Advertise on podcast: Smart Biotech Scientist | Master Bioprocess CMC Development, Biologics Manufacturing & Scale-up, Cell Culture Innovation

Have you ever wondered why cell therapies remain so expensive and hard to bring to patients worldwide, despite incredible scientific advances? Biopreservation and cell processing are critical pain points in scaling advanced therapies for global distribution, with variables like cryoprotectant toxicity, transport stability, and automation dictating both cost and clinical success. Sean Werner, CTO of Cell Processing at BioLife Solutions and former Sexton Biotechnologies leader, has seen the real cost when assumptions break down at scale. From container fractures to uncertain analytics, he’s guided teams through the frontline challenges of CMC and biologics. Topics discussed: Why decentralized manufacturing and local storage might be the most practical path forward for delivering cell therapies globally (03:05)Key distribution chain challenges—how logistics complexity escalates with cross-border shipments and the risks of primary packaging failure (03:44)Regulatory expectations for transport validation and the importance of container integrity during shipping (04:49)The growing role of automation and closed systems in reducing manual steps, with a look at current capabilities and future directions (06:41)How more advanced analytics could unlock greater efficiencies and reduce manufacturing costs in cell therapy (07:49)Practical guidance for scientists looking to optimize freezing and thawing processes, including common assumptions to avoid (08:39)When it makes sense to use DMSO, risk management considerations, and whether DMSO-free really means safer (10:39)Long-term aspirations for room-temperature biopreservation and challenging industry assumptions about stability (13:13)The importance of process control and attention to detail in minimizing variability and improving clinical outcomes (14:44)Smart insight: Sean Werner challenged the field to move beyond the cryo status quo: can we develop technologies for stable room temperature storage of living cells and biologics? While the hurdles are immense, questioning established dogma is the only route to transformative change. Above all, he warned, never treat biopreservation as an afterthought—the variability it introduces can undermine even the most promising therapies . As cell therapy matures, early and continual investment in process innovation and discipline will remain key. If this episode has you rethinking freeze-thaw, here’s where to go next. Start with the science behind cryopreservation, then compare two takes on cryoprotectants: DMSO-free formulations and antifreeze-inspired chemistry. Episodes 241 - 242: DMSO in Cell Therapy: Why Viability Scores Hide the Real Toxicity with Steve OhEpisodes 161 - 162: How to Achieve 85%+ Cell Recovery Without DMSO’s Toxic Side Effects with Jeffrey AllenEpisodes 65 - 66: Freezing and Thawing Cells: the Science Behind Cryopreservation with Mark DavisonEpisodes 129 - 130: Revolutionizing Cell Therapy Manufacturing: Reducing Costs to Reach More Patients with Jason FosterConnect with Sean Werner:  Website: www.biolifesolutions.com LinkedIn: https://www.linkedin.com/in/sean-werner-54688326/ Support the show

The integrity of individual cells is the cornerstone of breakthrough cell and gene therapies—but translating lab discoveries into clinical success demands mastering cryopreservation challenges rarely discussed in depth. Sean Werner, Chief Technology Officer of Cell Processing at BioLife Solutions,a leading provider of bioproduction tools and services to the cell and gene therapy and broader biopharma markets, has dedicated his career to safeguarding cell viability from the lab bench through to clinical application. Topics discussed: Sean Werner's unconventional career progression and early experiences in regenerative medicine (03:22)The critical role of cryopreservation in cell and gene therapy product quality (05:59)Biophysics of freezing: ice nucleation, supercooling, and their impact on cell viability (07:32)Hidden pitfalls in cryopreservation, including ice recrystallization and osmotic stress (07:43)Real-world challenges during clinical handling and thawing of cell therapies (11:18)Why the commonly used -1°C per minute freeze rate is not universally optimal (13:09)Difficulties in tracing clinical problems back to early cryopreservation choices (13:54)Importance of evaluating long-term cell function, not just post-thaw viability (15:08)Regulatory expectations around freeze-thaw processes in therapy manufacturing (16:34)Smart insight: Success in cell therapy and advanced biologics is inseparable from mastery of cryopreservation. By adopting an experimental and data-driven mindset—questioning assumptions, customizing protocols, and measuring what truly matters—scientists can better fulfill that original promise: that a single cell, carefully protected, can change the course of medicine for patients worldwide. If this episode has you rethinking freeze-thaw, here’s where to go next. Start with the science behind cryopreservation, then compare two takes on cryoprotectants: DMSO-free formulations and antifreeze-inspired chemistry. Episodes 241 - 242: DMSO in Cell Therapy: Why Viability Scores Hide the Real Toxicity with Steve OhEpisodes 161 - 162: How to Achieve 85%+ Cell Recovery Without DMSO’s Toxic Side Effects with Jeffrey AllenEpisodes 65 - 66: Freezing and Thawing Cells: the Science Behind Cryopreservation with Mark DavisonEpisodes 129 - 130: Revolutionizing Cell Therapy Manufacturing: Reducing Costs to Reach More Patients with Jason FosterConnect with Sean Werner:  Website: www.biolifesolutions.com LinkedIn: https://www.linkedin.com/in/sean-werner-54688326/ Support the show

