaceutical manufacturing in space—a major leap forward in drug development.Navigating Challenges: The Complexities of Space Re-EntryThe mission wasn’t just about science—it was also a complex regulatory and logistical feat. One doesn’t just bring a satellite back whenever and wherever you like.There is a lot of planning required for the re-entry, from coordinating with the FAA to clearing commercial airspace over the Western United States during their 35-minute descent. The spacecraft re-entered the atmosphere at Mach 25, a speed that necessitated strict safety protocols to avoid any conflicts with other air traffic.Varda’s spacecraft had to endure extreme temperatures during re-entry, reaching three times the surface temperature of the sun. The team licensed the protective shield licensed from NASA, allowing them to maintain a stable internal temperature throughout the process. This ensured that the drug samples remained intact and unchanged during their return to Earth—a critical validation for future missions.Small Capsule, Big Impact: The Benefits of Space ManufacturingThe whole purpose of manufacturing in space is to solve formulation challenges. In microgravity, Varda was able to manipulate ritonavir’s crystal forms in ways that are impossible on Earth. Beyond the chemistry, the technical and logistical challenges of this mission, honestly, blow my mind. The spacecraft’s small size belies the complexity: inside, the “huggable” capsule maintains the temperature within a one-degree range, even while moving from sunlight to shadow multiple times every day in orbit.To ensure they could isolate the effects of microgravity, the team included controls—different forms of ritonavir that were stable on Earth. This careful experimental design allowed Varda to confirm that the re-entry process did not alter the drug samples, proving that drugs manufactured in space could be brought back without compromising their integrity.Are you subscribed yet? If not, let’s fix that.Looking Forward: Expanding Horizons in Space-Based Drug ManufacturingVarda’s success presents new possibilities in space-based manufacturing. Currently, their focus is on small molecule crystallization. By 2025, Varda plans to expand into solvent-based applications, allowing them to test a broader range of small molecules. By 2026, the company hopes to launch biologics—complex molecules used in cutting-edge therapeutics that often face formulation challenges on Earth.Mark spoke about how Varda’s work could eventually transform biologics manufacturing. For instance, many biologics are currently restricted to intravenous administration because of stability issues tied to Earth’s gravity. Microgravity could help overcome these limitations, enabling new formulations that are more convenient and accessible to patients.Hypergravity: A New Tool for Drug DevelopmentHow does one determine that gravity influences the crytallization of any particular molecule? Draw the curve for the effect of increased gravity and extrapolate backward. Varda has developed a hypergravity platform at their El Segundo facility, which allows them to study the effects of increased gravity on pharmaceutical processes. By simulating up to 5G conditions, Varda is able to screen molecules and processes terrestrially, providing valuable data before investing in the high costs of spaceflight. This approach not only maximizes the chances of success in orbit but also adds a new dimension—literally—to pharmaceutical research.Hypergravity serves as a negative dataset, helping researchers anticipate how microgravity might alter their processes. By tweaking the “gravity knob,” Varda can better design experiments that leverage the unique conditions of space to create novel drug formulations.Future Vision: Monthly Missions and New FrontiersVarda’s ultimate goal is to conduct space missions on a regular cadence, with plans to have quarterly launches through 2026 and the potential for monthly missions if the demand arises. Their focus remains on pharmaceuticals, particularly small molecule crystallization and biologics. Varda’s platform is designed to make space accessible for drug development, offering new tools to researchers looking to solve problems that Earth’s 1G environment cannot.Beyond the immediate applications, Varda’s work represents a paradigm shift in how we think about drug development. As Mark pointed out, this technology could enable the creation of entirely new therapeutics that would be impossible under Earth’s gravity. It’s a thrilling prospect—one that could redefine the future of medicine and bring treatments manufactured in orbit into everyday healthcare.Final ThoughtsVarda’s journey is not just about the technology—it’s about opening up new possibilities for researchers and patients alike. As someone who grew up during the space age, I never imagined that some day, we could be receiving treatments that were made in space. This is just the beginning, and Varda is leading the way into a new era of drug manufacturing.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it too. Please share it with them. 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 first heard about hydrosomes, I honestly thought, “That can’t be real.” Hydrosomes are microscopic bubbles that stay in water without coalescing and rising to the surface. Then I met Nick Jackowetz, the Senior VP and Principal Scientist and the team from Hydrosome Labs at BIO 2024 in San Diego. They answered my questions and I invited Nick to be a guest on the podcast to share the story with you. Hydrosomes are also known as ultrafine bubbles, and they have incredible potential for many applications. If you’ve ever wondered how something as seemingly simple as a bubble could revolutionize fields like agriculture, cosmetics, and even fermentation, then this episode is definitely one to tune into.Nick started by breaking down the basics of what makes these ultrafine bubbles so unique. We’re talking about bubbles so small that they’re measured in nanometers—around the size of a virus particle. To put that into perspective, imagine a champagne bubble, which is already tiny to the naked eye. Now, pack a trillion of these ultrafine bubbles into that single champagne bubble, and you start to grasp just how small we’re talking about. It’s mind-boggling, right? These bubbles don’t even float like the ones we’re used to; they stay suspended in solution because they’re not governed by the same buoyancy rules. This leads to some pretty wild implications for how they can be used.Even the physics of these bubbles changes at such a small scale. For instance, the pressure inside these bubbles can reach up to 30 atmospheres, which is 30 times the pressure we experience in our everyday environment. This intense pressure doesn’t make them pop as you might expect; instead, it opens up new possibilities for gas delivery in various applications. Imagine being able to deliver oxygen directly to cells in a way that’s more efficient and targeted than ever before. Because the bubbles have an enormous collective surface area, believed to be charged, the team is looking at how they attract and move nutrients around. While the concept has been around since the 1980s, the science has only really taken off in the last decade. The early research mainly came out of Japan, where these bubbles were first studied in applications like agriculture and aquaculture. It turns out that these tiny bubbles can help grow plants more effectively by delivering nutrients and gases directly to the roots. Are you subscribed yet? If not, let’s fix that.I was curious to learn about potential applications. One area that’s particularly exciting is their potential in consumer packaged goods, especially in cosmetics. Imagine being able to deliver active ingredients like vitamin C or retinol more effectively into the skin without the need for added chemicals. That’s exactly what these ultrafine bubbles can do. By improving how these ingredients penetrate the skin, we could see a new wave of cosmetic products that are not only more effective but also safer for consumers.We didn’t stop there. The potential for these bubbles in the beverage industry is another game-changer. Picture your favorite sparkling water, but instead of regular carbonation, the drink is infused with ultrafine bubbles. These tiny bubbles could enhance flavor profiles, reduce the need for added sugars, and even change the overall sensory experience of the drink. Nick mentioned ongoing research into how different gases inside these bubbles—like nitrogen or nitrous oxide—could create new taste sensations and improve the mouthfeel of beverages. The idea that you could enjoy a sweeter taste with less sugar is not just intriguing; it could have significant implications for the health-conscious consumer market.For life sciences, the interesting application is in fermentation processes. These bubbles could play a crucial role in making fermentation more efficient, which is especially important as industries increasingly rely on fermentation not just for food and beverages but also for producing pharmaceuticals, enzymes, and other valuable compounds. The idea that you could boost the growth and productivity of cells in a fermentation tank just by adding these bubbles is something that could have wide-reaching benefits, particularly for biotech companies looking to optimize their production processes without the need for expensive new infrastructure. To be clear, it’s not just putting bubbles in the media. The effect, in addition to transporting oxygen, is enhanced by how the hydrosomes attract and transport nutrients.One of the most exciting projects Nick mentioned is a preclinical study on how these bubbles might affect the gut microbiome. Early evidence suggests that drinking water infused with ultrafine bubbles could positively impact gut health, potentially altering the microbiome in ways that benefit overall health. This could lead to a whole new category of wellness products that deliver health benefits just by changing the way water is consumed.Of course, there are still challenges ahead. One of the biggest hurdles is accurately measuring these bubbles, especially as they get smaller. The equipment needed to detect and analyze these tiny bubbles is still catching up with the science, which makes it difficult to fully understand their potential. But as technology advances, we can expect to see more precise tools that will allow scientists like Nick to push the boundaries even further.Whether it’s improving the efficiency of fermentation, enhancing the delivery of cosmetic ingredients, or even opening up new frontiers in drug delivery and gut health, ultrafine bubbles are something to keep an eye on. I’m excited to see where this technology goes next, and I hope to have Nick back on the podcast in the future to update us on the latest developments. I’m particularly interested in what RNA analysis might tell us about how gene expression might change in cells grown in hydrosome-infused media. Stay tuned. But for now, enjoy the episode. Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it too. Please share it with them. 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 BIO2024, I spoke Sam Clark, CEO and founder of Terran Biosciences, about their development of new long-duration dosage forms for the treatment of schizophrenia . We discussed the development of prodrugs, the potential of psychedelics, and the journey of founding a biotech company. The Genesis of Terran BiosciencesSam's journey into biotech was personal. Growing up around friends and family members with severe mental illnesses like bipolar disorder and Alzheimer's disease, he saw the limitations of existing treatments. Through his studies at MIT and Columbia, he recognized the slow pace of development and the significant side effects of available medications. Existing treatments for mental illnesses have many unpleasant side effects from cause weight gain to Parkinsonian symptoms and hormonal disruptions. All of that led to his decision to found Terran Biosciences hoping to transform the standard of care.Terran's PipelineTerran's lead asset, TerXT, is a novel combination of prodrugs of xanomeline and trospium, compounds that have been around for a long time, but with less than ideal pharmacokinetics. They also have Idazoxan XR, an adjunctive treatment for schizophrenia, and several new forms of psychedelics like psilocybin and MDMA with differentiated pharmacokinetics aimed at making these treatments more accessible and affordable.Sam explained the significance of prodrugs in their approach. Unlike simple reformulations, prodrugs are entirely new compounds created by attaching a side chain to the original molecule. This attachment improves pharmacokinetics, allowing for more effective absorption and longer-lasting effects. For example, the older compounds xanomeline and trospium, which need to be taken twice daily, have been modified into prodrugs that can be administered once daily or as long-acting injectables with multi-month durations. This innovation not only simplifies the regimen for patients but also leverages the FDA's accelerated 505(b)(2) pathway, potentially bringing these new treatments to market faster.Overcoming Development ChallengesCreating effective prodrugs is no small task. Sam described the extensive process, involving a team of world experts and over 200 FTE chemists working tirelessly. They designed over 10,000 prodrugs, synthesized 700, and conducted 500 preclinical studies to refine their approach. This massive undertaking, though challenging, has led to promising results.Are you subscribed yet? If not, let’s fix that.The Potential of PsychedelicsI also wanted to explore psychedelics, a field that has generated significant interest in recent years. Terran is developing new forms of MDMA, psilocybin, and 5-MeO-DMT, aiming to improve their pharmacokinetics and make these treatments more accessible. Sam highlighted MDMA's potential, currently under FDA review for treating PTSD, with a decision expected soon. (Right after we spoke, the FDA advisory panel recommended rejecting approval for MDMA. The decision has not been made yet.) By creating new forms and leveraging the 505(b)(2) pathway, Terran aims to overcome patent barriers and ensure these treatments are affordable.Insights into Brain FunctionI am particularly curious about anything we can learn about neurobiology from studies around these therapeutic compounds and psychedelics. Here is the challenge: Psychedelics, for example, act on multiple receptors. Teasing out different pathways in the brain is complicated. Functional MRI studies of people undergoing psychedelic trips show reproducible changes in brain pathways, suggesting potential mechanisms but the circuitry is complicated. There are no simple answers yet.The Journey of a First-Time FounderI asked Sam about his experience as a first-time founder. Terran's success is in large part due to its corporate structure, modeled after fast-moving Silicon Valley companies. By avoiding traditional hierarchical structures and instead utilizing a flat organization with world experts leading sub-teams, Terran has managed to solve complex problems efficiently.Team building has been essential to Terran's achievements. Sam's approach involves creating specialized teams for different facets of a problem, ensuring a comprehensive and collaborative effort. “Workflows” for the WinI have seen a pattern in several interviews recently. Changing a process can have as big of an effect on solving a problem (and creating success for a company) as developing a new product. In this case, it’s a bit of both. The problem being solved by TerXT is the patient regimen. Prodrugs with longer-duration pharmacokinetics make adherence easier for the patient. At the same time, I appreciate the enormous amount of development effort that went into creating those prodrugs. A different approach to assembling teams and managing them is also a significant change in the workflow that will have an impact.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it too. Please share it with them. 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

