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 Baker
• Episodes 221 - 222: From 2D Cultures to Advanced 3D Cell Models for Preclinical Research with Catarina Brito
• Episodes 275 - 276: From Lab-Scale Molding to GMP: Manufacturing a Collagen Implant for the Clinic with Eva-Maria Balet
• Episodes 279 - 280: Why Nanovesicles Outperform Exosomes: Scalable Drug Delivery Beyond Injectable Vaccines with Christopher Locher

Connect 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

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Batch-to-batch variability isn’t just a minor annoyance in bioprocess development; it’s often a systemic design flaw hiding in plain sight.

That’s the challenge Sandra Núñez, CEO of Amela Biosciences, set out to eliminate. Drawing on 15 years across Lonza, Medinova, Baxalta, and Biogen, she’s engineered a new generation of animal-free, recombinant protein matrices that promise researchers experimental consistency on demand.

Topics discussed:

• The widespread issue of batch-to-batch variability and why Sandra argues it’s a design failure, not the norm (02:49)
• The mechanics and biological tunability of Amela’s engineered protein matrices, and how this technology works (06:34)
• How Amela’s recombinant protein bioinks differ from traditional animal-sourced extracts, enabling reproducibility (08:53)
• Manufacturing insights: why the proteins are relatively straightforward to produce for research use (12:05)
• Engaging with users to optimize and customize protein matrices for diverse tissue and assay applications (13:33)
• The creation and use of protein libraries for specific user requirements and the flexibility this provides (16:20)
• Definitions and roles of ‘bioinks’ in tissue modeling and 3D cell culture (16:52)

Smart insight: Reproducibility remains the cornerstone of reliable science. With innovative platforms like Amela Biosciences’ engineered protein matrices, the future of tissue engineering and in vitro biology looks not just reliable, but radically empowering. If you’re striving for consistency, customizability, and cutting-edge technology in your workflows, the era of animal-free, batch-consistent bioinks has arrived.

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 Baker
• Episodes 221 - 222: From 2D Cultures to Advanced 3D Cell Models for Preclinical Research with Catarina Brito
• Episodes 275 - 276: From Lab-Scale Molding to GMP: Manufacturing a Collagen Implant for the Clinic with Eva-Maria Balet
• Episodes 279 - 280: Why Nanovesicles Outperform Exosomes: Scalable Drug Delivery Beyond Injectable Vaccines with Christopher Locher

Connect 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

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Manufacturability challenges in biotech are becoming more complex as therapies become more potent, formats diversify, and timelines compress across the industry.

On this episode, David Brühlmann sits down with Sigma Mostafa, Chief Scientific and Technology Officer at KBI Biopharma. Sigma brings deep expertise in early-stage CMC decision-making and has guided countless programs—from upstart startups to established pipelines—through the traps and trade-offs of process development. Her ground-floor perspective spans in silico modeling, innovative cell line engineering, and the gritty realities of tech transfer.

Key topics discussed:

• Practical advice for startups on selecting robust cell lines and avoiding long-term lock-in to problematic platforms (03:07)
• Managing risks in process development, such as high oxygen demand and filter loading, before tech transfer to manufacturing (04:47)
• The value of pressure testing bioprocesses at scale and identifying potential failure modes, including filter clogging and narrow feeding windows (07:41)
• Balancing speed, robustness, and regulatory expectations when advancing new molecules (09:23)
• How fast-tracking from transfection to IND is changing timelines, and the associated risks of accelerated development (09:54)
• Trends and caution in applying AI and in silico tools to protein and process modeling, and the limits of digital solutions (12:01)
• What first-time founders need to get right, including early analysis of molecular issues and careful cell line selection (15:48)
• Shifting modality trends—growing numbers of ADCs/XDCs, more complexity, and the move toward smaller scale and more potent molecules (16:55)
• The overarching lesson: invest early in the areas you cannot change later—especially cell line and understanding of molecule challenges (18:23)

Smart insight: Startup founders often wonder which fires to fight first. Sigma’s advice: focus on deep molecular assessment and making informed, scalable cell line choices above all else. These are the “few things you cannot change later” and the investments that separate enduring programs from cautionary tales.