Biologics development is full of hidden pitfalls, from selecting the right cell line to navigating analytical assessments that can make or break a therapy's success. Today, we feature Lars Stöckl and Lena Tholen, industry experts from FyoniBio GmbH, who have deep experience guiding biotech teams through the maze of CMC development, troubleshooting both common and unusual product quality challenges. Topics discussed: Key factors in selecting host cell lines and the importance of matching the platform to molecule complexity (02:34)The role of broad analytical assays early in cell line and pool development for better decision-making (03:34)Glycosylation, post-translational modifications, and analytical strategies for both standard antibodies and more complex biotherapeutics (05:10)When and how to conduct developability and manufacturability assessments, especially for novel or specialized molecules (06:55)Troubleshooting glycosylation and aggregation problems—when to tweak the process and when to reconsider the molecule (08:05)Importance of clear, direct communication with clients regarding manufacturability and process viability (09:32)Example of how different CHO cell lines can dramatically impact molecule outcome and company trajectory (12:08)Keeping pace with technological advances through collaboration, conferences, and feasibility studies with startups (13:55)The move toward customization over standardization in cell line and process development (18:07)Smart insight: The future of bioprocess development lies in a customized, molecule-centric approach. Rather than relying on generic, pre-set development platforms, success comes from carefully matching cell lines, processes, and analytical methods to the unique requirements of each molecule. True innovation and commercial success arise from adapting everything—cell line, process, analytics—to the molecule at hand. Lars and Lena’s main point is that early choices about the host cell line, the analytics and the partner decide what’s possible later on. The episodes below take that idea further. One looks at the mechanics of cell line development, one at why promising molecules fail to manufacture, and two at outsourcing CMC work from the sponsor’s side. Episodes 117 - 118: Cell Line Development Secrets: Eliminating Critical Bottlenecks for Faster Timelines with Andrea GoughEpisodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan SharfsteinEpisodes 103 - 104: One-Stop Shop vs. Specialist CDMO: A Scientist’s Guide to CDMO Selection with Sigma MostafaEpisodes 71 - 72: Effective Outsourcing: How Small Biotech Companies Can Thrive with Mark MelvilleConnect with Lars Stöckl and Lena Tholen:  Website: www.fyonibio.com LinkedIn:www.linkedin.com/in/dr-lars-stoeckl LinkedIn: www.linkedin.com/in/lena-tholen-80642a11a Support the show

How can small biotech companies navigate increasing molecular complexity, tight budgets, and the ever-present pressure to accelerate timelines while ensuring long-term process success? In this episode, David Brühlmann welcomes Lena Tholen and Lars Stöckl of FyoniBio GmbH—two scientists who’ve dedicated their careers to optimizing cell line and process development for biopharma clients. Topics covered in this episode: The trend toward outsourcing CMC development and the reasons behind it for both large pharma and small biotechs (07:27)How specialized CDMOs innovate and continuously improve cell line development platforms, giving clients access to new options and efficiencies (10:36)Real-world experience navigating project pitfalls from discovery to clinical studies—including differences between cell lines and processes (13:38)The importance of retaining key activity assays and critical knowledge in-house—and the risks of over-reliance on consultants (15:04)Key factors that help biotech companies thrive when partnering with CDMOs, including internal expertise, flexibility, and milestone planning (17:32)Smart insight: Product quality and success are designed in early through careful choices about cell lines, processes, and analytical strategies. Streamlined outsourcing and platform innovation can turbocharge development, but only when matched with committed, knowledgeable in-house leadership and measured, forward-thinking investment. The next time a CMC decision seems minor or a shortcut tempting, remember the long game—your product quality, speed to clinic, and future cost may all depend on it. Lars and Lena’s main point is that early choices about the host cell line, the analytics and the partner decide what’s possible later on. The episodes below take that idea further. One looks at the mechanics of cell line development, one at why promising molecules fail to manufacture, and two at outsourcing CMC work from the sponsor’s side. Episodes 117 - 118: Cell Line Development Secrets: Eliminating Critical Bottlenecks for Faster Timelines with Andrea GoughEpisodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan SharfsteinEpisodes 103 - 104: One-Stop Shop vs. Specialist CDMO: A Scientist’s Guide to CDMO Selection with Sigma MostafaEpisodes 71 - 72: Effective Outsourcing: How Small Biotech Companies Can Thrive with Mark MelvilleConnect with Lars Stöckl and Lena Tholen:  Website: www.fyonibio.com LinkedIn:www.linkedin.com/in/dr-lars-stoeckl LinkedIn: www.linkedin.com/in/lena-tholen-80642a11a Support the show