In this episode, recorded at BIO2024 in San Diego, I had the pleasure of speaking with Martin Brenner, the CEO and CSO of iBio. Our focus was the challenges and innovations in developing antibody-based therapeutics, particularly through their AI-driven discovery platform. Martin shared his insights into the current landscape and future directions of antibody therapies, touching on key aspects such as target selection, engineering challenges, and the role of AI in optimizing therapeutic antibodies.The Challenges of Developing Antibody TherapiesAntibodies have revolutionized therapeutic approaches over the past two decades, with numerous successful drugs already approved. However, as Martin pointed out, we've now picked much of the low-hanging fruit. The target space is becoming increasingly complex, with most approved antibodies focusing on a small set of targets. For instance, about 40% of all approved antibodies target PD-1. While anyone can now develop a PD-1 antibody, the real challenge lies in identifying and effectively targeting novel, more complex antigens.Another significant challenge Martin highlighted is improving the safety and therapeutic window of antibodies. Highly potent antibodies, particularly in oncology, can cause severe side effects. Enhancing the safety profile while maintaining efficacy is a critical area of ongoing research.Potency vs. Therapeutic EffectivenessIt turns out that the best-binding antibody isn't always the most effective therapeutic. For example, in bispecific molecules, where one arm binds to a tumor cell and the other to an immune cell, the tightest binding isn't always ideal. Overstimulation can lead to cytokine release and toxicity. Instead, finding the right balance in binding characteristics is crucial to avoid adverse effects.Traditionally, the goal was to find an antibody that binds quickly and stays bound indefinitely. However, this might not always be the best approach. Understanding on and off rates of antibodies is important for delivering the desired response. Novel technologies now allow us to screen for these characteristics early, optimizing therapeutic effectiveness and safety.Are you subscribed yet? If not, let’s fix that.iBio's AI-Driven PlatformiBio focuses on generating small, high-dimensional data sets to train their models. Their technology starts with an epitope steering engine, which creates engineered epitopes that precisely reflect the surface of target proteins. This innovative approach allows for targeted antibody development, even against challenging targets.For example, iBio can create PD-1 agonists that activate receptors instead of merely blocking them. This capability opens up a new realm of possibilities in antibody therapies, particularly for complex and hard-to-target proteins.Discovering New Biology Through TargetingOne of the most exciting parts of our conversation was discussing how iBio's platform not only targets known regions of proteins but also helps uncover new biological functions. By addressing the entire protein surface with engineered epitopes and screening them, iBio can identify antibodies that reveal new aspects of a protein's role. This approach not only enhances therapeutic development but also contributes to our broader understanding of biology.Smart Antibodies and MaskingMartin explained their concept of smart antibodies, which are designed to be inactive until they reach the disease tissue, like a pro-drug. This masking technique, particularly useful in tumor biology, involves connecting a mask to the antibody with a linker that is cleaved off by enzymes in the tumor environment. This method allows for higher precision in targeting and reduces side effects by ensuring the antibody is only active in the intended tissue.For example, targeting the epidermal growth factor receptor (EGFR) can be problematic due to its expression in the skin, leading to side effects. Using a masking approach, iBio can target EGFR in tumors while minimizing impact on the skin, potentially allowing for higher dosing and improved efficacy.Optimization and Rapid DevelopmentiBio's approach to optimization sets them apart. Traditional methods like phage display create large libraries of molecules but require significant time to identify and develop drug-like characteristics. In contrast, iBio uses machine learning to create localized diversity in a smaller, more manageable library. This method mimics the diversity of large libraries while maintaining high developability, drastically reducing optimization time from months to weeks.Focus Areas and Future DirectionsI asked Martin about what areas they are focused on with their pipeline. iBio is currently focusing on cardiometabolic and immuno-oncology areas. Their preclinical pipeline includes promising targets in immuno-oncology, with plans to partner these developments strategically. Additionally, Martin's background in diabetes and obesity research has driven their pivot into cardiometabolic diseases, aiming to develop drugs for those indications that avoid muscle and bone loss, crucial for the aging population.Other molecules, single chain antibodies from sharks or human heavy chain alone may eventually form the basis of new therapies for more complex targets.For me, the attraction of this approach is the broader look at the target molecules to survey all the possibilities beyond developing a small molecule that fits in a binding site and the benefit of everything we learn about biology that may lead to new discoveries in the future.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it also. Please share it with them. 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

In this episode of CC Life Science, I had the pleasure of hosting Neil Spooner, the founder and chair of the Patient-Centric Sampling Interest Group (PCSIG). Neil shared his insights into patient-centric sampling and its potential to revolutionize healthcare and clinical trials.Introduction to Patient-Centric SamplingNeil began by explaining the concept of patient-centric sampling, which prioritizes the patient's needs over traditional methods that often inconvenience them. Traditional methods like venous phlebotomy or standard urine collection are designed with the analytical labs, clinicians, and logistical chains in mind rather than the patients. For patients, that means they have to have to take time out of their day, possibly missing work or school, to visit a clinic for sampling.This is an added burden for patients, particularly those with chronic conditions requiring frequent testing. I shared the example of a family member, who had leukemia and needed to visit the hospital twice a week for tests. This was a significant strain not only on her but also on family members. Neil explained that patient-centric sampling offers a more convenient alternative, allowing samples to be collected at a time and place that suits the patient, whether at home or any other location.Benefits for Clinical Trials and HealthcareI was curious about what this approach would mean for clinical trials and healthcare. Neil pointed out that easier and more flexible sampling methods could improve patient recruitment and retention in clinical trials. It could also help gather data that is currently difficult to obtain, such as samples taken during a clinical event like a migraine. This approach not only enhances data collection but also broadens the patient pool to include those who might otherwise find it difficult to participate due to geographical or physical constraints.Current Research and Stakeholder EngagementBring this concept to life isn’t just about workflows and analytical science. Marketing plays a big role as well. And I don’t just mean promotion. I mean understanding the needs of everyone involved. Neil explained that the PCSIG is actively engaging with various stakeholders to understand their concerns and benefits regarding patient-centric sampling. They are doing market research to identify key stakeholders in different use cases, such as clinical trials, therapeutic drug monitoring, diagnostics, and drug testing in sports. By having conversations with these groups, PCSIG aims to educate and address their concerns while identifying potential benefits and gaps in the current system.Addressing the Resistance to ChangeOne of the significant challenges discussed was the resistance to change within the healthcare and clinical trial sectors. Neil ponted out the importance of finding passionate individuals within organizations who can champion the adoption of new sampling methods. These individuals need the support of their superiors and a network of like-minded professionals to overcome the inevitable hurdles that come with implementing new technologies.Are you subscribed yet? If not, can we fix that?Technological and Logistical InnovationsWe spent a little bit of time discussing sample formats and logistics. Currently labs doing routine analyses operate large analyzers that are set up for huge volumes of a standard set of tubes. Neil provided insights into the technological and logistical innovations required for patient-centric sampling. He mentioned various devices that can collect blood samples through finger pricks or from other body parts like the arm or thigh, often producing dried samples that can be mailed to labs. The COVID-19 pandemic demonstrated the feasibility of such home-based testing, showing that logistical systems can adapt to handle new sampling methods.Impact on Drug Testing in SportsI was surprised to hear about the application of patient-centric sampling in drug testing for sports. Chain of custody is crucial here to ensure the integrity of the samples. Neil explained that while athletes would still need to be witnessed during sample collection, blood sampling could be a more comfortable and less invasive (in terms of witnessing) option compared to urine sampling. Ultimately it’s likely to be complementary to urine testing. It does bring benefits for the athlete. It can make ongoing monitoring more practical for providing valuable data for athletes' training and health.Sponsorship and Future PlansFinally, we touched on the PCSIG's funding and sponsorship. Neil explained that the organization aims to keep sponsorship levels low to encourage broad participation, including startups and companies from less affluent regions ensuring that no one sponsor has outsized influence on the direction of the group. Sponsors benefit from visibility on PCSIG's platforms and involvement in the sponsors' advisory group, which helps shape the group's activities. Sponsors recently voted on nine proposed activities, and the top two priorities would soon be announced.Reducing the burden on patients needing frequent testing alone makes this effort worthwhile in my opinion. The benefits for recruitment and retention in clinical trials and drug/health monitoring in sports are icing on the cake.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it also. Please share it with them. 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 kept hearing about the use of organoids in clinical trials and elsewhere and was curious to know more. Luckily, I connected with Samantha Nicholson, the Global Technical Marketing Manager for Cell Culture at Millipore Sigma. She has a very cool job. Samantha is a hub, as she calls it, bringing together scientists to make progress in this exciting new area of research. She described her role, the applications of organoids, and their implications for future scientific research and healthcare.Organoids, as Samantha explained, are critical in basic research like organogenesis and developmental biology, offering insights into organ functions and disease modeling. Beyond that, their utility spans from drug discovery, where they aid in understanding drug effects and disease development, to pharmacogenetics and even regenerative medicine, potentially leading to breakthroughs like synthetic organs or alternative meat production.Organoids are not just a mix of cells from a particular organ, they mimic the structure and function of the organ itself. She gave the example of a colon and an organoid having a mucosal layer, an absorptive layer, and a muscle layer , derived from a specific subset of adult stem cells. This allows them to model diseases and organ functions more accurately than traditional 2D cell cultures.Perhaps most interesting is how organoids can significantly improve the inclusivity and diversity of clinical trials. Historically, clinical trials have suffered from a lack of diversity, often excluding women and other demographic groups. Organoids can be developed from tissue samples from diverse populations worldwide, allowing for a broader understanding of how diseases and treatments affect different demographic groups without the ethical and logistical complexities of human trials.We'll also be able to do patient stratification. So we're able to look at specific metabolic profiles or racial profiles or genetic mutational landscapes and thentest those drugs in those patients as a stratified process.So we can compare female and male, Caucasian versus African versus Middle Eastern, for example. And we can also start to develop patient-specific models. So we can take, for example, someone who has hereditary cholesterol and compare it to somebody who has developed cholesterol. And what does that mutational profile, differences in that mutational profile, what does that mean for those people?Are you subscribed yet? If not, can we fix that?As someone whose last job in a lab was studying host pathogen interactions, I got pretty excited when she told me about the applications in this area. Organoids may fill the goldilocks region between expensive experiments in small animals like mice and the limitations of 2D cell cultures with representing a single cell type. I could have used this 25 years ago!We briefly dove into process of creating organoids, starting from the isolation of stem cells from a tissue biopsy or through induced pluripotent stem cells. This involves cultivating these cells in specialized media to promote growth and differentiation, mimicking the natural growth environment of cells within the human body.Despite the promising applications, there are challenges in organoid technology concerning the variability and reproducibility of organoids. The size and shape of organoids can vary, which complicates their use in high-throughput screenings and other standardized tests. Achieving full functionality and maturation of organoids remains a hurdle, as they often lack certain cell types found in natural organs, such as immune or endothelial cells.When I asked her what is next in the world of organoids, Samantha was optimistic about their potential to democratize drug development and reduce reliance on animal models. She believes that advancing organoid technology could lead to more personalized and effective treatments, enhancing the inclusivity and ethical standards of biomedical research.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it also. Please share it with them. 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

Could bacteriophage be an alternative to antibiotics for Group B Strep (GBS) in pregnant women? GBS is a commensal bacteria, found harmlessly in the gut of some people. But it is an opportunistic pathogen that can cause significant disease - sepsis, meningitis, lung injury and bacteremia - in newborns exposed to it in the vaginal tract during birth, for example. Lucy Furfaro is an Emerging Leadership Fellow at the University of Western Australia in Perth. I spoke to her about her research in this area, how she became interested in the microbiology of newborns and their mothers, and the advantages of living in the most remote city on Earth.Lucy works at the King Edward Memorial Hospital, the referral center for all of Western Australia which covers an area approximately equal to the US west of the Rocky Mountains.What makes the hospital unique is that it hosts The Raine Study, the world's oldest prospective birth cohort, which has been collecting ongoing health data on mothers and their babies for 35 years. Preventing infection of newborns is done differently depending on where you are. The standard in Australia and the US is universal screening, typically a swab test. Expectant mothers testing positive for GBS in the vaginal tract (about 1 in 4) are given antibiotics pre-emptively. The UK and New Zealand take a risk-based approach (e.g., a history of infection) to determine who gets the antibiotic. While antibiotic resistance is not an issue of concern in GBS yet, we know that eventually it can be. Also of interest is what antibiotics do to the microbiome of moms and their babies. These concerns lead to the consideration of phage as a possible targeted therapy for GBS. At least a few challenges, both scientific and regulatory, remain to be solved.Are you subscribed yet? If not, can we fix that?Bacteriophage or simply phage are viruses that infect and kill bacteria. They are typically specific to a single type or closely related bacteria. Some are obligately lytic phages that infect a bacterium, replicate inside, lyse the cell and move on to the next bacterium. Others can hedge their bet, taking either the lytic pathway or occasionally integrating their DNA into the DNA of the host bacteria. These temperate phage might later be induced to lyse their host cells and move on. Ideally, phages chosen for antimicrobial therapies are of the lytic variety. But every phage found to infect Group B Strep so far is a temperate phage. That is either a sampling problem or an interesting biological question of why that is so.Beyond the biology are the regulatory questions. Are phage biologicals? They aren’t alive. However, neither is an engineered antibody, which is subject to a lot of analysis to confirm its identity. One possible solution is to avoid using intact phage particles. It involves the engineering of phage lysins, the enzymes that disrupt bacterial cell walls and membranes. These might be delivered in a topical cream to prevent infection at birth avoiding broad spectrum antibiotic resistance and causing minimal disruption to the maternal microbiome.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it also. Please share it with them. 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’m eating blueberries from Chile here in California, I assume that they arrived by air after being picked a couple of days ago. That isn’t necessarily true. Delivery by sea could take weeks from the time they are picked by the grower until they arrive on the shelf at my local grocery store.In this episode, I talked to Tristan Kaye, Director of Global Marketing and Business Development at It's Fresh about the challenges of shipping fresh produce across the planet while avoiding waste and spoilage. According to the UN Food and Agricultural Organization, up to 45 percent of all fresh produce grown is never consumed. For two reasons. One is food loss. So this is through poor infrastructure, lack of appropriate cold chain, mishandling these sorts of things, or food waste. Another significant challenge in the supply chain is controlling the levels of ethylene, which is a signaling molecule produced in plants for many things, including maturation and ripening. And it doesn’t take much to have an impact on fruit during shipping. …kiwi fruit can be sensitive down to four or five parts per billion. So to give that a sort of sense of context, a billion seconds is about 33 years. So it's lik if you're looking for ethylene in kiwifruit, that is the equivalent of trying to find five seconds of a 33-yearr period… But it fundamentally affects all of the elements in terms of the fruit and many vegetables that are developed.It’s Fresh offers an interesting solution to this challenge. We didn’t go deep into the chemistry of their ethylene control technology. It allows growers to pick fruit a little early and allow it to ripen slowly so that, ideally, it shows up on our local shelves ready to be consumed. Our conversation focused on all the other aspects of the supply chain that illustrate the challenge of getting fruit to market in a condition that consumers expect regardless of where they were grown:Growers get paid based on what arrives at the destination. They must decide when to harvest their fruit at some interval before ripening, yet they have no control over much of what happens or how long it takes before fruit arrives.Market pricing and seasonal demand influence the decision of whether to ship by air or sea.There can be tremendous uncertainties around the time spent in a warehouse at either end. Even shipping routes are facing uncertainty as there is a restriction on what can go through the Panama Canal due to a drought that has Lake Gatun at record low levels. Ships may have to wait in an anchorage at the canal, deliver some containers elsewhere or go around the tip of South America. Conflict near the Suez Canal, or the inability to access the Port of Baltimore might also be a factor right now.Damaged fruit produces ethylene as a stress response. To top it all off, there is ethylene in the exhaust of internal combustion engines. Warehouses that store fruit may use electric machinery like forklifts, but imagine the challenge of keeping motor exhaust out of your entire supply chain.The next time you grab a handful of blueberries grown out of season in the other hemisphere, give a thought to all the considerations and decisions that help preserve them from the moment of harvest to the moment you enjoy them.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it also. Please share it with them. 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