This episode unpacks what that means in practice and where speed and robustness pull against each other. If it resonated, these conversations expand the picture: how to spot manufacturable candidates early, how in silico tools predict stability and aggregation before the lab, and which early CMC decisions quietly become permanent.

• Episodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan Sharfstein
• Episodes 213 - 214: From Developability to Formulation: How In Silico Methods Predict Stability Issues Before the Lab with Giuseppe Licari
• Episodes 231 - 232: From IND to BLA: The Biologics CMC Decisions That Determine Regulatory Success with Henri Kornmann
• Episodes 103 - 104: One-Stop Shop vs. Specialist CDMO: A Scientist's Guide to CDMO Selection with Sigma Mostafa

Connect with Sigma Mostafa:
 Linkedin: https://www.linkedin.com/in/sigma-mostafa-79180817
KBI website: https://www.kbibiopharma.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

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A breakthrough in drug discovery can be derailed in an instant if manufacturability is left as an afterthought. Too many biotech programs hit bottlenecks at scale-up because key decisions in cell line and process development get kicked down the road.

On the Smart Biotech Scientist Podcast, David Brühlmann spoke with Sigma Mostafa, Chief Scientific and Technology Officer at KBI Biopharma. She’s spent 25+ years converting early-stage discoveries into commercial biomanufacturing success and she’s adamant: manufacturability decisions belong at the candidate selection stage, not after.

Topics discussed:

• Why manufacturability should be assessed at the candidate selection stage, not later (03:02)
• Sigma’s background in bringing math and biology together and her path into bioprocess engineering (04:18)
• The "art" and complexity of bioprocess development, especially with new molecule types (05:54)
• A case study of how switching cell lines revealed hidden manufacturability issues (07:33)
• Key properties affecting manufacturability, such as aggregation and thermal stability (10:10)
• Reasons companies delay manufacturability assessments—timing pressure, costs, and lack of early deep characterization (11:02)
• Why CMC should be integrated from day one and concerns with treating scalability as 'just' engineering (12:08)
• Critical decisions and pitfalls in cell line development, including robustness, media choices, and adapting after the master cell bank is made (12:48)
• Regulatory aspects of cell line development: demonstrating clonality, avoiding animal source materials, and documentation requirements (15:04)

Smart insight: Manufacturability is not just a box for the CMC team. It’s a proactive mindset, to be embraced from day one. Early, cross-functional scrutiny—examining both molecule and cell line—preempts disasters during scale-up and accelerates timelines to market while minimizing costly surprises.

This episode unpacks what that means in practice and where speed and robustness pull against each other. If it resonated, these conversations expand the picture: how to spot manufacturable candidates early, how in silico tools predict stability and aggregation before the lab, and which early CMC decisions quietly become permanent.

• Episodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan Sharfstein
• Episodes 213 - 214: From Developability to Formulation: How In Silico Methods Predict Stability Issues Before the Lab with Giuseppe Licari
• Episodes 231 - 232: From IND to BLA: The Biologics CMC Decisions That Determine Regulatory Success with Henri Kornmann
• Episodes 103 - 104: One-Stop Shop vs. Specialist CDMO: A Scientist's Guide to CDMO Selection with Sigma Mostafa

Connect with Sigma Mostafa:
 Linkedin: https://www.linkedin.com/in/sigma-mostafa-79180817
KBI website: https://www.kbibiopharma.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

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What does it take to crack the code of protein production and why do some proteins stubbornly refuse to cooperate, despite the best efforts of scientists and engineers? Biotech’s ambitions are often limited not by vision, but by the real-world bottlenecks of host cell lines and the unpredictability of post-translational modifications.