Is your process model gathering dust while real-world decisions march on without it? Many technically strong digital tools—no matter how powerful—end up sidelined in bioprocess development. Why is that, and what does it actually take for digital modeling to earn its place at the lab bench? In this episode, David Brühlmann sits down with Moritz von Stosch of HINA Bioventures, a scientist-turned-investor who’s navigated both the technology provider and pharma end-user sides. Moritz von Stosch brings firsthand insights from building digital solutions, deploying them in pharma, and evaluating what actually sticks when the clock is ticking and the stakes are high. Topics discussed: The importance of starting with your purpose when selecting a modeling strategy (03:00)Experimental design: when to use factorial versus random space-filling designs, and the inherent biases each can introduce (04:22)The future of agentic workflows, AI, and autonomous labs in bioprocessing, including the importance and challenges of sensor technologies (06:02)Practical hurdles to implementing fully autonomous laboratories, and the non-obvious value humans still bring (09:09)Adapting mindsets for the evolving role of the bioprocess engineer in a more automated, agent-driven workflow (11:48)Advice for biotech professionals on how to assess the real value in new technologies versus hype, and the role of proprietary algorithms and company stability (13:33)How cultural factors, not just technology, shape the adoption of modeling and digital tools in biotech (16:02)Strategies to help the bioprocess community adopt more innovation while ensuring compliance in regulated environments (17:14)Three key takeaways for staying relevant—including generating data for tomorrow’s questions and balancing curiosity, experimentation, and oversight (19:14)Smart insight: Three takeaways from Moritz von Stosch: Generate data for tomorrow’s questions, not just today’s.Be curious—try, adapt, don’t over-plan.Stay relevant: Use digital tools but keep your human edge (creativity, critical thinking).To keep exploring how modeling and prior knowledge can speed up process development, check out these related conversations: Episodes 05 - 06: Hybrid Modeling: The Key to Smarter Bioprocessing with Michael SokolovEpisodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist GernaeyEpisodes 277 - 278: Your Bioprocess Data Already Holds 35% More Yield: From End-to-End Models to Digital Twins with Ignasi Bofarull-ManzanoEpisodes 215 - 216: From Data Silos to Autonomous Biomanufacturing: Digital Twins and AI-Driven Scale-Up with Ilya BurkovConnect with Moritz von Stosch:  Website: www.hinabioventures.com LinkedIn: www.linkedin.com/in/movosto Support the show

Are you frustrated with reinventing the wheel every time a new molecule enters bioprocess development? Is there a better way to harness data and modeling to accelerate breakthroughs in biotech? The bioprocessing industry is constantly searching for ways to streamline development, reduce costs, and speed new therapies to market—yet leveraging existing knowledge remains a significant challenge. In this episode, David Brühlmann welcomes Moritz von Stosch, partner at HINA Bioventures and a pioneer in digital bioprocess development. Spanning roles from academic research in hybrid modeling to solution design at DataHow and now biotech investment, Moritz von Stosch’s journey traces how mechanistic, hybrid, and machine learning models have (and haven’t) changed process development over the last two decades. Topics discussed: Moritz von Stosch’s career: from early interest in modeling to investment in digital bioprocess tools (03:36)The reality and limitations of platformization and knowledge reuse in large pharma (07:37)Historical context and effectiveness of QbD (Quality by Design) and PAT (Process Analytical Technology) initiatives (10:24)Where modeling can reliably deliver value today in process and clinical development—and where it still overpromises (12:17)The importance of starting to build models early and collecting data that can be reused and repurposed across the process lifecycle (14:17)Approaches to transferring learning between molecules, cell lines, platforms, and the fundamental limitations of this transfer (16:40)Opportunities and difficulties in transferring process knowledge across scales (from microtiter plates to large bioreactors) (18:31)Smart insight: David Brühlmann and Moritz von Stosch agree that models are only useful when they are built on reliable data and interpreted with expert judgment. Models can help biotech teams make better decisions, but they don’t replace human expertise. The real value comes from looking at the whole process, focusing on the data that matters, and making sure knowledge is shared effectively. This can help teams improve bioprocess development and bring new treatments to patients sooner. To keep exploring how modeling and prior knowledge can speed up process development, check out these related conversations: Episodes 05 - 06: Hybrid Modeling: The Key to Smarter Bioprocessing with Michael SokolovEpisodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist GernaeyEpisodes 277 - 278: Your Bioprocess Data Already Holds 35% More Yield: From End-to-End Models to Digital Twins with Ignasi Bofarull-ManzanoEpisodes 215 - 216: From Data Silos to Autonomous Biomanufacturing: Digital Twins and AI-Driven Scale-Up with Ilya BurkovConnect with Moritz von Stosch:  Website: www.hinabioventures.com LinkedIn: www.linkedin.com/in/movosto Support the show