If you have a PhD in life science, are working toward one, or just considering it with an eye toward getting an academic job, the math is not in your favor. There are way more PhDs than the number of academic slots available. How that gets resolved with respect to your career was the core of my discussion with Ali Divan, Founder of Trulitica, where he is helping life science PhDs get into biotech. Don’t miss the SPECIAL OFFER at the bottom of this post.For many, there is a mismatch between expectations of what a career in life science might look like and where you end up working. But it’s not all bad. There are good jobs to be had. Just maybe not the ones you expected. Ali’s job is helping folks reframe their skills (and conversations) to open up new opportunities.A math problemOur discussion covered the challenge from several angles. PIs need to generate publications. Historically, that has been done in the process of training scientists who then go on to train more scientists in their own quest for publications.This has led to an oversupply of scientists looking for academic jobs. Entering graduate school now betting on an uncertain outcome eight years down the road (generously) is risky. But should you give up your dreams of doing science? No. The system is definitely ripe for change. At the same time, it’s important to be open to new possibilities. That’s good advice for anyone looking eight years ahead.We don't really walk in and go, “Yeah, I'm, I'm going to do some career planning. I'm going to figure out what I'm going to do.” Most of us, we go, “Hey, I'm pretty good at school. I should keep doing it.”Universities need to changeCheck out Ali’s article at the end of this post for details. Ali says some of them are aware:What I've seen when I started speaking to the deans of graduate schools at universities, they're very well aware of this. And a lot of them, what they say is, “You know, I think we just need to be a little bit more responsible at the time that graduate students are applying and beginning.We need to tell them what they're signing up for and what the landscape is” so that they don't show up thinking, as I thought, that if you just show up and be excellent and try hard enough, that's enough because (for) everything up to that point in your life, that was enough.The other challenge for PhD graduates is that university career centers are set up for undergrads. For a new PhD, your PI and whatever network you have created through conferences, your committee etc. is your career center. The problem is that the only job they can likely help you get is one that looks exactly like theirs. Because of the bottleneck or for other reasons, some people will decide to leave academia. But their training (they’re 30+ years old now) has not prepared them. The rest is up to youHow do you build a good life as a scientist? Isn’t that the real goal? Do good science, make discoveries, solve problems and enjoy all the other things life has to offer?What should you do if you had planned on a career as academic scientist and now need to look elsewhere? And how do you make that transition? How do you frame the skills you have in a way that’s relevant for employers? Here’s the good news: Ali says most of what you need is around strategy and communication, not hard skills. You’re only a few months away from being ready.The way that I help them is we first start out by sort of dismantling some of the practices that are that are so common and valued in academia. And so, as an example, in academia, it's highly valued to debate.It's highly valued to ask anytime you feel like you have a question or an argument. You just, you put it out. What I generally say is, well, in the industrial setting, when you don't have time, you have to have a very good reason for meetings. It's much more valuable to listen…That’s just one example of the difference you might find in industry.Focus on skills as opposed to topicsYou must realize that the people who will be hiring you probably don’t have a problem that your dissertation will solve. They have problems that require similar skills. Talk about those.The first step is networking. Ali also gives some great recommendations here. I could go on forever about this because there is good networking and bad networking. I’m sure I have been an instigator and a recipient of both types. No one enjoys it until they really understand it. But it doesn’t have to be uncomfortable. Be human. Build a relationship and don’t be in a rush to hand someone your resume. This is a valuable skill worth developing for the long haul. You had a long view when you started grad school didn’t you? I’d add that getting good at making conversation with anyone, is not only a good skill to have, it actually will bring you joy. I like what Ali said here: …so if somebody says something nice to you, and they're sincere, and they say, “Oh, hey, it looks like we also both study at this university, or I see you're a fellow immunologist… You know, my default answer, when I don't know anything, is cytokines. That'd make them laugh and they'll go, okay, who is this, who is this guy?My own perspectiveI find this whole topic fascinating. I went to graduate school because I didn’t look around enough to see the opportunities a bachelor’s degree would give me. I thought, “Who’s going to hire me?” My undergrad advisor founded a biotech with some of my other professors. I didn’t even ask them for fear of being laughed at. They wouldn’t have. It took me too long to realize that I wasn’t cut out for the bench. I feel fortunate to have eventually found positions using what I had learned that were scientifically stimulating, fun and rewarding. Personally, I enjoy a broader view of cutting-edge science as opposed to chasing a single thread to the end in the hope of a significant discovery. I also hope that the life science ecosystem (universities, funding agencies etc.) can evolve to help people find their path more quickly while maintaining the pipeline of PhD scientists we need to do basic research. Because beyond the bench, we need more science and appreciation of science in our communities. There are so many ways to use your scientific knowledge and skills. I promise that there is a job out there that you will enjoy. I only wish I had met Ali thirty-five years ago.SAVE 10% on the Trulitica Biotech Careers Course (Affiliate link valid until 5pm PST, April 30, 2024.) Use Code: LIFESCIENCEAnd if you’re in a hurry, you can hire Ali to work with you at Trulitica.How universities can prepare Ph.D.s for a changing job market.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it also. Please share it with them. 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

Reduce. Refine. Replace. These are the three Rs of animal research. The intent is to reduce the number of animals used, refine methods to be efficient and humane and replace animals with other models where possible.This cc: Life Science episode is sponsored content, courtesy of MediLumine.I talked to Stephen Marchant, Founder and CEO of MediLumine about the importance of animal research, how imaging in small animals is different from humans and innovations that support the 3Rs of laboratory animal sciences.    While the FDA no longer requires the testing of all new drugs in animal models prior to clinical trials, for some drugs, the requirement may stand. Animal research has been essential for many advances in human health and will surely remain relevant in the quest to discover new treatments in the future.As compassionate beings, we want to help our fellow humans whenever possible. When a child has cancer or a mother with a diagnosis of early onset Alzheimer’s tells her children that at some point she may not recognize them (or they her), no options will be left unexplored to look for and find solutions and those options likely include some research using animal models to better understand disease. The animal technicians and scientists working in laboratory animal sciences have a passion for developing therapies and treatments for human disease but also for taking care of animals. For those interested to know more, Stephen recommends the GetReal Podcast by Dr Cindy Buckmaster to truly appreciate the reality of this and what it is like to work with laboratory animals in the life sciences.In vivo imaging is used to better understand disease progression or response to treatment, and it is one aspect of research that isn’t likely to be replaced soon. The development of novel contrast agents allows scientists to visualize structures such as tumors or vasculature much deeper in the organism thus precluding the use of visual inspections and use of a caliper to measure tumor size. This breakthrough is built in to MediLumine’s tag line ‘Vision without Sacrifice’.      Imaging structures in a mouse, whether by MRI or PET scan is very different from imaging in humans. The structures are (obviously) much smaller. What I hadn’t realized previously is how the small size requires longer measurements to get the desired resolution. Typical contrast agents like CT contrast agents used in the clinic are rapidly cleared making it more difficult for small animal micro-CT systems to generate high resolution images with these contrast agents. Stephen explained how the development of contrast agents like Fenestra HDVC, allows improved imaging of mouse organs with in vivo micro-computed tomography (CT).Depending on the goal of an experiment, modalities like MRI or CT can provide good resolution which allows researchers to calculate, for example, the volume of an object such as a tumor. Other modalities, such as optical imaging, are preferred when sensitivity is important. Bioluminescent reporters can sensitively be detected in vivo with the trade-off being resolution.…with optical imaging, it's a very sensitive modality. So you might be able to see something at lower concentrations, for example, with bioluminescent imaging. If you look at some of the tumor studies, in some of the publications, we see even a few days after the injection of tumor cells, we're able to see signals, but we're not necessarily able to localize them very well. So, for example, if you have, let's say, a signal in the right lobe of the liver, you would see something coming with optical imaging, but you wouldn't necessarily be able to localize it and say precisely exactly where it is.Without these in vivo imaging methods, understanding the biology of tumor progression would require a larger cohort of animals, with a requirement to euthanize some fraction at various time points to locate tumors and measure their size. That’s the reduction element of the 3 Rs.Refinement is also possible. Stephen shared an example of how new contrast agents in microCT allow the study of fatty liver disease that couldn’t be done previously with terminal studies and histology.As for replacement, the development of organoids, small collections of differentiated cells, offer an alternative to some animal assays while more closely reflecting an in vivo condition than monolayer cell cultures. I’ll be covering that in a future episode.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.If you appreciate this content, you likely know someone else who will appreciate it also. Please share it with them. 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

AgBio, sustainability and DoE all come together in this episode. Tim Cuthbertson is the Chief Science Officer at VelociGro where they are using Design of Experiments to optimize plant growth media for vertical farming.I was curious to learn about the concept of vertical farming and how it can make an impact relative to the massive acreage involved in traditional agriculture. There are scenarios where it makes a lot of sense. First of all, greenhouse-grown produce is nothing new. Tomatoes are the most commonly grown crop in what is known as protected agriculture. And overall, in 2019, 55% of vegetable growers had some component of indoor operation, extension of the growing season being the primary reason. A greenhouse can produce 2.5 pounds of food per square foot per year. That’s horizontal growth. Growing plants vertically should increase that productivity further. So where is the impact? Consider what it takes to send blueberries from Chile to Alaska. Now what if blueberries could be grown indoors locally year-round? With LED lighting (which apparently doesn’t have to work on a 100% duty cycle) there could be significant savings in carbon emissions. Not to mention loss from spoilage etc in transit. In case you haven’t heard, the Panama Canal is backed up and the largest container ships can’t go through with a full load currently because there is not enough water in Lake Gatun due to decreased rainfall. That means produce either being offloaded elsewhere and sent by train or truck or a longer trip around Cape Horn and associated delays. Don’t miss my upcoming episode on “the ethylene problem”. We’ll talk about what it takes to keep fruit “fresh” on those long journeys.Sorry to interrupt. Not subscribed yet? Let’s fix that.Either way, I appreciate you spending time here.Local access to fresh produce in urban areas is another opportunity to deploy vertical farming. It occurs to me that a lot of empty office space is ripe (yeah, I said it) for conversion to urban indoor agriculture. I’m beginning to imagine a back-to-the-office campaign where a company leases some of its space for growing produce to be sold while allowing people who come back to the office to have access to a share of the crop to take home each week. Where does Design of Experiments come in? We covered DoE in a previous episode. Briefly, it’s a method of testing multiple variables simultaneously to quickly iterate and find the optimal solution to a problem or process. A typical one-factor-at-a-time (OFAT) approach makes all the results dependent on the optimal value of the first variable you test. That doesn’t in any way guarantee the best final outcome.How is VelociGro using DoE? We didn’t go into details about their products. Whether plants are grown on a substrate or in a soil-free environment, they need nutrients to grow. DoE allows their company of six people to iterate and optimize formulas for new products in as little as six weeks. Even if agriculture is not your field, you can see how DoE can save huge amounts of time in product or method development.It strikes me that once again, regardless of what area of the life sciences you work in, thinking about how things are done is as important for delivering a successful product as the science that goes into the product itself.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

Thomas Farb-Horch is the CEO of Thrive Bioscience. He has founded 18 companies. Seven of those turned out to be unicorns (sold at a valuation of >1 billion dollars).I was curious to know how he had identified so many opportunities correctly. BTW, Tom is not a scientist and has no advanced degrees in case you were thinking that was a requirement.He credits his success to being observant and inquisitive. That means keeping your eyes open for problems and asking why things are the way they are. The most attractive problem is one where people have been working the same way for a very long time. And if a process can be digitized, even better. As ever more computing power and storage capacity becomes available, more processes are in reach.Yet good ideas and smart solutions aren’t enough. Tom told me that every one of those unicorns came close to failure multiple times.How did he manage to dodge the bullet so often? One area where data and computing power won’t solve anything is our interactions with other people. To be successful as an entrepreneur, in addition to solving whatever technical challenges you have identified, you are still left to deal with customers, investors and board members. This is where Tom’s experience struck me.If you think reproducibility is a challenge in science, no amount of data or computing power can make humans more predictable.Getting people to change something that has been done the same way for decades is difficult. First for them to recognize the value and then to adopt new behaviors. Even early and late adopters won’t respond the same way. Your solution needs to appeal to both.At another level, while all your investors have a common goal of getting a return on their money, how and when they expect that to happen may be different. As you are likely to pivot at some point, it’s worth considering how you will keep them aligned on the new approach.The makeup of your board is critical and Tom has some essential advice on how you should negotiate their selection with investors. Listen to the episode for details. When it comes to what you are looking for, I’ll share one example here. Board members are sometimes (often?) selected for their name recognition as opposed to their domain expertise. Alexander Haig (former NATO Commander and Secretary of State) might have fit that description. Nevertheless, he brought value to the table in other ways. Tom told me that his skill at observing people and making sure everyone was heard to get to a result was off the charts. Given the roles I just mentioned, maybe that’s not so surprising. These skills are applicable everywhere.Board of directors is one of my favorite topics. It's so incredibly important. Many entrepreneurs don't spend enough time focusing on compatibility across the board. And kind of the profile of what they want.Every founder is likely to encounter a dark night of the soul moment. Tom said, “Fear is a terrible advisor.” It’s at those times when having chosen the right investors and board members will pay off. Who will stand by you and brainstorm solutions to see you through?Science is complicated and often difficult. Human behavior is even more so. It strikes me that in science, even if we don’t yet know the answer, we know it’s there and that certainty is comforting. I wonder if we shouldn’t spend more time thinking about how the people around us are going to affect our success and who we choose to do that.As an example of how humans can make an impact in our interactions, more than once over several conversations, Tom asked me, “How can I make this podcast successful for you?” I replied, “That mindset alone is all I need.” 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