Nathan Lewis, GRA Eminent Scholar at the Center for Molecular Medicine, Complex Carbohydrate Research Center, and Department of Biochemistry and Molecular Biology at the University of Georgia, has made a career out of asking impossible questions about glycosylation, cell line selection, and the hidden machinery at work inside every productive cell. He’s moved beyond academic curiosity—translating discoveries into applications and even launching a company, Augment Biologics, that’s taking glycoengineering from theory to practice.

Topics discussed:

• A proximity proteomics approach to identify supporting machinery for challenging-to-express proteins like rituximab (02:36)
• Findings from expressing the full human secretome in CHO cells, and the correlation between host cell gene expression and protein productivity (05:00)
• Clarifying when host cell characteristics matter more than the protein construct itself (05:46)
• Emerging evidence that protein sequence and structure influence glycosylation patterns (contrary to previous dogma) (06:49)
• Engineering point mutations to precisely tune glycan features for improved therapeutic efficacy (09:25)
• The vision and activities of Augment Biologics in custom glycosylation control for drug discovery (10:32)
• The importance and barriers to open data sharing in bioprocessing, and thoughts on overcoming them (11:11)
• The shifting landscape as technology advances and the need for high-quality, annotated data (13:54)

If this got you thinking about the data already sitting in your freezer, and what it would take to actually use it, start here. These four conversations dig into AI-ready data, actionable omics, hybrid-model digital twins, and the cell-engineering biology underneath it all.

• Episodes 263 - 264: Why AI and Automation Tools Won't Deliver Until Your Lab's Data Is Connected with David Hardy
• Episodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist Gernaey
• Episodes 169 - 170: Why Your DNA Is a Terrible Disease Predictor (And How Multi-Omics Changes Everything) with Mo Jain
• Episodes 77 - 78: Cell Factories Explained: How Synthetic Biology and AI Revolutionize Protein Production with Mauro Torres

If you'd rather follow the glycosylation thread, check Episodes 69 - 70: Glycoanalytics Explained with Róisín O'Flaherty

Connect with Nathan Lewis:
Website: www.lewislab.uga.edu
LinkedIn: www.linkedin.com/in/nathanelewis

Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here

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Dormant omics data are a goldmine for CMC innovation waiting to be unlocked. But legacy structures, poor annotation, and spreadsheet chaos hold most biotech teams back from the real breakthroughs.

Nathan Lewis, GRA Eminent Scholar at the Center for Molecular Medicine, Complex Carbohydrate Research Center, and Department of Biochemistry and Molecular Biology at the University of Georgia, has a clear message: actionable data is now within reach thanks to hybrid modeling, advanced study design, and AI as a true scientific collaborator.

Topics discussed:

• Rethinking the dogma: controlling protein glycosylation quality from the inside out, not just by bioprocess conditions (03:00)
• Nathan Lewis’s journey into science and bioprocessing, from unexpected college choices to pivotal advances in CHO cell engineering (05:12)
• The evolution of omics in bioprocessing: why actionable insights, not just big datasets, should be the goal (10:49)
• Strategic advice for structuring, annotating, and making old and new datasets ready for AI and LLM analysis (17:34)
• The balance between mechanistic and machine learning models—when each makes sense, and why hybrid modeling is gaining ground (22:20)
• The current and future role of digital twins in process development and why foundation models and data consortia matter for scalability (26:24)

Smart insight: The real revolution isn’t in making new data, but in unlocking the value of what already exists. Advances in AI, hybrid modeling, and collaborative standards promise to turn decades-old data into a catalyst for innovation—enabling faster, smarter, and more reliable bioprocess development.

If this got you thinking about the data already sitting in your freezer — and what it would take to actually use it — start here. These four dig into AI-ready data, actionable omics, hybrid-model digital twins, and the cell-engineering biology underneath it all.