The entire public record of antibody affinity data comes to about half a million measurements, and by David Younger's estimate, upwards of 75% of it is AlphaSeq data from his own company's publications. His conclusion is that no single company can close the gap alone. So he is asking pharma and AI labs to pay for an experiment and share every result with the other members. In Part 2 of this two-part conversation, David Brühlmann talks with Younger, founding CEO of A-Alpha Bio, whose AlphaSeq platform uses engineered yeast to measure protein interactions at scale. Part 1 set out the shortfall: about 10,000 antibody-antigen structures in the Protein Data Bank against a need of hundreds of thousands to millions. Here Younger explains how the consortium keeps proprietary targets out of the shared pool, who has joined, and why he believes it differs from federated learning. Topics discussed: Challenges faced by individual companies in generating sufficient data for effective AI models (02:17)How a data consortium enables pre-competitive data sharing while protecting proprietary information (06:13)Profiles of ideal consortium members and examples of current participants from pharma and AI model builders (08:36)The consortium’s current focus on VHH antibodies and plans for expansion to broader datasets and applications by 2030 (10:00)Comparison between the consortium approach and federated learning models in data sharing and collaboration (12:01)The main takeaways about the quantity and quality of data needed for machine learning in protein engineering (14:09)Smart insight: As David Younger envisions it, successful maturation of these consortia could fundamentally shift the field by 2030. Multiple consortia could address different scaffolds, data types, and problem statements, alleviating the bottleneck that has long constrained progress. The hope is that abundant, high-quality data will enable breakthrough therapeutic advancements while revealing new gaps that, in turn, inspire the next wave of innovation. Notably, David Younger sees collaboration—not just data scale—as the true secret weapon. Unlike federated learning, consortia incentivize members to share not just data, but experimental insights and best practices, effectively lifting all boats and accelerating collective progress. Curious how others are tackling the data problem in protein design? These episodes pick up right where David Younger leaves off. Episodes 185 - 186: How Generative AI Accelerates Protein Design for Biotech Discovery with Elise de ReusEpisodes 115 - 116: Revolutionizing Biologics Development with Hyper Throughput Screening and AI with Jeremy AgrestiEpisodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan SharfsteinEpisodes 219 - 220: From 10,000 Structures to 1.8 Billion Interactions: Breaking the Data Bottleneck to Engineer Efficacious Therapeutics with Troy LionbergerConnect with David Younger  Company website: www.aalphabio.com LinkedIn: www.linkedin.com/in/david-a-younger/ Data Atlas website: www.atlas.aalphabio.com Support the show

The Protein Data Bank holds about 10,000 antibody-antigen structures and grows by roughly 1,000 a year. David Younger's scaling work suggests that generalizable de novo antibody design needs hundreds of thousands to millions. At that pace, even 200,000 structures is nearly two centuries away. In this episode, David Brühlmann hosts David Younger, founding CEO of A-Alpha Bio and the mind behind the AlphaSeq platform. Trained at the intersection of synthetic biology and computational protein engineering, David Younger cut his teeth at the Institute for Protein Design and sharpened his focus on the stubborn gap between theoretical promise and practical performance. His approach rewrites the rules of data generation—scaling up both the volume and the insight from protein interaction data to deliver the kind of information AI needs to actually make an impact in therapeutic design. Topics discussed: Bottlenecks caused by insufficient and low-quality data in AI-enabled protein engineering (02:53)The limitations of traditional protein discovery methods and the persisting role of serendipity in antibody development (08:02)An overview of the AlphaSeq platform and how it enables large-scale measurement of protein interactions using engineered yeast (10:50)The differences between measuring protein-protein affinities with conventional techniques and AlphaSeq’s batch approach, including cost and speed advantages (16:54)Strategies for generating training data for machine learning models in protein engineering, including the need for structural and affinity data (18:23)The value and limitations of the Protein Data Bank (PDB) in training de novo design models (20:17)The challenge of benchmarking foundational models for protein engineering and the need for universal industry standards (23:11)Smart insight: The future of biotherapeutic innovation is intertwined with a simple truth: more and better data unlock AI’s true potential. With breakthrough wet-lab technologies like AlphaSeq, and commitment to openness and benchmarking, the dream of efficient, precise, and truly rational protein engineering may soon become reality. The next big leap in biotech is not just smarter algorithms—but the scale, quality, and transparency of the data that powers them. Curious how others are tackling the data problem in protein design? These episodes pick up right where David Younger leaves off. Episodes 185 - 186: How Generative AI Accelerates Protein Design for Biotech Discovery with Elise de ReusEpisodes 115 - 116: Revolutionizing Biologics Development with Hyper Throughput Screening and AI with Jeremy AgrestiEpisodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan SharfsteinEpisodes 219 - 220: From 10,000 Structures to 1.8 Billion Interactions: Breaking the Data Bottleneck to Engineer Efficacious Therapeutics with Troy LionbergerConnect with David Younger  Company website: www.aalphabio.com LinkedIn: www.linkedin.com/in/david-a-younger/ Data Atlas website: www.atlas.aalphabio.com Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here Support the show