Kurt Mussina is the CEO of Paradigm Clinical Research. Their model involves dedicated sites chosen for access to their desired patient and physician populations to participate in clinical trials. Access to historically underrepresented populations for both patients and healthy volunteers is a key requirement.One can imagine it takes a lot of effort to figure that out from demographic data etc. Kurt shared with me their approach using ChatGPT with some plugins not only for determining the best places to lease space, but also for qualifying and scheduling potential participants and determining which contracts to pursue based on their historical successes and current strategy.3 Applications of ChatGPT or AI:Where to lease and build out clinical trial sitesKurt and his head of clinical operations are based in Boise Idaho. The first requirement was to be able to visit sites without spending too much time traveling. He searched the website of the Boise airport for nonstop destinations that were reachable in a half day or less. That narrows things down to the western half of the US. They queried ChatGPT to identify which of those have, within a two-hour drive, populations with a significant proportion of people historically underrepresented in clinical research.For example, Chico California is one of those cities. Paradigm already has sites in Sacramento and Redding, which allows them to use the staff they already have on the ground and existing relationships to get a good start.Using AI chatbots to qualify patients and volunteers for studiesParadigm runs ads on Facebook to recruit potential participants. When a person visits the website looking for trials to participate in, rather than delivering a long list to browse, a chatbot will ask them questions about their age, background etc, to preview relevant trials and pre-qualify the person. It can then help schedule a phone appointment for further information and qualification.Thanks for reading cc: Life Science! Subscribe for free to receive new posts and support my work.Contract assessment and budgeting There are thousands of trials going on at any one time. Which ones does Paradigm want to bid on based on their patient populations, investigators, and desired indications?Paradigm uses Salesforce to manage their sales pipeline. A sponsor or CRO may send out a feasibility questionnaire. This clip from the interview explains how an AI, based on their previous successes, helps decide which studies they’d like to bid on as well as providing a range of cost estimates and contract terms. I asked Kurt, how they decided to take this approach to all of these important steps. It turns out the husband of a board member is pretty AI-savvy. Would you be as comfortable trying something similar if you didn’t know anyone with that kind of AI expertise? In a couple of years, no one will think twice about this kind of approach. As I see it right now, the real barrier is our own imagination in terms of what problems do we need to solve and how to ask the right questions. Many of the current examples we see are using AI to generate content - images or drafts of written content, or some data analysis. It might be helpful to think of ChatGPT and its “colleagues” as individuals you hire to do a specific job. In this example, it would be like, “Hey Joe, can you compile a report on cities we can get to easily that have historically underrepresented populations? When you are done with that, set up a web page to qualify and inform people interested in participating in a clinical trial. Oh, and then, take a look through our historical data and let me know which of our leads in Salesforce are the most promising.” Those are the jobs to be done. I should say that Kurt was very clear that they worked with people outside the company to get these tasks done. In the end, one can see how it improves efficiency at every step.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

Up to this point, I have resisted doing any episodes around cannabis because 1. I’m a little old-school 2. I probably don’t know enough and 3. I want to avoid, in the words of my guest, “being painted with green paint” and tainting the brand.Separating emotions from logic, however, if there are cannabis components that could be effective therapies, it would be foolish to ignore them. There is already one cannabis-derived compound approved by the FDA. Epidiolex is pharmaceutical-grade cannabidiol (CBD) prescribed for the treatment of seizures associated with Lennox-Gastaut syndrome and Dravet syndrome. Pebble Life Science is taking a rigorous approach to investigate whether other compounds derived from hemp might be effective as therapies, either for other neurological disorders or even cancer, initially focused on ovarian.I spoke with Patrick Moran, the founder and CEO of Pebble Life Science about their approach, the challenges they have faced, and the success they have had in forming collaborations with the MD Anderson Cancer Center as well as participating in the NCI Applicant Assistance Program.Everything we discussed is in the pre-clinical phase, preparing for and gearing up toward clinical trials. A key event in this journey was the 2018 farm bill that allows the cultivation of hemp as long as the THC content is below 0.3%. That opened the door to growing and extracting components from hemp, all non-psychotropic, for investigation.Thanks for reading cc: Life Science! Subscribe for free to receive new posts and support my work.Either way, I appreciate you spending time here.One obstacle was bridging the gap between (clinically unproven) claims of cannabis killing cancer and putting in place procedures to rigorously investigate those possibilities. Another challenge, as mentioned above, was breaking through the cloud of suspicion that exists around cannabis. After being invited to apply for a drug development grant by the Cancer Prevention and Research Institute of Texas, one reviewer labeled them as drug dealers.While the research staff took that hard, their legal team suggested taking their data and the positive feedback they had received from the other three CPRIT reviewers and contacting the NCI. That led to an NCI sponsorship for the NIH Applicant Assistant Program which Patrick said was invaluable in helping his executive team prepare to submit an SBIR grant to help fund clinical trials.Based on pre-clinical studies in mice, Pebble is currently focused on the potential of a hemp-derived compound as both an adjuvant therapy and a frontline monotherapy for ovarian cancer. At the end of our interview, I asked Patrick what he had learned that would be helpful to any biotech startup whether or not they are in the cannabis space.Interestingly, I’ve recently had another conversation with someone I hope will be on this podcast soon. We concluded that science is difficult. People can be more so. It’s yet one more challenge to get people to change their thinking or to deal with the obstacles they place in front of you, intentionally or not. I hope this episode help you figure that out on your own journey.There were a few terms I had to look up in our conversation. You may find these useful:RPPA analysisEntourage effectYour 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.0 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

This week, I talked to Dr. Michael Harman, an executive advisor, and consulting partner at Harmon Consulting about commercializing medical diagnostics, exploring various aspects from technology development to market trends and the integration of different scientific disciplines.I asked Michael about the process of transitioning laboratory technology into clinically viable products. He described a series of well-defined steps, starting from concept generation to prototyping and feasibility testing, eventually leading to a minimally viable product ready for market launch. It starts with identifying a gap in the market and scouting relevant technologies.Scouting is the process of identifying existing technologies that can be utilized to construct different subsystems of the proposed diagnostic tool. He used the analogy of assembling Lego pieces. While innovation can add value and is, of course, a little more exciting, it also increases risk.The engineering process of diagnostics involves bringing together various fields like industrial design, electrical and mechanical engineering, and crucial business aspects like sales and marketing. I didn’t know much about the world of diagnostics that lies between lateral flow tests like the ones we all use for COVID-19, and large analyzers running thousands of samples per day delivering results of multiple assays to your doctor.Michael noted a significant shift from centralized laboratory instruments to more compact, point-of-care devices, largely influenced by the COVID-19 pandemic. He highlighted the growing trend towards personalized medicine and home testing kits, demonstrating the evolution of diagnostic technology in response to global health challenges.This got me curious about the role of electrical engineering in diagnostics. So we took a little sidebar into the intricacies of technologies like thermocyclers for PCR. While heating a metal block seems straightforward, doing so evenly across 96 samples may not be. And I never put much thought into what it takes to cool that block quickly and where the heat needs to go. Needless to say, I have a new appreciation for electrical engineering beyond circuits and robotics.A key takeaway from our conversation was the integration of various scientific disciplines, such as computer science, biology, and physics, in developing new diagnostic methods. He mentions several innovative diagnostic projects he's involved in, such as non-invasive tests for endometriosis and personalized contraception compatibility tests. These projects exemplify the potential of predictive diagnostics to revolutionize patient care and treatment.There have been significant strides made in this field, largely due to the collaboration across different scientific domains. He emphasizes the importance of bioinformatics and the role of computer science in medicine, marking a paradigm shift in how medical research and diagnostics are approached. It also presents challenges:People don't always necessarily know what to do with diagnostic information either. That is a big challenge in terms of, okay, great. You've identified a marker now exists, but what is that now? How do you then inform the patient of or change their treatment based on that information?If you find this helpful, it kind of makes sense to subscribe, doesn’t it?Thanks for spending some time here, either way.As we often do, we discussed the challenges faced by academic founders in transitioning their ideas from academia to industry and the mindset changes required for successful commercialization. He notes that while academics are used to being highly independent and handling various aspects of a project, success in the industry often requires a more collaborative approach. Founders must learn to trust and leverage their teams, allowing each member to contribute their expertise to the project.Michael mentions the debate about the necessity of having clinicians or scientists in leadership roles in medical companies. While their deep understanding of the technology is beneficial, it can also be challenging for them to step back and allow others to handle aspects of the business they are less familiar with. This transition, from being an independent academic to a team-oriented industry leader, is crucial for the successful commercialization of medical technologies.Our conversation shed light on the complexities of commercializing medical diagnostics and highlighted the importance of interdisciplinary collaboration in driving innovation in this field.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 it comes to chemical reactions, if you can imagine it, somewhere out there a microbe is already doing it. This was something we used to say in graduate school. The challenge is finding that microbe among the billions that exist in environments all around us.Surehka Karudapuram is the VP, Commercial Operations at Isolation Bio where they are helping researchers solve that needle in a haystack problem. In this episode we talked about the what, the how and the why.Check this out:Isolation Bio specializes in high-throughput and automated isolation and cultivation of microbes. Surehka explains that Isolation Bio's platform consists of an instrument, consumables, and accessories that enable the efficient study of new microbes, their unique products, and their impact on the world.One could isolate many different microbes by diluting and plating extracts from your environment of interest on petri plates and then waiting to see what grows. Isolation Bio's technology allows researchers to perform massively parallel cultivation of hundreds of bacteria from various samples, such as soil or feces. This takes place in an array with over 6,000 nanoscale wells. I found it amazing enough to sort microbes into the wells. What blew my mind was the ability to then pick the desired samples out of those wells and transfer them to 96- or 384-well plates for further analysis.Incubating the array under specific conditions is the first step in screening for the type of bacteria you are looking for. In one example, the desired bacterium grew slowly and would typically be overtaken by other species. Creating individual isolates gave researchers the chance to find and cultivate exactly the species they were looking for.Thanks for reading cc: Life Science! Subscribe for free to receive new posts and support my work.Either way, I appreciate you spending time here.Microbiome research has evolved from observation and cataloging into studying actual biology. We’ve gone from metagenomics (identifying what's there by next-gen sequencing) to identifying the capabilities of bacteria and purifying compounds. We discussed various application areas, including human health, animal health, agriculture, and environmental sciences, where microbiome research and bacteria play a crucial role.Human health is a big area for our customers and the microbiome space and it's just so many kinds of diseases that are now being linked to the microbiome and then also getting to that point of that causation. I'll just use the example of drug response or immunotherapy response in cancer patients. There's a clear population difference between the responders and the non-responders.And now we're starting to see work where the bacteria from the responders are being isolated and then being used in mouse models and then again, down to the next step, which is purifying, you know, maybe from the supernatant, the molecules, and then seeing that that can enhance immunotherapy drug response.Getting back to “If you can imagine it…”, we discussed potential commercial applications of isolated bacteria, including the development of probiotics, therapeutics, and products for various industries. Surehka highlighted the possibility of bacteria as "chemical factories" that produce beneficial compounds and explained how synthetic biology can be applied to engineer bacteria for specific functions, such as producing biodegradable plastics.It’s an exciting time to learn about the connection between our gut microbiome and other aspects of human health. On the other end of the spectrum is the possibility of discovering useful new compounds or ways of synthesizing them in living chemical factories. Where do you see the biggest potential? Leave a comment.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

Rochelle Prosser is the founder and president of Orchid Healthcare Solutions, the company she created to consolidate cancer treatment information and improve access to that information. We discussed the difficulties in navigating healthcare systems and the importance of having comprehensive, scientifically-driven resources for cancer patients and caregivers.Rochelle is a neurotrauma critical care nurse with 30 years of experience. She has had her own journey in healthcare and felt the impact of cancer on both her husband ( a two-time survivor) and young daughter. She described the challenges of a family trying to stay together and making decisions for a daughter who was only beginning to experience life when she was diagnosed with a rare cancer at the age of four. She had this arbitrary, completely rare brain cancer and it took nine years to figure it out for her to find survival. And that's a long time. Most people can't deal with that. Marriages are lost, finances are ruined, but we remained intact.Although her daughter was put into hospice five times, Rochelle never gave up advocating for her. I was curious about how you persuade a doctor to try something new when your child is already in end-of-life care. Her advice was to try to always be collaborative. Doctors and nurses want to help. There is value in being persistent, but it’s also important to listen. Not every treatment is the right one. If the doctor says no, there is likely a reason. But that doesn’t mean you stop trying:And so I had to find a way. to politely and effectively navigate and communicate so that I could get to that next cure, to that next option. For me, 50 percent chance of working for two years until the next treatment was a better option than 10 percent chance on a conventional treatment.Thanks for reading cc: Life Science! Subscribe for free to receive new posts and support my work.Either way, I appreciate you spending time here.Based on genomic analysis, her daughter’s tumor was a mosaic of glioblastoma and DIPG (diffuse intrinsic pontine glioma). Imagine how complicated that sounds even to a healthcare professional, let alone anyone else. In addition to advocating for her daughter, Rochelle decided she would try to help others in similar situations.I felt the need to intercede in that space intentionally with what I knew and how to navigate. So this is why I started Orchid Healthcare Solutions. I created a cancer treatment library that houses all cancer treatments from soup to nuts. Everything that's out there that is scientifically driven in one place. One of the biggest pain points, being on the provider side, but also on the recipient and caregiver side that I found was there wasn't a place that had a unified place to go.It was really difficult to navigate to get information just to find out that knowledge. And I said, if there was one way that I could share my knowledge was to consolidate that, remove the silos so that you have effective and appropriate information sharing, and that will help vulnerable populations. That will increase knowledge and awareness and increase participation in clinical trials.Because genomics was so important in her daughter’s case, Rochelle feels strongly about the need for diversity in clinical trials to understand how treatments affect different populations. Representation in those trials is critical to advance medical science that benefits everyone. At the same time, she is very clear about the importance of informed consent and the conditions around consent for participation. Bottom line - we need more people to participate AND understand their rights regarding their tissues and data. That’s how we get to the end goal of more diversity and better understanding of which treatments will work for different populations.That is the only way to move us forward. We all must come together because where it works or is expressed in one, it doesn't work (in another), but we need to find out why. And when you find out why, it is that nuance of why that then can put protection and then advancement and an improvement in care overall for all of us. 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