• Episodes 263 - 264: Why AI and Automation Tools Won't Deliver Until Your Lab's Data Is Connected with David Hardy
• Episodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist Gernaey
• Episodes 169 - 170: Why Your DNA Is a Terrible Disease Predictor (And How Multi-Omics Changes Everything) with Mo Jain
• Episodes 77 - 78: Cell Factories Explained: How Synthetic Biology and AI Revolutionize Protein Production with Mauro Torres

If you'd rather follow the glycosylation thread, check Episodes 69 - 70: Glycoanalytics Explained with Róisín O'Flaherty

Connect with Nathan Lewis:
Website: www.lewislab.uga.edu
LinkedIn: www.linkedin.com/in/nathanelewis

Free 5-day email course, The CMC Failure Chain: the five recurring CMC mistakes that put your promising program at risk → Get it here

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“Does DNA barcoding actually work?” It's the first question Kent Rapp hears from prospective customers when he pitches Biolinco's DNA barcoding platform. By his own admission, the technology can sound too good to be true.

In Part 2 of this conversation, Kent rejoins the Smart Biotech Scientist Podcast to address that skepticism head-on, unpack how subclone variability and bispecific antibody purity concerns shape customer trust, and share what it actually took to move Biolinco from a Johns Hopkins postdoc project to a company with its first paying customer.

In this episode:

• Common pushbacks and questions from industry regarding new cell line development technologies (03:18)
• Practical advice for resource-constrained startups developing cell lines, emphasizing efficiency and data quality over brute force automation (08:42)
• The role and value of DNA barcoding in screening and developing robust cell lines for therapeutics (08:56)
• Lessons learned from translating scientific innovation into a commercial product, including securing early support and customer trust (10:27)
• Insights on adapting messaging, leveraging feedback, and understanding market needs as part of the entrepreneurial process (13:52)
• Key differences between academic research and industry requirements for reliable, repeatable biotech tools (15:26)
• Kent’s most important takeaway for successful cell line development: focus on collecting the right data at the right scale for informed decisions (17:14)

Smart insight: Translating innovations from academia to industry brings a new wave of challenges. Kent describes the “valley of death” separating a publishable prototype from a reliable, commercial-grade product. Academic success is often tied to novelty, publications, and grants, while industry demands repeatability, robustness, and consistent performance across labs and operators. Securing early champions and funding, iterating based on tough industry feedback, and building trust with initial partners all require resilience, and a willingness to pivot as needed. Feedback, even when harsh, becomes a “gift” that helps refine the product and business model. The secret is not a single breakthrough, but adaptability and relentless customer focus.

If this got you rethinking how you screen clones, you'll want these next. We've tackled cell line development, high-throughput screening, and the art of spotting manufacturable candidates early from a few different directions — here are four worth queuing up.

• Episodes 117 - 118 : Cell Line Development Secrets: Eliminating Critical Bottlenecks for Faster Timelines with Andrea Gough
• Episodes 09 - 10: Revolutionizing Cell-Line Development: Unleashing the Power of Nanopens and Microenvironments with Tanner Nevill
• Episodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan Sharfstein
• Episodes 115 - 116: Revolutionizing Biologics Development with Hyper Throughput Screening and AI with Jeremy Agresti

Connect with Kent Rapp:
LinkedIn: www.linkedin.com/in/kent-rapp
Biolinco website: www.biolinco.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

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What if the bottleneck in cell line development isn’t how many clones you screen, but how you track them?

Cloning workflows have long relied on brute force: screen more cells, automate harder, and hope that small-scale performance predicts manufacturability. But too often, the “perfect” clone in a 96-well plate turns into a dud when it reaches the bioreactor. That disconnect costs time, money, and promising therapies.

This week, host David Brühlmann welcomes Kent Rapp, Co-founder and CEO of Biolinco, an entrepreneur who’s turning the classic approach to cell line development inside out. Drawing from his background in chemical engineering and his work in biomanufacturing at Johns Hopkins University, Kent teamed up with DNA barcoding experts to pioneer a new workflow: barcode every cell, pool them, and track their true performance in the environment that matters.