Cardiovascular disease has long been managed by slowing its relentless progression. But Matthew O'Connor, CEO of Scientific Affairs at Cyclarity Therapeutics, is betting on an outright paradigm shift: treating atherosclerotic plaque with therapies designed to actively reverse disease, not simply manage symptoms or risk. In this episode, David Brühlmann explores the strategy, regulatory journey, and manufacturing realities behind Cyclarity's unconventional cyclodextrin-based approach—a molecule sitting at the crossroads of small and large molecule drug development. Topics discussed: Insights into the company's clinical development progress, including completion of a first-in-human study and what comes next (02:47)How the FDA views drugs that don't fit traditional categories and how this influences development pathways (04:35)The challenges and considerations in demonstrating efficacy for drugs designed to reduce heart attacks and strokes (05:22)Cost considerations in manufacturing the cyclodextrin dimer and how it compares to biologics and GLP-1 drugs (08:14)Vision for how cardiovascular disease may be diagnosed and treated a decade from now, including the role of imaging and prevention (10:24)Broader implications for treating age-related diseases by targeting toxic metabolites in the body (14:25)Why next-generation therapeutics may be built not by sticking to old modalities but by tackling root causes with custom solutions (16:10)Reflections on making new drugs both safe and fundamentally beneficial, minimizing side effects (17:10)Smart insight: Start with the problem, not the modality. Matthew O'Connor argues that instead of defaulting to an antibody, a small molecule or a gene therapy, developers should build a custom solution to the problem they're trying to solve. A drug that suppresses a pathway across the whole body brings side effects you have to manage. A drug that removes something harmful, like oxidized cholesterol, can have side effects that are actually beneficial. His goal for the next generation of drugs is ones that simply make people healthier. When a drug is too big to be a small molecule and too small to be a biologic, every CMC decision gets harder. These episodes look at what it takes to develop, characterize and manufacture a modality that doesn't fit an existing box. Episodes 281 - 282: When Your Delivery Vehicle Contains a Membrane Protein: CMC Decisions With No Regulatory Precedent with Jitendra KumarEpisodes 207 - 208: Cryogenic Infrared Ion Spectroscopy: From Mass Spec Limitations to Molecular Precision with Tom RizzoEpisodes 197 - 198: Mastering ADC Development: CDMO Strategies for Analytics and Scale-Up with Amanda HoertzEpisodes 231 - 232: From IND to BLA: The Biologics CMC Decisions That Determine Regulatory Success with Henri KornmannConnect with Matthew O'Connor: Website: www.cyclaritytx.com LinkedIn: www.linkedin.com/in/droki Email: [email protected] Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here Support the show

Why does CMC development still expect every drug to be one molecule with one peak, when new therapeutics don't always fit neatly into existing regulatory or chemical categories? Matthew O'Connor, CEO of Scientific Affairs at Cyclarity Therapeutics, is developing a drug that sits between a small molecule and a biologic. On the Smart Biotech Scientist Podcast, Matthew shared how his team engineered a cyclodextrin dimer that binds and removes 7-ketocholesterol, an oxidized form of cholesterol that builds up in artery plaque and is linked to a higher risk of heart attack and stroke. Topics discussed: Matthew O'Connor's motivation for focusing on aging and molecular damage (03:39)The biological problem of oxidized cholesterol buildup and its role in atherosclerosis (04:42)Mechanism of action: how the cyclodextrin binds and removes 7-ketocholesterol (06:23)Approaches to designing a highly specific cyclodextrin therapeutic (09:14)The "medium-sized molecule" characteristics and the question of regulatory classification (12:16)Why cyclodextrin starting material is cheap and not a manufacturing bottleneck (15:37)Manufacturing strategies and the role of specialist CDMOs in complex carbohydrate chemistry (17:04)Methods for demonstrating identity and consistency in isomeric mixtures (18:43)Drug formulation considerations and why an injectable route is necessary (21:46)Smart insight: Matthew O'Connor's work shows what happens when you start with the problem rather than the drug format. His team's cyclodextrin dimer doesn't fit neatly as a small molecule or a biologic, and that makes manufacturing, analytics and regulatory work harder. But if it can remove oxidized cholesterol from the body, it could help reverse plaque instead of just slowing it down. When a drug is too big to be a small molecule and too small to be a biologic, every CMC decision gets harder. These episodes look at what it takes to develop, characterize and manufacture a modality that doesn't fit an existing box. Episodes 281 - 282: When Your Delivery Vehicle Contains a Membrane Protein: CMC Decisions With No Regulatory Precedent with Jitendra KumarEpisodes 207 - 208: Cryogenic Infrared Ion Spectroscopy: From Mass Spec Limitations to Molecular Precision with Tom RizzoEpisodes 197 - 198: Mastering ADC Development: CDMO Strategies for Analytics and Scale-Up with Amanda HoertzEpisodes 231 - 232: From IND to BLA: The Biologics CMC Decisions That Determine Regulatory Success with Henri KornmannConnect with Matthew O'Connor: Website: www.cyclaritytx.com LinkedIn: www.linkedin.com/in/droki Email: [email protected] Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here Support the show