Tom Pesnot is the Head of Medicinal Chemistry at Concept Life Sciences. I invited him to talk about AI and virtual screening in the drug discovery process.By way of review, Tom laid out the overall process of discovery. One needs to identify a target whose activity can be modulated in a way that is of course, relevant to the disease of interest. Most often we are trying to stop a protein from carrying out its normal function. Then we are looking for hits — interactions of candidate compounds with the target molecule. The quality of those hits are important. Typically, this has been done in high throughput screening using in vitro assays. This requires lots of compounds and lots of assays, making the process inaccessible for many. As you might imagine, it is very expensive with fancy robots etc.All of this provides the rationale for virtual screening because computers are becoming more powerful for predicting interactions between small molecule compounds and target proteins.Instead of starting with a compound collection (that few have access to), you start with a database. It’s possible to virtually make tens of billions of compounds in silico for screening. What blew my mind was the fact that they are only screening molecules that can be made in two or three steps from existing building blocks. Tens of billions! That means the time from identification to testing is essentially the time needed for shipping the constituent compounds.And of course, at the other end, you still need a model to recapitulate the proposed activity in vitro.AI is used along with known protein structures to see what molecules fit and how well in the target’s binding site. I asked about binding in other places that would affect activity. Ligand-based interactions are legitimate, Tom told me. For example, GPCRs (G-protein coupled receptors) elicit different pharmacology depending on where binding occurs, but AI has more impact in structure-based screening focused on active site binding.Thanks for reading cc: Life Science! Subscribe for free to receive new posts and support my work.Either way, I appreciate you spending time here.The big innovation is narrowing down the possibilities to test. The traditional brute force approach, even with AI, is to screen one compound at a time. This requires huge amounts of computing power. An AI-derived algorithm that tests the most likely candidates can accelerate the process 1000-fold.“And that means that because you're accelerating the process by a hundredfold or a thousandfold, then you don't need 10,000 CPUs. But you need 12 CPUs. And then you can screen billions of compounds using, you know, average Joe’s (gaming) computer and get that done in a week. So that's really one of the aspects where AI is having a huge impact on virtual screening. It means that even for huge collections, this process is accessible to small biotechs, to everybody.”While machine learning is working on making hits more relevant, false positives are a still a challenge. Many things need to work well for a drug to be approved. Safety, efficacy, solubility etc are all important.We’re not making virtual medicinesSo how many compounds from a screening will be tested in an actual in vitro assay? Tom says they might start with 500-1000 molecules. Then those are whittled down to 50-100.Then they make/buy them and do an in vitro assay.I’ve been curious about where we are in terms of AI developed drugs in the pipeline. It’s still early days with respect to approved drugs from discovery by AI. According to this article, as of August 2023, none are yet at the approval stage.One big problem, yet to be overcome, is that typically negative data are not published.“The problem is, We have a lot of positive data points, negative data points are not necessarily as available because we don't tend to publish negative data. Even though there are some channels to do that and the problem is to build and test and validate a machine learning model or any model, you need to have positive and negative data.”There are many reasons why a tested compound doesn’t work including a specific protocol or human error. Yet, I can’t help but wonder how much money and effort is wasted on testing compounds that have already been shown to be ineffective, but the data not shared.Worse yet is the fact that there are published papers with fake data written by AI which is a whole other topic.Maybe drug discovery is getting harder because we are getting to the proteins that are involved in more complex processes. But Tom points out that many targets that were thought to be undruggable have seen success. Ideally, AI will help us get there faster.My question for all of you: Where else might AI be applied to make drug discovery more successful, improving on the 90% failure rate? And is anyone working on that?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

Note: For this episode, because we are discussing the narrative capabilities of AI, I asked ChatGPT to write a summary based on the transcript of our conversation. I enjoy doing these interviews and consider myself a decent writer. However, it takes a lot of time each week to write a summary that I find minimally satisfying and acceptable. You deserve better and I can put my efforts to better use elsewhere or upgrading the whole experience here. I did lightly edit this to make it sound as if I could have written it. Let me know what you think in the comments.In this episode, I had the opportunity to chat with Matt Lewis, the Chief AI Officer at Inizio Medical. We dove into the world of artificial intelligence (AI) and its pivotal role in the field of medical affairs, particularly in aiding the commercialization of medical innovations. This conversation shed light on the remarkable ways in which AI can be harnessed to enhance decision-making, streamline data analysis, and shape the narratives around product launches.Introduction Inizio supports various players in the life sciences arena, including pharmaceuticals, biotechnology, medical devices, digital therapeutics, and more. Inizio helps these entities translate their scientific endeavors into compelling narratives tailored for a diverse set of stakeholders, from clinicians to regulators, payers, and patients.AI has been a significant player in the medical field for several years. Matt, with over a decade of experience in medical affairs and 15 years in AI, highlighted how AI first emerged as a solution to address the overwhelming volume of scientific data, including clinical research, published papers, and patient information. This surge in data presented a challenge as it exceeded the capacity of an individual to process effectively.Matt went on to explain how AI, particularly Natural Language Processing (NLP), was employed to sift through vast amounts of content. This enabled the identification of relevant terms and concepts that were crucial for strategists and scientists to focus on. It essentially acted as a tool for surfacing meaningful insights from the sea of information. The AI-driven lexicon analysis and scientific platform considerations played a vital role in ensuring that medical professionals could efficiently navigate the complex landscape of scientific data.The Role of Subject Matter Expertise in AIWhile AI is a powerful tool, it requires substantial input from subject matter experts. To effectively utilize AI, you need to define the key terms and concepts that the tool should focus on. In the medical field, this entails understanding the therapeutic area, specific indications, and relevant terms and vocabulary that are integral to the domain. Without this critical input, AI can't effectively sift through and categorize the data. It should be viewed as an amplifier of human expertise rather than a replacement for it.Crafting Effective Narratives with AIHow can AI be used to craft narratives that resonate with various audiences? Matt explained that in the past, narrative development was often based on subjective, qualitative discussions within multidisciplinary groups. While these discussions were essential, they sometimes lacked objectivity. The loudest voices or the strongest opinions often win.There was a lot of evidence, but sometimes the subjectivity and the qualitative nature of kind of what made sense of the organization kind of won the day, if you will. I think when we started moving into more of an evidence-centric, data-centric, AI-centric type of environment, those contributions are still there for sure, but they're kind of counterbalanced by more of an objective evidence-based approach…AI has transformed this process by providing an evidence-centric, data-driven approach. Instead of relying solely on subjective opinions, AI can analyze data to reveal how different narratives perform in the market. For example, if several competitors dominate a specific narrative, it might not be the best strategy to enter that conversation. AI can help identify unexplored "blue ocean" areas where the competition is less intense.Matt also highlighted that AI has evolved to provide real-time insights based on citation information, sentiment data, and relevant word associations. This dynamic approach allows companies to adjust their narratives based on changing market conditions and emerging trends. The ability to capture contextual intelligence from medical encounters, such as conversations between medical science liaisons and opinion leaders, provides valuable insights for crafting narratives. AI's role is not to replace human input but to augment it and ensure that strategic decisions are grounded in data-driven insights.Thanks for reading cc: Life Science! Subscribe for free to receive new posts and support my work.Either way, I appreciate you spending time here.AI and Drug RepurposingAI is also playing a vital role in drug repurposing. AI can help identify existing drugs that have the potential to be repurposed for new therapeutic uses. By analyzing vast amounts of scientific data, AI can uncover hidden connections and suggest novel applications for existing drugs. This approach not only accelerates the drug discovery process but also helps in finding treatments for conditions that were previously overlooked. The ability to sift through extensive literature and uncover these hidden gems is a game-changer for the pharmaceutical industry.The Data Sources for InsightsConversations between medical science liaisons and key opinion leaders are a primary source of the data used. These conversations are crucial for understanding the sentiments, opinions, and insights of experts in the field. Additional data sources include advisory board meetings, market research, and physician interactions with medical information customer centers.Currently, conversations are not typically recorded due to privacy and legal considerations. The information is likely captured in field notes, which are then input into Customer Relationship Management (CRM) systems. AI is used to analyze this data and extract insights, but the human touch remains essential in filtering and interpreting the information.The Future of AI in Medical AffairsThere is the potential for AI to capture not only the words spoken but also the tone and emotional cues in conversations. AI could help detect subtle nuances in conversations, allowing for a deeper understanding of sentiment. This level of emotional intelligence could be a valuable tool for improving customer interactions.The integration of AI in CRM systems is also expected to grow, providing more robust insights and streamlining the entire process. With advancements in technology and an increasing comfort with AI in the medical and scientific community, we may see a shift toward recorded conversations, enabling more comprehensive and context-rich analysis of customer interactions.ConclusionAI, when combined with human expertise, has the potential to revolutionize the way medical professionals navigate the sea of data and make informed, data-driven decisions. The future promises even greater integration of AI, enhancing the quality and depth of insights, and ultimately improving the medical and scientific landscape.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

Barry Goldman, founder and CSO of Pluton Biosciences introduces the concept of microbial cover crops as a new and innovative approach to improving soil health and sustainable agriculture. A plant cover crop e.g. alfalfa, is typically grown in the off-season and plowed back into the field to enrich the soil before the actual crop is planted. Barry and his team set out to see whether some bacteria can do this, particularly around nitrogen fixation, adding ammonia to the soil from the atmosphere. He points out that since the 1950s and 1960s the world’s population has gone from roughly 3 billion people to 8 billion. Some part of that is due to the use of synthetic fertilizers - ammonia made from the Haber-Bosch process. That has fed a lot of people. But that process creates a lot of greenhouse gas as well.Is there another way to add nitrogen to the soil that avoids undesirable side effects? When Barry and I were classmates and labmates in grad school studying Salmonella genetics, We had a saying. “If you can imagine it, a bacterium is already doing it.” Starting with a soil sample containing about 10,000 different species, the scientists at Pluton Biosciences have identified a consortia of bacteria that will grow in the absence of carbon and nitrogen except for what they can get from the air. The consortia work together using energy from the sun to reduce CO2 into usable energy sources (photosynthesis) and fix N2 to ammonia which can be used to synthesize amino acids etc. As an additional benefit of deploying microbial cover crops on a large scale for nitrogen fixation, it’s possible to sequester a significant amount of carbon dioxide from the atmosphere. "If you could now take this on a hundred million acres, you removed a hundred million tons of CO2 per year... you can start tackling this and give ourselves more time to come up with even better solutions. We also believe we can put on 30 pounds of nitrogen per acre. So now, if you're on that for that much, you're essentially almost turning the amount of the Haber-Bosch process to zero. That's roughly 20 percent of the greenhouse gases that are being emitted. You put those two together, now you have a massive impact on climate change." Not subscribed yet? Can we fix that?Either way, I appreciate you spending time here.What would it take the bring this potential to reality?Of course, like anything else in life science, safety and efficacy matter. These consortia need to be tested in the field. Because they are not genetically modified, the EPA would be satisfied to know that the constituents of the consortia have been identified and are typically present wherever they are intended to be applied.The second challenge is getting farmers to test the consortia in their own field (or a portion thereof). They will want some assurance that they would at least be compensated for any reduction in yield. And to be paid for their effort as well. Testing in real-world fields is crucial to prove that these microbial cover crops work as expected. This involves multiple phases, from starting with a few fields to expanding once efficacy and safety are demonstrated. Amazingly, the consortia create a visible crust on the soil. Similar to what we discussed in a very early episode of this podcast, drone technology and machine vision can be used to monitor the fields and gather data on microbial cover crop performance.Oh yeah. What’s the business model? Someone needs to pay for this. If the consortia works, the grower gets value from savings on synthetic fertilizer. There is also the carbon market. Right now that’s at $15-30 per ton of carbon sequestered per acre. Finally, does the soil improve? Does it result in better yields (more revenue)?Barry reminds us that this is not a complete solution. But microbial cover crops have the potential to put a significant dent in greenhouse gas emissions giving us more time to develop additional remedies for climate change.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.Intro Music stefsax / CC BY 2.5 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

Dr. Antonio Tito is the Founder and CEO of rEthix in Houston, Texas. rEthix is the world’s first Liaison Research Organization (LRO) facilitating clinical trials in Mexico and Latin America.A search of clinicaltrials.gov shows that several large pharma companies are currently running trials in Mexico. rEthix is leveraging the ICH (International Council for Harmonisation) guidelines to run these trials in Mexico and use that data to support IND-enabling studies in the US. The ICH sets the guidelines that the FDA and equivalent agencies in other countries follow. COFEPRIS, the Mexico Ministry of Health, assesses the laboratories. rEthix also prepares those laboratories to pass that assessment.One advantage is cost. According to Dr. Tito, the cost of a trial in Mexico may be 15-25% of the cost for a similar trial in the US.Another advantage is meeting your goals for testing diverse populations.While it’s common to run trials in Mexico, it is not common to start them there. …that is reflected only that only 3. 5 percent of new drugs are generated out of Mexico. And most of that has to do with communication. It's important that we have these type of channels, like the one that you are promoting, Chris, to teach people that it's okay to start your clinical trial in Mexico. You can approach the FDA about it. Be very transparent with the FDA always. But don't let the communication gap, not only the language, but also the culture… the paperwork is very extensive in Mexico.Don't let that stop you from generating data that you can later use for submitting to your investors and, obtaining more funding.Antonio also mentioned the opportunity to expand into Latin America with, for example, devices already approved in the US.For a 510K device that you already have obtained approval for in the U. S., You can easily transfer that into Mexico very simply because you have all the data that you've used, you’ve generated it to demonstrate that it works and is similar to other predicate devices out there in the market.And you've generated that information for your filing for the FDA. All that information can be then translated by our team and we can pass it on to COFEPRIS and the process is similar to the U. S. as well. But it's... You get the advantage of tapping into sometimes virgin markets where there is absolutely no other alternative to that device or to that diagnostic in Mexico or Latin America.So you have a winning hand in leveraging tactics to negotiate with, like commercializing agencies in those countries. Whereas in the U. S., you have more competition. It takes longer to get your market traction. So it's a win-win situation.Not subscribed yet? Let’s fix that right here.Thanks for listening to the podcast and sharing this post.rEthix is developing an app…Let's say you have a new discovery in your research institute, and you've received approval from your tech transfer office to take your technology out into the commercial markets and you have partnered with us to help you get your innovation out. We are, as part of the app, what it's going to be, it looks at all the data that you have, implements AI, And determines what is the best pathway in terms of the study design, the type of protocol that needs to be developed for better for commercialization for your device or your drug or your diagnostics. Until the app is ready, they are building an incubator in Houston at the medical center to connect life science companies to share ideas and facilitate access to data that will generate traction for IRB studies in Houston.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. 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

