Smart Biotech Scientist | The CMC and Bioprocessing Podcast for Process Development and Manufacturing Leaders

David Brühlmann - CMC Development Leader, Bioprocess Expert, Business Strategist
  • 5.0 (10)
  • Life Sciences
  • Weekly

The go-to CMC and biomanufacturing podcast for bioprocess development scientists and CMC leaders scaling biologics into regulatory-ready therapies with less trial and error. Practical, execution-focused, and strategic guidance on CMC development, tech transfer, scale-up, GMP readiness, CDMO partnerships, and manufacturing economics for biologics, cell and gene therapies, cultivated meat, and biomaterials. Hosted by Dr. David Brühlmann, CMC strategist, former Bioprocess Innovation Manager at Merck, PhD in glycoengineering, and close to 20 years of biomanufacturing experience. Smart Biotech Scientist delivers actionable insights for the people doing the hard work of turning promising molecules into scalable, regulatory-ready therapies. This podcast is for you if: You are a process development scientist or CMC lead managing a technology transfer, scale-up, or CDMO partnership You are a biologics developer working on upstream or downstream process development, cell culture optimization, or GMP manufacturing readiness You are a biotech founder preparing for an IND filing or Series A fundraise, and need a CMC strategy that holds up under investor and regulatory scrutiny You are building or advising an early-stage biopharma team and need to make smart manufacturing decisions with limited resources What you will learn: CMC strategy and regulatory planning, bioprocess scale-up from lab to clinical and commercial manufacturing, cell culture process development and media optimization, technology transfer best practices, CDMO selection and partnership management, hybrid modeling, manufacturing economics, continuous manufacturing, digitization, and Industry 4.0 in biopharma. Top 10 life sciences podcast with 200+ episodes and guests from Merck, FUJIFILM Irvine Scientific, Cytiva, KBI Biopharma, Eppendorf, and biotech innovators worldwide. New episodes released weekly. Subscribe and join 400+ biotech leaders already using these insights to accelerate development, reduce manufacturing costs, and de-risk scale-up. Next Steps: Get the 5-day CMC email course: https://smartbiotechscientist.com/#cmc Visit the website: https://smartbiotechscientist.com Email us: hello@bruehlmann-consulting.com

  1. 13h ago

    300: Where Bioprocess Models Deliver and Where They Overpromise: Choosing Between Hybrid, Mechanistic, and Machine Learning with Moritz von Stosch - Part 2

    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

  2. 2d ago

    299: Where Bioprocess Models Deliver and Where They Overpromise: Choosing Between Hybrid, Mechanistic, and Machine Learning with Moritz von Stosch - Part 1

    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

  3. Oct 22

    298: 10,000 Structures Are Not Enough: The Data Gap Limiting De Novo Antibody Design with David Younger - Part 2

    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

  4. Oct 20

    297: 10,000 Structures Are Not Enough: The Data Gap Limiting De Novo Antibody Design with David Younger - Part 1

    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

  5. Oct 15

    296: Neither Small Molecule nor Biologic: The Cyclodextrin Dimer CMC Challenge with Matthew O'Connor - Part 2

    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: matthew.oconnor@cyclaritytx.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

  6. Oct 13

    295: Neither Small Molecule nor Biologic: The Cyclodextrin Dimer CMC Challenge with Matthew O'Connor - Part 1

    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: matthew.oconnor@cyclaritytx.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

  7. Oct 8

    294: Is CFD Overkill for Your Scale-Up? Why It Belongs in Every Biotech Scientist's Toolkit with Christian Witz - Part 2

    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: christian.witz@simvantage.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

  8. Oct 6

    293: Is CFD Overkill for Your Scale-Up? Why It Belongs in Every Biotech Scientist's Toolkit with Christian Witz - Part 1

    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: christian.witz@simvantage.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

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The go-to CMC and biomanufacturing podcast for bioprocess development scientists and CMC leaders scaling biologics into regulatory-ready therapies with less trial and error. Practical, execution-focused, and strategic guidance on CMC development, tech transfer, scale-up, GMP readiness, CDMO partnerships, and manufacturing economics for biologics, cell and gene therapies, cultivated meat, and biomaterials. Hosted by Dr. David Brühlmann, CMC strategist, former Bioprocess Innovation Manager at Merck, PhD in glycoengineering, and close to 20 years of biomanufacturing experience. Smart Biotech Scientist delivers actionable insights for the people doing the hard work of turning promising molecules into scalable, regulatory-ready therapies. This podcast is for you if: You are a process development scientist or CMC lead managing a technology transfer, scale-up, or CDMO partnership You are a biologics developer working on upstream or downstream process development, cell culture optimization, or GMP manufacturing readiness You are a biotech founder preparing for an IND filing or Series A fundraise, and need a CMC strategy that holds up under investor and regulatory scrutiny You are building or advising an early-stage biopharma team and need to make smart manufacturing decisions with limited resources What you will learn: CMC strategy and regulatory planning, bioprocess scale-up from lab to clinical and commercial manufacturing, cell culture process development and media optimization, technology transfer best practices, CDMO selection and partnership management, hybrid modeling, manufacturing economics, continuous manufacturing, digitization, and Industry 4.0 in biopharma. Top 10 life sciences podcast with 200+ episodes and guests from Merck, FUJIFILM Irvine Scientific, Cytiva, KBI Biopharma, Eppendorf, and biotech innovators worldwide. New episodes released weekly. Subscribe and join 400+ biotech leaders already using these insights to accelerate development, reduce manufacturing costs, and de-risk scale-up. Next Steps: Get the 5-day CMC email course: https://smartbiotechscientist.com/#cmc Visit the website: https://smartbiotechscientist.com Email us: hello@bruehlmann-consulting.com

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