Scale-up doesn't fail because the science was wrong. It fails because a cell's environment in a shake flask has little in common with its environment in a bioreactor. Christian Witz has spent years building the tools to close that gap: simulating exactly what a cell experiences as it moves from bench to plant, before a single liter is wasted finding out the hard way. Continuing from Part 1, David Brühlmann and Christian Witz, CEO and founder of SimVantage, go deeper into how CFD moves from theory to daily practice: validating simulation results, scaling real cell therapy and Streptomyces processes, and an active FDA-backed project on residence time distribution in continuous bioprocessing. Topics discussed: Why data validation is crucial in CFD simulations and how to interpret and trust simulation results (02:39)Real-world examples of scaling up from shake flasks to stirred tank reactors using CFD, including specific collaborations and cell therapy case studies (05:40)Technical and validation challenges in simulating fluid dynamics in shake flasks and integrating these results into scale-up strategies (08:14)Ongoing FDA-backed project to model residence time distribution in continuous bioprocessing and its regulatory significance (11:49)The increasing openness of regulators like the FDA to include CFD data in submissions and relevant guidelines for simulation credibility (13:23)Advice for small biotech teams on when and how to start using CFD in CMC development and scale-up planning (15:06)Insights on the future of bioprocessing, including virtual scale-up, digital reactor repositories, and the democratization of CFD tools (18:20)Smart insight: Christian Witz advised that teams begin CFD modeling as early as concept development. CFD not only helps choose the right equipment—even when working with contract manufacturers—but creates a digital process record that reduces experimental burden, shortens timelines, and impresses investors with its risk mitigation. If this conversation got you rethinking your scale-up strategy, here are a few past episodes that go deeper on the pieces Christian touched on: Episodes 91 - 92 : Mass Transfer Secrets: Mastering Bubbles and kLa from Bench to Large-Scale Production with Lars Puiman & Rik VolgerEpisodes 245 - 246: Why Your Shake Flask Culture Doesn't Scale: OTR, Shaking Diameter, and How to Fix It with Tibor AnderleiEpisodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist GernaeyEpisode 243: Turn Tech Transfer from a Gamble into a Managed Process: The 6-Pillar Biologics Scale-Up FrameworkConnect with Christian Witz: Website: www.simvantage.com Christian’s LinkedIn: www.linkedin.com/in/christian-witz-84aa9b162/ Christian’s email: [email protected] Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here Support the show