A new antimicrobial cured mice infected with bacteria deemed nearly “untreatable” in humans — and resistance to the drug was virtually undetectable.The World Health Organization has identified antimicrobial resistance as a major threat to global health. Bacterial resistance to antibiotics only increases over time. The problem is made worse by the fact that the incentives to discover and develop new antibiotics aren’t aligned with the pharmaceutical industry model. It takes billions of dollars to bring a drug to market and years to recover that investment. Sporadic 10-day prescriptions can’t compete with lifelong prescriptions for blood pressure reduction, cholesterol management etc. in terms of ROI. As a result, only one new class of antibiotic has been developed since the year 2000 and there are few new candidates on the horizon.In a previous episode, I spoke to Dr. Randy Rohde about methicillin-resistant Staph aureus and the importance of science communication in public health.In this episode, I talked to Mike Mahan, Professor in the Department of Molecular, Cellular and Developmental Biology at UC Santa Barbara. We talked about:* The challenges of developing new antibiotics and the need for new business models or societal incentives to pay for them* A supplement to the gold standard test for susceptibility that can lead to better patient outcomes* A promising candidate for a new class of broad-spectrum antimicrobial for which resistance is virtually undetectable Tackling the problem of antibiotic resistance will take effort on multiple fronts. As a society, we need to recognize the seriousness of the problem and decide to invest in the development of new drugs and models that can support that development. For example, a subscription model where companies are paid to develop and have antibiotics on hand whether or not they are used - a kind of strategic reserve. Jason Scharf and I discussed this in a previous episode.Improved Predictive Susceptibility TestFirst of all, are we using the antibiotics we have to our best advantage? Apparently not. The gold standard test for antibiotic susceptibility is done in rich media (ideal conditions for bacterial growth). If the test more accurately reflected in vivo conditions, would the same results be observed? Mahan and his colleagues have done the test. Comparing the results of the susceptibility test done in either rich or minimal growth media (closer to the host environment) with the ability of an antibiotic to cure sepsis in mice, in ten percent of cases there was disagreement between the gold standard test and the new test in terms of a clinical threshold: Is the bacteria resistant or susceptible? Using this test, we now check FDA-approved antibiotics that are dismissed by the gold standard test… there were several antibiotics that were highly effective in treating sepsis in mice that are never used by physicians because the gold standard test says it won't work. Consequently, our toolbox for antimicrobial infections is much larger than we once thought.A promising new class of antimicrobialIn a separate line of inquiry, conjugated oligoelectrolytes (COEs) were being investigated by a colleague for charging cellphones on the battlefield - a bacterial battery if you will, using bacteria and an energy source to drive electron transport. It’s no surprise that pumping electrons out of the cell for this purpose, rather than inward, is harmful to the bacteria in the long run. Because of this, it was hypothesized that COEs might be candidates as new antibiotics. Mike was skeptical. He thought that these compounds would be comparable to using bleach - great at killing bacteria, and very toxic for humans. “This is gonna be a really short collaboration,” he told his lab manager. Not subscribed yet? Let’s fix that right here.Thanks for listening to the podcast and sharing this post.They tested 17 different COE compounds for antimicrobial activity and toxicity in mammalian cells. All 17 had no problem killing bacteria. And most of them were highly toxic for mammalian cells, as predicted. But one of the 17, COE2-2hexyl, showed promise as being less toxic for mammalian cells. The next thing they did was immediately test this compound for its effectiveness at curing sepsis in mice. Mice were infected with a range of pathogens, including an isolate from a patient that had succumbed to refractory bacteremia - a multiply-resistant strain of Klebsiella from a community-derived urinary tract infection.They evaluated toxicity in mice via a blinded measurement of attitude scores (appearance/activity/clinical signs) as an outcome of drug treatment. The compound was well tolerated and able to cure sepsis in mice.However, the most remarkable observation was that resistance to this compound is virtually undetectable and it is effective against both gram-positive and gram-negative bacteria, presumably because it interferes with multiple membrane-based functions.Reflecting on this episode, beyond the obvious takeaways here about business models, improved testing and innovation, is the need to allow room for doing some things differently. I just learned this week that RNA editing is a thing and might be tested as a therapy ( I don’t remember for what) in clinical trials. This is a long way from what I knew about RNA, even in graduate school. But I was not surprised because remarkable innovations pop up every week in our industry. What is surprising is that a simple innovation that challenges a decades-old susceptibility test is met with resistance (no pun intended) because “that’s the way it’s always been done.” That resistance isn’t really a challenge about the science. It’s one of psychology - getting people to change their habits and ways of thinking. This has been a summary of the technical highlights. If you want the entertaining story of the scientific journey, give the full episode a listen. I think you’ll enjoy our lively conversation.Nature Medicine: How to Fight Antibiotic ResistanceYour 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. 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 enjoyed this conversation with Adrian Rubstein, founder of Ax3.bio, as he opened my eyes to different approaches to valuing startups. Make sure you listen to the full episode. I promise you will learn something valuable.Adrian inspired me to do some research on my own. So any errors in this description are mine. (A little knowledge is a dangerous thing). But let’s try anyway…Most biotech companies are destined to fail. That’s no secret. Biology is full of uncertainty. Outcomes in biotech are binary. A device or a therapy is approved for use or it is not, making valuations challenging. Even after approval, there is the challenge of gaining market share. It’s fair to assume, that growing the market for most therapies is not possible except by encouraging unhealthy behavior which is probably not part of your brand strategy.Adrian talked about understanding and evaluating the science in addition to assessing the size of a potential market. Ax3.bio employs a modified Real Option framework, modified for binary outcomes, for evaluating potential investments. This is way above my pay grade but I found this article from McKinsey helpful to get a sense of how this works. The article goes beyond using the framework for valuations to how it can be used strategically to understand the levers available to maximize value.If you just want the TL;DR, industries that require a lot of R&D, manufacturing and marketing investment can benefit from this framework. The example they give is drilling for oil and gas in the North Sea. Once a company has the right to explore blocks of the sea bottom for oil, they still need to figure out which ones might have oil, how much, and what it will take to get it out. All while the price of oil fluctuates over time. There is a lot of uncertainty at each step, not unlike developing new therapies. The model values the flexibility to make decisions about investment at each step while taking into account the possibility of changing market conditions.…as my economist friend says, “Models, they don't work it out, but they give you a compass on what may happen.” That's why we do sensitivity analysis and we say those are the different scenarios, right? The first one is that, okay, you get approval from the FDA, and then what is the probability for you to get acquired?The probability for you to hit a milestone? The probability that, okay, right now the KOLs like your product. What is the probability for you to get exponential sales? Or not. They're totally different scenarios and each scenario has a probability for it to happen. So that's a huge decision tree analysis. Not subscribed yet? Can we fix that right here?Thanks for listening to the podcast and sharing this post.As in the McKinsey article, this analysis can also be used as a strategic guide for the things you can do to raise the probability of success or a higher evaluation at each step. Many of these are familiar: Relationships with KOLs, publishing articles, letting people know about your progress and milestones through newsletters, podcasts etc. As has been mentioned several times on Life Science Marketing Radio, you can’t wait for approval to start telling your story. At that point, it’s too late.This got me thinking about the relationship between uncertainty and stories about a company’s journey over time. Many stories are based on uncertainty. Every athletic competition is a story because of the uncertainty of the outcome. And the more uncertain, the better. Presumably, each milestone on the company’s journey reduces uncertainty by some amount. This can be compared to a team’s progress toward a championship over the season. Just as you resolve one question, attention turns to the next victory (milestone) to be achieved. There are also individual stories within a team story that can be captivating. Every one of these milestones and individual stories is an opportunity to get people interested in your company. Would it be a stretch to say that stories themselves can increase the value of your business at any point? I don’t think so.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Visit Life Science Marketing Radio to learn more about how I help companies tell their stories.Ax3.bio Adrian’s Newsletter on LinkedIn, BioBusiness, 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’m not a healthcare expert by any stretch except as an occasional recipient of care that I’m generally happy with.As an observer, however, our system, in the US at least, looks fractured. Many people don’t have access to care. At the same time, significant innovations are racing along, but many physicians are likely too overwhelmed to incorporate new technologies like genomic testing. It probably feels like jumping on a moving train. Does that further increase the disparities in the system? How can we lower the risk and make it easier for doctors and healthcare systems to adopt advances like precision medicine to deliver better care?In this episode, I talked to Jeff Owen, VP of Marketing at Genomic Testing Cooperative about their business model and how they are trying to make comprehensive genomic testing routine and more accessible.There has been an explosion in biomarker-driven therapeutics.Yet, pathologists have expressed dissatisfaction with bringing genomic testing in-house, even with the best kits and equipment, seeing it as a moving target.The co-op model helps them keep pace by acting as a reference lab for systems with low test volumes, while guiding internalization, providing shared resources and education for higher-volume users. GTC manages the bioinformatics pipeline to simplify things further.This can help drive down costs and increase the consistency of testing and results. And drive a revenue opportunity.And a lot of pathologists are scared of next-gen sequencing because they think it's gonna take their job. And our company was founded by pathologists who understand that fear. But we also wanna show 'em maybe a different way of thinking about it, right? Because the next-gen sequencing is coming, right?…you're trying to stop technology that's coming. It's kinda like maybe a lot of people with AI right now, they're afraid. But this is the new tc/pc (technical component/professional component with respect to billing) The reason pathologists like the tc/pc split is because it makes, it allows them to generate revenue for their hospital, which is oftentimes one of the things that is important for their employment, so to speak.They have to generate a certain amount of money for their pathology department and the hospital to remain relevant… The margins are a lot better on next-gen sequencing than they are on some of the traditional routine pathology like immunohistochemistry.The output of this testing is a recommendation to pathologists and oncologists on the best therapeutic options based on the specific genomics of a tumor. Ideally, by making this more accessible and implemented sooner for each patient, the right therapy can be prescribed earlier, improving outcomes.Here is an example of how a business model can make a significant impact. I see a lot of life science or healthcare startups with innovative technologies or systems that are intended to improve patient care. But I see challenges around adoption and market penetration. The co-op model gets around these by offering different paths based on volume and the benefit of a network effect. As more systems participate, more data can improve recommendations while each member of the co-op can share in new IP generated along the way.GTC is conducting a Workshop, Chicago, September 23rdYour deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Visit Life Science Marketing Radio to learn more about how I help companies tell their stories. 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

For a patient with sepsis (an infection in the blood), the chance of survival decreases by 7-10% every hour. It’s important to quickly identify what bacteria are present and which antibiotics might be effective.Typically, there are very few bacteria in the blood. Culturing bacteria from a sample can take 12-24 hours and then one needs to test for drug susceptibility. Speeding up this process would save a lot of lives.Jen Dionne and her collaborators at Stanford are working on this problem using Raman spectroscopy. Through a combination of nanophotonics, acoustic bioprinting, and machine learning, they are developing methods to quickly and sensitively identify bacteria and screen for antibiotic susceptibility.What is Raman Spectroscopy?Raman spectroscopy is basically inelastic photon scattering. So if you think about having a laser or some other monochromatic light source, you shine that onto your sample, say onto a cell, like a bacterial cell. And the molecular vibrations in that sample basically add to or subtract from the energy of the laser source.You wind up with a fingerprint or a series of scattered wavelengths that are different from your incident wavelength. And you can use that spectrum to identify the constituents of what's in your sample.Raman spectra of complex mixtures appear as a wavy line, more like a snapshot of an oscillating jump rope than a series of distinct peaks that you would get from a pure sample of a small molecule.Here is what you need to know:* It’s possible to do Raman spectroscopy on whole cells. By training machine learning models on thousands of bacterial samples, Raman can identify different bacterial species and determine which ones are resistant to specific antibiotics.* Raman is typically not very sensitive but the efficiency goes up by the 4th power of the electric field strength. Surface Enhanced Raman Spectroscopy (SERS) using nanoparticles made of superconducting materials can focus light energy to a very small region without heating and destroying the sample, boosting the sensitivity. The added sensitivity allows the collection of more data (better resolution, more specificity). * Spectra can be collected in flight as droplets (of blood for example) are acoustically ejected at kilohertz frequencies and printed on a substrate. The identification of bacteria by the spectra can be confirmed by electron microscopy of printed drops on the substrate. Rapid diagnosis of sepsis is just one possible application. Analysis of environmental samples and wastewater epidemiology are also possible with this method.The takeaway for me is that with a large enough data set of samples, machine learning algorithms can identify subtle features that would never be possible for a human being. Adding more data through nanophotonics opens up even more possibilities to tackle bigger problems.More about SERSYour 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.Cover Image Credit (energy states): Moxfyre, based on work of User:Pavlina2.0, CC BY-SA 3.0, via Wikimedia Commons 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

Science is pretty cool. We can send astronauts to the moon, watch tv on a phone that fits in our pocket or rid the world of smallpox. It makes problems go away so well, it’s as if they no longer exist. That can be a problem in itself.In this episode, I talked to Dr. Rodney Rohde (Doc R) about the role of science communication in public health. To get warmed up, we had a conversation about the state of infectious diseases like rabies and MRSA (Methicillin-resistant Staph aureus).The incidence of rabies is on the way down (Yay, vaccines!) MRSA is on the way up (Yay, antibiotics?). Much of our current life expectancy can be attributed to the development of vaccines and antibiotics in the last century. These two examples show how, in some ways, we can become the victims of our own success and why science communication is still very important for public health.When my daughter was about five years old, she was bitten by a dog at a little league baseball game. The dog was new to the owners who were uncertain of its vaccination status. It was a stressful time considering the possibility of putting Ellie through a painful series of shots to avoid rabies, which might otherwise be fatal. Not subscribed yet? Can we fix that right here?Thanks for listening to the podcast and sharing this post.Fortunately because of our vaccination requirements, getting rabies from a dog bite is very rare in the US. One might assume that’s true elsewhere as well. One would be wrong. This is important information for travelers who might encounter an unvaccinated animal on the beach in another country. There is still a risk of rabies in the US, where the primary carriers are bats. Surprisingly, one can be bitten by a bat and not realize it, reaching into a woodpile, for example. Doc R shared this:And in many of these cases, you can look these up at CDC, there's some unfortunate ones, might have been a child… actually reported being bit by a bat. And the parents weren't aware of this rabies issue and they just kind of moved on. And then two, three weeks later, first symptoms… once symptoms start with rabies, you're pushing 98, 99% fatality. That is an example where science communication can save lives.Antibiotics present another success story that maybe we’ve learned too well. The overuse of antibiotics has led to resistant strains for which there are few or no effective antibiotics anymore. Can’t we just make new antibiotics? Let’s hope so. There are scientific and even economic reasons why that is more of a challenge now - a subject for a different podcast. But chasing the next cure is a never-ending game. This brings me back to the value of science communication.If you want to make an impact and save lives, you could look for the next cure for [fill in the blank]. Or you could help people avoid disease altogether. You might be able to develop a drug that will cure cancer. Maybe. And we should definitely try. But you can absolutely help someone understand and appreciate science. And that might actually save (many) lives someday.We live in a time where it’s easy to take aspects of our health for granted. One can look around and say, “No one dies from “X” anymore, why do we even worry about that?” The answer is “Because it wasn’t always this way and may not stay this way forever.”One might be able to say an antibiotic saved their life. They had a serious infection and the drug made it go away. Few people can say, “This vaccine saved my life.” Because they never got the disease and likely weren’t even exposed to it. But we know lives were saved. A lot of them. It’s just difficult to say whose exactly. Many of us will enjoy the privilege of growing old because of a disease we didn’t get. Thanks to a vaccine. Or an antibiotic. Or now, cell and gene therapy.I had the opportunity to interview Dr. Peter Hotez last fall at The Welch Conference where he spoke about the growing anti-science and anti-scientist movement. Every day on Twitter, people accuse him of being part of some huge conspiracy. I admire him for the example he sets. He calmly points out that all he has done is to create a patent-free Covid vaccine for distribution (nearly 100 million doses) in low-middle income countries. He is never rude or aggressive.Peter has also been a mentor to Rodney Rohde. I asked Doc R about how we can talk about things like vaccines with people who have this extreme level of distrust in science. His suggestion was to engage them and ask questions about why they think the way they do and just listen. You may not change many minds but building trust is important.We’re all on the same team and want to help each other. Let’s assume that much. Learning how to talk about science and have people understand is the first step and the best path is education. If you are considering a career in science or are looking to make a change within science, know that you can make an impact outside of the laboratory. It’s not as sexy as finding a cure for cancer. It’s not CRISPR and cell therapy. It’s the hard work of learning, thinking, writing and speaking. But you can save lives with a pen as easily as with a pipette.I really enjoyed this conversation and I’m pretty sure you will too. You’ll hear what a passionate and engaging science communicator sounds like. Make sure you give this one a listen.SciComm: Bacteria aren’t the only drug-resistant pathogens. A recent article from Doc R. And Thank You to Lemar Ashar for connecting us!Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. 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