You've perfected your process at the bench. Now comes the part that keeps CMC scientists up at night: will it still work at 2,000L? Right now, most teams find out the hard way, through failed runs, wasted batches, and months of delay to patients waiting on a therapy. Christian Witz believes there's a better way: use computational fluid dynamics to see how your cells will actually behave at full scale before you ever run the process, and stop treating scale-up as a guessing game. On this episode of the Smart Biotech Scientist Podcast, David Brühlmann talks with Christian, founder of SimVantage, about why he treats CFD as a tool every process engineer should use directly, not something you outsource to a specialist. Christian's path into biotech ran through heat pump simulations and GPU-based particle flow modeling before he rebuilt a legacy Fortran bioreactor simulation program in modern C++ and CUDA, work that became the foundation of SimVantage. Topics discussed: Christian’s path from simulating heat pumps and particle flows to pioneering GPU-based bioreactor simulations (03:54)The surprising lack of full equipment characterization in the biotech industry compared to fields like oil, gas, and iron & steel (06:40)The interdisciplinary challenges and steep learning curve when entering biotech from other industries (08:07)Why academic spinouts matter and the practical realities of founding a company based on university-developed software (09:44)Reasons behind CFD’s low adoption in bioprocessing—perceived complexity, need for specialists, and historical limitations in algorithms and computing power (11:58)How recent advances in GPU power, algorithms, and cloud computing remove barriers for routine use of CFD in process development (14:35)Strategies for characterizing and scaling processes across various reactor types, from shake flasks to manufacturing reactors (16:39)Practical considerations and limitations when setting up comprehensive CFD characterizations, including simulation parameter choices (19:49)Smart insight: The degree of reactor characterization depends on a company’s needs. Startups might analyze a scale-up project once, while contract manufacturers—handling diverse products—benefit from comprehensive, reusable characterization across all reactors and operating conditions. Simulations are guided by physics (density, viscosity, surface tension) rather than biological specifics, allowing quick adaptation to new media or cell types. If this conversation got you rethinking your scale-up strategy, here are a few past episodes that go deeper on the pieces Christian touched on: Episodes 91 - 92 : Mass Transfer Secrets: Mastering Bubbles and kLa from Bench to Large-Scale Production with Lars Puiman & Rik VolgerEpisodes 245 - 246: Why Your Shake Flask Culture Doesn't Scale: OTR, Shaking Diameter, and How to Fix It with Tibor AnderleiEpisodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist GernaeyEpisode 243: Turn Tech Transfer from a Gamble into a Managed Process: The 6-Pillar Biologics Scale-Up FrameworkConnect with Christian Witz: Website: www.simvantage.com Christian’s LinkedIn: www.linkedin.com/in/christian-witz-84aa9b162/ Christian’s email: [email protected] Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here Support the show

Biotech founders often pour everything into building the “perfect” product only to realize their real customers have walked out the door. Chasing perfection can burn money and stall even the most promising CMC innovations. In this episode, David Brühlmann continues his conversation with biotech entrepreneur and investor John Bonham-Carter. John shares his insights on the realities of building and scaling successful biotools companies, from the challenges of fundraising and the importance of authentic storytelling, to knowing when to stop perfecting a product and start selling. Topics discussed: How fundraising is less about money and more about the story, team, and real commitment behind a startup (02:33)Practical advice for founders: obsess over the customer, not just the technology (07:14)The dangers of spreading yourself too thin as a startup founder and lessons from parenting applied to startups (07:09)Choosing business partners and collaborators whose skills complement your own—and making peace with imperfection (10:10)John’s approach to building teams and why accepting mediocrity in some areas can lead to collective excellence (11:16)The story behind John joining Stellion Biosystems, and what makes their cell counting technology different in the market (11:51)Using creative, low-budget tactics for visibility—why John chose a lizard mascot for Stellion Biosystems (15:19)Thoughts on when (if ever) to stop and the value of keeping multiple life and career doors open (17:26)John’s main takeaway: “Try everything”—professional advice drawn from experience (and Zootopia) (19:01)Smart insight: John leaves us with a simple yet powerful credo: “Try everything.” In biotech, that means embracing experimentation not just in the lab, but in business strategy, partnerships, hiring, and technology adoption. By collaborating, iterating, and listening closely to customers, you can grow, succeed, and—perhaps—build something that truly makes a difference. In a field where the only constant is change, remember: launch before you’re ready, find your people, and keep your story genuine. Some ideas are ahead of their time; a few people make a career of being early. This is part bioprocess history, part founder's playbook: why the best technology doesn't automatically win, how to move a conservative industry, and when to sell rather than scale. To go further on both the technology and the business behind it: Episodes 191 - 192: Process Intensification Secrets: A Process Engineer's Decision Framework with Andreas CastanEpisodes 183 - 184: From Lab to Market: Secrets to Commercializing Cutting-Edge Biotech Innovations with Chervee HoEpisodes 259 - 260: Why Strong Science Isn't Enough to Get Funded: What Investors Actually Look For with Michael RomeEpisodes 165 - 166: Why Your Funding Pitches Fail Despite Brilliant Science (And How to Fix It)Connect with John Bonham-Carter: Website: www.stellion-biosystems.com LinkedIn: www.linkedin.com/in/johnbc Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here Support the show

Biotech loves talk of disruptive technology, but few have repeatedly shifted the industry's direction. This episode of the Smart Biotech Scientist Podcast focuses on an idea once dismissed as a fool's game: process intensification through perfusion—now the backbone of leading biomanufacturing platforms. Meet John Bonham-Carter, a serial entrepreneur whose fingerprints are on some of biotech's most transformative tools. From putting the once-ignored ATF system and perfusion on the global stage to pushing intensified cell therapy bioprocessing with ERBI, John's story isn't about chasing the next big exit. Instead, it's about spotting unmet needs and building and selling biotools companies more than once. Topics discussed: The story behind the ATF system, and how John Bonham-Carter and his collaborators convinced a conservative industry to adopt perfusion (04:43)Early career influences, including family ties to bioprocess equipment manufacturing (05:03)Reflections on the biotech industry’s culture of collaboration and the dual motivation to deliver medicines and achieve commercial success (07:18)Realities of scaling a startup, trading income for equity, and the role of persistence in sales (09:34)Lessons learned from global travel and building professional networks in biotech (10:16)The importance of recognizing what drives different biotech companies to adopt new technology (12:25)The transition from ATF to co-founding Erbi, a bioprocessing startup focused on small-volume cell therapy (19:05)Strategic acquisitions: experiences of being acquired by Repligen and Merck Millipore (22:50)Advice for founders on whether to build a company for exit or long-term operation (23:07)The limits of leading with technology, and why customer understanding is critical to success (26:10)Smart insight: For founders, John Bonham-Carter offers practical guidance anchored in self-awareness. Should you build a company for the long haul or for acquisition? The answer: “There isn’t really a right answer...it is, what is the life you want to lead?” Some entrepreneurs thrive at the scale of ten-person teams and relish the handoff to a strategic acquirer. Others yearn to build and steer a 200-person enterprise. Regardless, serving customers and employees well, and being attuned to the market’s shifting demands, matter most. Exit opportunities arise from building value and strategic fit—not from fixating on selling out. Some ideas are ahead of their time; a few people make a career of being early. This is part bioprocess history, part founder's playbook: why the best technology doesn't automatically win, how to move a conservative industry, and when to sell rather than scale. To go further on both the technology and the business behind it: Episodes 191 - 192: Process Intensification Secrets: A Process Engineer's Decision Framework with Andreas CastanEpisodes 183 - 184: From Lab to Market: Secrets to Commercializing Cutting-Edge Biotech Innovations with Chervee HoEpisodes 259 - 260: Why Strong Science Isn't Enough to Get Funded: What Investors Actually Look For with Michael RomeEpisodes 165 - 166: Why Your Funding Pitches Fail Despite Brilliant Science (And How to Fix It)Connect with John Bonham-Carter: Website: www.stellion-biosystems.com LinkedIn: www.linkedin.com/in/johnbc Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here Support the show

What if building a world-class biotech company didn’t require owning a single piece of manufacturing equipment or even a lab of your own? Most startups obsess over bricks, mortar, and stainless steel. Not Sandra Núñez. She’s challenging the status quo as CEO of Amela Biosciences by running a “virtual plant” model: zero in-house production, everything outsourced, and agility baked into every decision. It’s a bold experiment in redefining what a biotech company can look like. One that’s already delivering real, animal-free products to customers today. Topics discussed: Key considerations and pitfalls in tech transfer from academic labs to external CDMO partners (02:34)The reasoning behind choosing a virtual plant model with no in-house manufacturing (04:57)Criteria for selecting external manufacturing partners, including technical capabilities and cultural fit (06:28)Stakeholder communications and managing misconceptions about outsourced manufacturing (07:44)Process development challenges when scaling products for commercial use, including impurity profile and scalability of purification methods (08:53)Early preparations for future GMP manufacturing and building a foundation for regulatory compliance (11:20)The impact of regulatory shifts (like the FDA Modernization Act 2.0) on manufacturing strategy and product reproducibility (12:47)Hopes for the company’s future role in the transition to animal-free and regenerative medicine (14:19)Practical advice for startup founders considering a leap from corporate biotech to entrepreneurship (15:09)Reflections on the importance of addressing batch-to-batch variability and building reproducible systems (16:40)Smart insight: Don’t accept batch-to-batch variability. Reproducibility is non-negotiable. Batch-to-batch variability, whether in raw materials or process design, is a critical risk that forward-thinking should design out, not accept as inevitable. As Sandra concludes, reproducibility isn’t just a lab problem, it’s a company-building problem, one that shapes strategy, manufacturing partnerships, and regulatory success. Here are four episodes that pick up the same threads: animal-free matrices, reproducibility by design, and building a biotech without a factory: Episodes 271 - 272: From Static Scaffolds to Dynamic Matrices: Hydrogels for Animal-Free 3D Cell Culture with Jan Hunik and Matt BakerEpisodes 221 - 222: From 2D Cultures to Advanced 3D Cell Models for Preclinical Research with Catarina BritoEpisodes 275 - 276: From Lab-Scale Molding to GMP: Manufacturing a Collagen Implant for the Clinic with Eva-Maria BaletEpisodes 279 - 280: Why Nanovesicles Outperform Exosomes: Scalable Drug Delivery Beyond Injectable Vaccines with Christopher LocherConnect with Sandra Núñez: Website: www.amelabiosciences.com Company LinkedIn: www.linkedin.com/company/amela-biosciences-ag Sandra’s LinkedIn: www.linkedin.com/in/sandra-nunez-ch Sandra’s email: [email protected] Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here Support the show