What is the cost to an employer of chronic presenteeism, where a person is well enough to go to work but isn’t really productive? What is the dollar value to a patient of being married in terms of health outcomes? How do you figure that out? There are so many factors to consider. When we read that condition [fill in the blank] accounts for X dollars of lost productivity per year, I always wonder, “where does that number come from and who came up with it?” In this episode, we find out.Lemar Ashar, a previous guest on Life Science Marketing Radio introduced me to Mark Gannott, to talk about pharmacoeconomics. We explored the cost and value of medical interventions, particularly drugs, from various stakeholders' perspectives (patients, healthcare providers, insurance companies, and healthcare systems). I was curious about the challenges of estimating disease costs and treatment impacts, where the data comes from and how it’s used to make decisions.Genomics, including genome-wide association studies (GWAS), and polygenic risk scores also play a role, potentially improving health outcomes and reducing side effects. We touched on a few specific use cases, such as the treatment of endometriosis and the use of polygenic risk scores in depression. I found it fascinating to get a glimpse into how decisions around the development and use of different drugs are made. Mark thinks that in the future, a field called precision pharmacoeconomics will incorporate personalized genomics data to assess the cost-effectiveness of drug therapies. If you want a (sort of) quick intro into the topic, this is the episode for you. 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 went to SLAS this spring to talk to old friends, meet some new ones and learn whatever I could. I met Maggie Vantangoli, the Director of Marketing at Araceli Biosciences in their booth where we chatted about the use of artificial intelligence (AI) for high content analysis (HCA) in drug discovery and development. She was kind enough to join me on this podcast and fill in the (large) holes in my knowledge of cell biology. HCA is basically automated microscopy and analysis of fluorescently-stained (or otherwise) cells to identify changes caused by various compounds. This rich phenotypic information can provide valuable insights into how a drug or compound might work or whether it could be toxic.You can listen to the podcast to learn about how HCA is used to group compounds based on the morphological changes in cells exposed to them. A few things stood out for me. In terms of AI, the most interesting application was that of unsupervised learning, where the AI can learn to detect patterns that a human might not look for or even see if they were looking. One can imagine that a lot of information about biology could be uncovered aside from evaluating potential therapies.When I asked about where HCA might go in the future, Maggie talked about doing tests on organoids as a replacement for animal models. This is a topic that has come up in a few of my conversations lately on and off this podcast.I also asked Maggie what she thought about the possibilities for combining HCA with DoE (Design of Experiments) that I featured a few episodes back. Thankfully, she listened to that episode. (You should too.)I definitely think there are amazing applications here and you know, I think it's a massive amount of untapped potential, particularly in that high content space.I know that different aspects of drug discovery are getting there, particularly like the structure-activity type relationships. But I think this is a completely untapped market for the DoE type of type of work and there's huge amounts of applications because high content's also, you know, per assay, like most assays in drug discovery, there's cost associated there and that's not... When you're scaling up, that is not in insignificant amounts of money. So running millions or even tens of thousands of compounds a day with staining and all the liquid handling and tips and all of that is, is quite expensive. The amount put into that one little plate is extremely expensive.So you can kind of do your work ahead of time and, and utilize the Design of Experiments to stack the deck in your favor. Sorry to interrupt here, but you are subscribed aren’t you?I get a special joy out of when two episodes connect in that way. I’m going to see if we can get Maggie to come back with Markus to discuss the possibilities.I’d love to hear what you think of this episode or the podcast overall. Feel free to drop a comment.Also, if you want to talk about custom content for your life science brand, let’s chat. 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

According to their website, IQVIA holds over 60 petabytes (60 million gigabytes) of proprietary data used to provide insights and inform decisions across the healthcare industry. Think market dynamics around a disease, demographics and site selection for clinical trials or pricing for a new therapeutic.How does one pull the insights out of that mountain of data? Chris Steel was brought on board to drive AI and machine learning into all their products, standardize on platforms and unify the message. Our conversation went from things AI can do to how to manage AI projects across the enterprise. We talked about creating synthetic data to help diagnose rare diseases, wrangling multiple AI projects, and of course, the potential of ChatGPT.As I reflect on our conversation, it strikes me that AI broadly is very much like a child. (Keep in mind that I am very much a noob in this world and know just enough to be dangerous.) When you first get one, you have high hopes for its potential. You also have a responsibility to train it well.Diagnosing rare diseaseChildren learn a lot about people by observation. Similarly, a deep learning model can figure out on its own what relationships exist in a collection of data. Rare diseases are often difficult to diagnose (partly because they are rare). How can we identify patients with a rare disease whose diagnosis is currently uncertain?Training a model on a limited number of positive diagnoses is problematic. AI can be used to generate a set of synthetic data based on known positive cases. That data along with normal data is used to train a model that can then be tested. Finally, the model is used to identify patients with the disease that have been undiagnosed up to this point.That is pretty remarkable.Sorry to interrupt here, but you are subscribed aren’t you?ChatGPTIf you’ve been paying attention, you know that ChatGPT has also delivered some pretty remarkable results and its performance on professional medical and legal exams is stunning. At the same time, it can be a confident liar. In my own experience, I have seen it deliver scientific references that would be completely convincing if I didn’t bother to look them up and find out that they don’t actually exist.Chris agreed ChatGPT has a lot of potential. He also offered some important caveats. It can record your questions and whatever else you feed it - like your data. Don’t do that. Remember: if it’s free, you are the product. It could share that info with someone you wouldn’t want to have it. Again just like a child! Beyond testing the free version, get your own instance, be aware of the cost and have a business case because that computing power is not cheap. Chris kindly explained the difference in computing power between Google looking up the information it has indexed and ChatGPT delivering complex answers almost instantly on the fly, (and not paid for by advertising (yet?) How many projects?Avoiding duplication of effort across teams in a company as large as IQVIA is a challenge. Chris needed to know who was doing what with AI when he came on board. He asked people to share their projects but didn’t get a lot of response. So he took what he got, put it in a spreadsheet… And then in the virtual team that I've mentioned where we have all these leaders… I plopped up the spreadsheet and I said, “Here’s what people are doing.And look, you know this team is doing this and this team is doing that. You know, these guys are the leaders.” And suddenly right after that, as you can imagine, everybody starts dumping all of their projects on me. A lot of them we had to sort of weed out because they actually weren't really AI/ML related, but yeah, turn it into competition and then they are willing to share.There is your management tip for the day. When you want people to share projects across teams, make it a competition. This all has me thinking about what the data ecosystem of the future will look like. Where is the dividing line between companies that collect and analyze data for themselves and large repositories that sell the insights to multiple customers? Let me know what you think in the comments.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. 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

Early in our education about science, we learn that to understand what is happening in a system, we can only change one variable at a time. That seems reasonable. By doing that, we can see which variables matter. It turns out that this is not only slow, but in biology, possibly incomplete. If there is a two-factor interaction (not uncommon) you will miss it. The good news is that it’s possible to analyze many variables at the same time and understand which ones matter. One can also see the interdependence of multiple factors. Markus Gershater and Claes Gustafson joined me to talk about Design of Experiments and how it can be used to understand and optimize processes with multiple variables. …particularly with biological systems, often the best setting for a particular factor will depend on the level of another factor, right?This is called the two-factor interaction. And when you are only investigating one, each factor in the isolation of all of the others, you'll never see those. … a fundamental feature of biology is this kind of interaction and you'll just never see that doing one factor at a time. - Markus GershaterAs I think about it based on my own experience, a long time ago in a galaxy far away, a lot of academic science was focused on understanding one narrow slice of biology. (Is this gene important for pathogenesis?) Scale and automation had not yet entered the picture. I’m not sure I even imagined it.But in this galaxy now, there are all kinds of biology being done at scale. Science can be done faster, but scale can also be more expensive. It makes sense to optimize processes, not only to produce a better product but also to reduce the cost. Design of Experiments can do both. You can use it to make a better antibody, enhance the yield of an enzyme and/or reduce the cost of the media used in either of those. The magic of DoE is how we can get the most information from the least data. Sorry to interrupt here, but you are subscribed aren’t you?Interestingly, we don’t need to test every value of every variable. If you have two values for six variables, 26 is 64 but you don’t need to test 64 combinations. Sixteen may be enough to see what’s important (because math) and then you iterate to hone in on a solution from there.In some (many?) cases, you don’t need the best solution, you need one good enough to commercialize, e.g. an antibody with a ridiculously low Kd . …if you just take the simple example of an antibody, you wanna make sure it's, it, it certainly binds to your target at the Kd that makes it relevant. And you wanted to make sure that it can be produced at a titer that is high enough in your CHO system and you wanna make sure it has a melting temperature that is above a certain degree and you wanna make sure it doesn't aggregate at a concentration of x… I mean, who cares if it binds? What you truly care about is, does it shrink the tumor? - Claes GustafsonWhile much of this may be new to biologists (who don’t like math), this is chemical engineering 101. It can be used to optimize microwave popcorn or your route to work. (Listen to the interview). My marketing friends could use it to optimize variables in an email or on a landing page. Believe it or not, this concept is close to 90 years old. Now would be a good time for more biologists (and popcorn lovers) to take advantage of it. It’s also an awesome time to share this podcast with your colleagues. Thanks.Markus Gersahter is the CSO and Co-Founder of Synthace.Claes Gustafson is CCO and Co-Founder of ATUM.Conversations are fun and your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. 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

Because most of us have likely had a Covid test done in the last few years, you might think that getting diagnostics to market is a straightforward proposition. But you’d be wrong. The reason is that even if you have a clinically proven test, there are no guarantees that someone will pay for that test. Further, there is no standard by which diagnostics are evaluated that leads to reimbursement. Hannah Mamuszka is the CEO at Alva10. She explained to me the market dynamics around developing new diagnostic tests and how she and her team are working to make it easier to get new ones developed. When Covid tests were first approved, the reimbursement was less than the cost of making them, accounting for some of the delay in accessing them.Just because a test is approved by FDA or CLIA, doesn’t mean it will be paid for. In order to get payment, you have to go through the American Medical Association to get a code, which is essentially an alphanumeric set of numbers and letters that identify your test, and then you have to go and apply for what's called coverage which is determining who's gonna pay for your test. And there is no standard of how much evidence, what kind of data you have to present with your test in order to get it covered. It's just submitted and it's kind of a crapshoot which ultimately means that it usually takes on average diagnostic tests about seven years before they're paid for.And most companies can't survive for seven years without getting paid. As most companies can't survive. I mean, it's not limited to healthcare. You know, if you don't get paid for seven years, you probably don't exist anymore.Every modern drug is rationally designed. We know the pathways and the intended targets. But without diagnostics, for example, to determine whether a treatment can work, a lot of time and money is wasted. The overall success rate for approved drugs is about 36%. That means not only do we waste money on prescribed therapies that don’t always work, but in the meantime, patients may also be declining, adding costs.I am no expert on the US healthcare system. Far from it. But while many are trying to innovate, for now, we play the hand we’re dealt. I wanted to know how would diagnostics improve overall care and what is the path to making that happen?Pharma companies want to claim as big a market as possible to make money for shareholders. Segmenting the population based on a diagnostic that can predict success is a tradeoff between market size and efficacy. You can see that the incentives are misaligned.The leverage would seem to be with payors. They don’t want to waste money. If they had economics and science in front of them, they could drive coverage toward more effective treatments, couldn’t they? It takes time and effort to bring these insights to you. Would you be willing to bring a subscription to me?Hannah’s experience here is informative as well as an interesting study in psychology. We take all of those clinical changes and we, we translate them all into numbers and then figure out how the payors are gonna see it, how much they're gonna value it, and then we show it to them strictly from an economic perspective first.And when we show them the economic perspective, the first thing they ask for is, “Oh, well, you know, we need to see the clinical evidence”, which we immediately give to them. But I can tell you from a lot of experience trying to go the other way and showing them clinical evidence and then wanting to talk about economics, I mean, I essentially got nowhere. So the best approach to aligning incentives seems to be economics first, science second. I asked Hannah if there were healthcare systems in other countries that we could learn from. The US FDA approves drugs based on safety even if they might only benefit a few patients. Here again, the incentives are misaligned. Other countries would like to identify those few patients before approving the drug for use. But a diagnostic to find those few might exclude a large number of patients, making the economics of that drug unfavorable on the whole.Economics has been called the dismal science. But understanding and aligning incentives for all the parties in our healthcare system may be more challenging than the science of bringing new diagnostics to market.Conversations are fun and your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. 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

Imagine a capsule whizzing by some 200 miles overhead. It’s just big enough to hold a medium size dog (curled up and sleeping) but there is no life onboard. Instead, there is an automated laboratory designed for manufacturing pharmaceuticals. That is the vision of Varda Space Industries. Do they really envision a future where drugs are manufactured in space at scale? Yes. I talked to Mark Herbert, VP of Biopharma Business Development at Varda, about their plans. My two big questions were 1. What is special about microgravity for this application? and 2. Why does pharmaceutical manufacturing makes sense economically?Lifting payloads into space isn’t cheap, although the price/kilogram is coming down. On a per-gram basis, pharmaceuticals are one of the more valuable things you could make, so at some point, that can become profitable. And the reason microgravity matters is that in the vacuum of space there is no convection. That affects how crystals are formed. Experiments on the international space station with Merck’s cancer immunotherapy, pembrolizumab (Keytruda), show a more uniform particle size distribution and reduced viscosity. That has implications for how it can be delivered to patients. Pardon the interruption. You are subscribed aren’t you?The science is pretty cool. But when I reflect on a project like this, I wonder how a project like this comes together? Sixty-five years of space exploration is part of the foundation, of course. That inspires the next generation in terms of rockets, working in microgravity etc.What stands out is the vision it takes to make it a reality. First, there is the imagination of the end state. What do we want to achieve? What brings that to fruition is the ability to imagine and execute all the steps in between. It’s a special skill to be able to put all of that together, convince others that it’s worth doing and meet the rigid timelines of a launch schedule. Because they’re not delaying the launch just because you forgot to pack a key item for the trip.Epic projects like this one and the de-extinction of the wooly mammoth we talked about last week are not only inspiring, they are both essential and inevitable. At some point, we can’t not try. And when that happens, human beings find themselves capable of achieving what was once thought to be impossible.Gordon Cooper knows what that feels like:The interviews with my guests are the highlight of my week. Listeners seem to enjoy them too.Conversations are fun and your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. 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

My first reaction when I heard that George Church wanted to bring back the wooly mammoth was, “Uh, why don’t we stop trashing the environment and save the species we have left?” Later on, I learned that I may have missed the point. It turns out that as engineers of the environment, wooly mammoths might enhance the carbon storage capacity of the tundra and help us all chill out a bit (slow climate change). That covers part of the why question but not all of it. This is a BIG science project so there is a lot more to it.I talked to Alexander Titus (he goes by Titus) from Colossal Biosciences to learn what it will take to de-extinct the mammoth, what we’ll learn along the way, and how you fund a project like this when the final product is not for sale. You’ll have to listen to the pod to get all the details but here is the TL:DR. Mammoths from elephantsThe Asian elephant is the closest living relative of the mammoth. There is some ancient mammoth DNA available but it’s incomplete. It’s not a matter of injecting it into an elephant egg and hoping you get some hybrid. This is a massive genome engineering project that starts with figuring out which genes contribute, for example, to the wooliness and cold tolerance of the mammoth and engineering those into an elephant to produce a mammoth.How does that happen? So many technical challenges! Can CRISPR technology be used to make multiple (hundreds?) of genome changes in one cell? Then there is the challenge of somatic nuclear transfer, etc. Probably a couple more things…. And if you successfully get a mammoth after all of that, what kind of environment will they need to thrive and expand the population enough to be eventually reintroduced into the Arctic? After that, it’s a question for science and society of accepting and protecting them.Not subscribed yet? Really? Let’s fix that. Next week we’re talking about manufacturing drugs in space. After that, who knows?Bioinformatics, AI and the business modelFiguring out which genetic variations matter and aren’t just neutral changes along with understanding the elephant genome including regulatory sequences no doubt, is an enormous bioinformatics project. That brings me to the business model. Titus says that analogies to the space program may be overused, but in this case, it seems appropriate. There are many technologies and capabilities to be developed along the way that could be commercialized to support the core mission. One example: Colossal recently spun out a company, Form Bio, based on their bioinformatics technology that will help the cell and gene therapy industry.We chatted briefly about an AI component of this project. How do you identify all the elements of the target environment? One way is by listening and identifying specific sounds. That’s tedious and time-consuming for a human being but…My team in particular developed an interesting way to use machine learning, unsupervised, and actually read through and listen through audio. And instead of having a manual annotator, someone who goes through and listens to something and puts a little mark in their digital notebook, we can actually have an algorithm go through and say, “There is a point of interest.”Then a human can go directly to the annotations and try to identify the source of those sounds in the environment. Given all the tech needed to make these projects happen and the biology learned as a result, more spinoffs seem likely. But wait! There’s more.The mammoth isn’t the only animal on the bring-back list. Scientists at Colossal are also working on the dodo (not long extinct) and the Tasmanian tiger, which I learned is not actually a cat. The thylacine, although it has stripes that make it somewhat resemble a tiger, looks more like a dog and is actually a carnivorous marsupial, as is (fun fact) the Tasmanian devil. The last one in captivity died in 1936. Each of these is significant for restoring their native ecosystems. As you can tell, while there are lots of questions to be answered yet, I’ve become a fan of this project for its sheer boldness and the joy of discovery. We’ll cover another bold project in the next episode: manufacturing drugs in space. More why and how questions. Make sure you subscribe and share. And let me know what you think about all of this in the comments. The interviews with my guests are the highlight of my week. Listeners seem to enjoy them too.Conversations are fun and your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. 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

Growing primary cells in 2D on plastic surfaces is not a good representation of the 3D environment of the body, regardless of your purpose. Cells grown in a dish eventually run out of room. They need to be disrupted and seeded onto new plates at a lower density. Then they run out of time. They just get tired and stop dividing. TBH, some days, I feel the same way.If these challenges can be overcome, we can, in addition to growing larger quantities of cells for investigation or production, learn a lot more biology. I talked to A.J. Mellott, CEO and co-founder of Ronawk, about the technology they have developed that uses hydrogels to allow cells to grow in 3D microenvironments and interact with each other more like they would in the body. The hydrogel blocks - they call them bioblocks - contain microchannels that provide a large surface area, but they also fit together like LEGOs allowing the expansion of a culture by simply adding more blocks to the matrix.It's really fascinating because now we're starting to see things that happen inside our hydrogels that we can point to the body and look and say, “Oh, this is similar. I see this happening in the body, and we can get more information out of, uh, what's going on.And we can even start looking at the signaling between the cells and how they talk to each other. So from a scientific perspective, it's really fun. But then also from a business perspective, we now have this really easy-to-use technology that can help others scale, help others try new experiments and test new medicines that weren't easy to test before this.As much as I enjoyed hearing about the scaling up of cell populations (and scaling down the labor involved), for me the chance to study some biology was equally exciting. One can embed the material with growing cells in paraffin and section it with a microtome to investigate what’s going as cells are migrating and laying down extracellular matrix. What will we learn about cell communication and extracellular matrix production? What are cells putting into exosomes and why? Can we engineer useful therapies from those processes?Now add a level of complexity. Imagine the possibilities for studying the interactions between different cell types such as joining two blocks, one with tumor cells and another with immune cells to see what happens. For some reason, I can’t get the image of gladiators doing battle in a massive arena out of my head. That’s a ticket I’ll get in line for.I really enjoy these interviews with my guests. The deepest insights are the best branding. I’d love to help you with that. Chat with me about custom content for your life science brand. 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 will we get to a place of reliable protein biomarkers as predictors or indicators of disease? Ole Vorm is a founder and director at Evosep, producing separation products between the patient sample and a mass spectrometer.What is the state of those analyses and what are the obstacles yet to be overcome? The first obstacle in terms of the proteome itself is that in any sample - urine, blood etc.- there are a few abundant proteins that represent the bulk of the material. It’s likely that the proteins of interest (if we can find them) are a small portion of the total and any changes in quantity or relevant modifications may be subtle. But of the currently FDA approved biomarkers typically analyzed by ELISA assays, about 50 can be detected by simple injection of a protein digest into a mass spec. That’s good but not a lot.From a physician’s perspective in the clinic, …they never start out, uh, from a blank sheet of paper. They have an idea what they're looking for and asking for quantitation of say, two or three biomarkers, I mean, proteins basically,would typically suffice to say, okay, we're in this direction, versus going in that direction. And that is very cheaply, automatically done with ELISAs running on a fully automated, robotic platform in the clinical biochemistry labs.The current ability to detect 300 proteins out of the mix is way more than a physician could use right now, but probably does not go deep enough to uniquely detect a disease. In many sports, this is called no man’s land.Nevertheless between improvements in detection, robustness and AI to help analyze the data, Ole sees the field moving dramatically over the next few years.In terms of analysis, we may find that the changes we see in a patient’s proteome, may not directly identify targets for therapy. Rather they might reflect secondary effects of a disease. In this case, where treatments can be found, those biomarkers may serve to monitor progress during treatment as opposed to being used for diagnosis.Beyond the need for improved robustness (a clinical analyzer needs to run hundreds of samples per day without human intervention), there aren’t enough mass spectrometers to analyze the possible volume of samples. Using proteomics on top of genomic or metabolic analysis seems to be a more likely strategy.Ole closed with this idea:I do think things are progressing and, and I think, you know, what is really, really needed in our field would be sort of like the first success story. I mean that, from my perspective, that's what we really need to somebody, some group coming out and saying, so now we have this, this protein pattern is the detection of this and this. Whatever the success story basically is, I think it is just important that we begin to see some success stories and that will fuel the fire and get, more things going.I’m interested in your thoughts. Do you know of any success stories already? Where do you see proteomics taking off?Chat with Chris about custom content for your life science brand. 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

It turns out, you can do quite a lot.Jud Schneider is the CTO of Nashville Biosciences. I reached out to him to talk about their collaboration with Amgen and Illumina to sequence 35,000 African-American genomes. How is that possible?Nash Bio (owned by Vanderbilt University Medical Center) has about three and a half million de-identified health records. About 10% of those have consented DNA tied to those records. This is a treasure trove of data for pharma and AI companies to uncover patterns and develop new therapies.The number of genomes in that project blew me away from the start. But among genome data sets, African Americans are underrepresented. This is an opportunity to make important discoveries for a significant part of the population as well as the population as a whole.The genome data by itself isn’t enough. The real value is tying the genetic data to health records to find and understand patterns that associate genetic variation with disease or simply biology.Our conversation evolved into the possibilities with such a massive data set for training AI, including imaging data, and how to get them most out of it. With the help of their clinical team, they can build very specific cohorts for training AI models. Jud says they can think of about a hundred ways to use the data, but customers can think of a thousand.Let's just say we're looking at chest CTs. And you're looking for your, I'm just making something up, but we're developing a product that looks for lung nodules. right? Well, we've got lots of chest CTs that have diagnosed certain types of lung cancers, and you can actually get very specific on the type of lung cancer. And we've also got lots of, you know, just kind of blank chest CTs, you know, and ones with artifacts that are important, like there's a pacemaker in there. There's other types of medical devices that may be implanted or, you know, there's some different anatomies that you need to take into account. We just got quite a diversity of information that you can really end up with an extremely powerful and well-trained model you know is really starting from a place of grounded in the actual diagnosis and not necessarily just CPT codes.Pardon the interruption. You are subscribed aren’t you?It’s not enough to have a lot of data. You need to understand the protocols under which it was generated and factors that might not be immediately apparent. It would be easy to hand over a bucket of data based on an ICD code and let the customer have at it. (I learned that ICD codes might be what I would describe as “squishy”. Sometimes an initial diagnosis might be uncertain or inaccurate. But some thoughtful analysis can make the data much more useful. That’s the role of the clinical team who are working with the data on a regular basis.We find ourselves in a situation all the time where we're really able to disambiguate the, uh, the nuances of the ICD coding system and the billing data to really find the patients that actually have the diagnosis and actually have the data, you know, within routine clinical care that's necessary.The big takeaway for me is that while we generate and capture ridiculous amounts of data every day (in healthcare and elsewhere) it’s still important to understand the limitations of how the data is gathered (ICD codes for example) and be thoughtful about what you are looking for to get the most value out of it.Chat with Chris about custom content for your life science brand.Fun fact: I first interviewed Jud on Flip Turns, my podcast about people whose lives were changed by swimming. 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

ChatGPT has become the AI that is impossible to ignore. As I wrote in my first post a little more than a year ago, I would be neither a cheerleader nor a detractor, but rather a curious observer. So here we are. My main concern with respect to many technologies is the dilution of our humanity. In response to all the posts I was seeing where people were asking ChatGPT to create content, I wrote on LinkedIn that the value of your voice, even better with your face attached to it, would increase. The more AI-generated content is available, the more you will stand out, not to mention the benefits of a human interaction.Declan Dunn commented:AI is part of the game, and while some will use it instead of writing, most are using it to get a starting point, to brainstorm ideas when they don't have folks.Agree with putting a voice or visual on it, especially short snippets - you have to earn attention today, and while AI can sort of mimic your voice, it can't replace the inflections, passion, and unique humanity your voice delivers...Declan and I had not chatted in quite some time so he DM’d me to propose a conversation on this topic which I thought (correctly) would be fun. This episode is a freestyle exploration of our thoughts about the possibilities - good and bad - for ChatGPT.As he mentioned above, brainstorming and outlining may be great uses of ChatGPT. A quick first look at current thinking around a topic can get the juices flowing. And if the answers aren’t satisfying, we will slowly learn to ask better questions, provide better prompts.I also wondered about how future versions will be trained when so much of the information it is trained on was generated by a previous version. Will it know when it’s looking at something that was AI generated?In this Wired article, Phil Libin, former CEO of Evernote was said to be enthusiastic about AI in general but shared my concerns:“All of these models are about to s**t all over their own training data,” he says. “We’re about to be flooded with a tsunami of b******t.” -Phil LibinListening back to our conversation, Declan mentions some interesting uses for life science researchers in terms of improving both the inputs and the outputs (presentation) of their work. He also raised the question of does an AI understand the audience? As humans, we tailor our message for the audience. Are their hints of the audience in the questions we ask? Maybe, but not always. There is no shortage of opinions on this new tool. I found this podcast from Scott Galloway enlightening:Prof G and the AI Hype CycleAnd in the next episode of Life Science Marketing Radio, I’ll talk to David Nathan who used ChatGPT to write a children’s book in the carpool lane and generated an illustration through Midjourney a generative AI for images. If you are as interested in this episode and subject as I have been, I hope you share your thoughts below!Chat with Chris about content for your life science brand 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