Topics discussed:

• The pitfalls of brute-force screening in traditional cell line development (03:05)
• Kent’s background and how he was drawn to combine science, startups, and biomanufacturing (04:37)
• Overcoming discrepancies between small-scale and large-scale screening environments (08:30)
• How DNA barcoding allows for high-resolution, pooled clone screening (10:34)
• Sensitivity advantages of sequencing over plate-based detection (14:21)
• Methodology for tracking and recovering individual high-performing clones from pools (15:13)
• Impact on speed and workflow efficiency in cell line development (17:31)
• Regulatory and safety considerations related to DNA barcodes in cell lines (19:04)

Smart insight: According to Kent, biotech as an industry has a tendency to "automate problems instead of solve them". Rather than addressing the root causes—like lack of meaningful measurements at relevant scales—companies often throw more robots and more plates at the issue, hoping brute force will finally yield the magical clone. But real process improvement requires a rethinking of what is being measured and how those insights are generated—not just a higher throughput of the same flawed assay.

If this got you rethinking how you screen clones, you'll want these next. We've tackled cell line development, high-throughput screening, and the art of spotting manufacturable candidates early from a few different directions — here are four worth queuing up.

• Episodes 117 - 118 : Cell Line Development Secrets: Eliminating Critical Bottlenecks for Faster Timelines with Andrea Gough
• Episodes 09 - 10: Revolutionizing Cell-Line Development: Unleashing the Power of Nanopens and Microenvironments with Tanner Nevill
• Episodes 123 - 124: Manufacturability: Why Most Protein Candidates Fail (And How to Pick Winners Early) with Susan Sharfstein
• Episodes 115 - 116: Revolutionizing Biologics Development with Hyper Throughput Screening and AI with Jeremy Agresti

Connect with Kent Rapp:
LinkedIn: www.linkedin.com/in/kent-rapp
Biolinco website: www.biolinco.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

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Your active ingredient is the nucleic acid. So why does a proteolipid vehicle filing include viral clearance studies, stability data and full characterisation of a membrane protein that is not the drug? Because that protein sits on the particle surface, and a component nobody has filed before is the agency's problem regardless of what you call it.

Proteolipid vehicles (PLVs), the platform Jitendra Kumar works on as Lead Scientist for Chemistry and Process Development at Entos Pharmaceuticals, represent a novel frontier in drug delivery, Instead of being taken up into an endosome and having to escape it, a PLV fuses with the cell membrane and releases cargo straight into the cytosol. That opens targets and patient groups that liver-tropic lipid nanoparticles and viral vectors have struggled to reach, and it leaves Kumar building a regulatory file with nothing on the shelf to copy.

Highlights from the episode:

• Strategies for communicating novel technology with regulatory agencies and ensuring robust science-driven submissions (02:34)
• What differentiates the analytical characterization of PLVs compared to standard recombinant proteins or antibodies (04:03)
• The development plan and regulatory pathway towards clinical and commercial approval for their lead leptin therapy (05:35)
• The evolving role of advanced techniques—such as cryo-EM—in supporting regulatory filings and product understanding (06:56)
• Jitendra Kumar's career journey: from agricultural research in India to protein science and neurodegeneration, and how these experiences inform current PLV technology development (09:00)
• Challenges of early diagnostics and product development in neurodegenerative diseases (14:29)
• Decision-making differences and focus in academic versus industry biotech research (15:32)
• Practical advice on the importance of honest technology assessment, building networks, and understanding both strengths and weaknesses (16:16)

Smart insight: A persistent challenge for groundbreaking delivery systems is the lack of established regulatory playbooks. Jitendra Kumar laid out a science-first approach: let data do the talking, supported by rigorous GLP toxicology studies and transparent communication with agencies. Regulatory bodies like Health Canada are receptive to innovation, provided that sponsors demonstrate safety, efficacy, and scientific rationale for any deviation from standard criteria.

If this conversation got you thinking about how novel delivery vehicles reach the cell — and what it takes to carry one from bench through CMC, scale-up, and regulatory review — these four episodes go deeper:

• Episodes 125 - 126: How to Enhance Cell Engineering Using Mechanical Intracellular Delivery with Armon Sharei
• Episodes 231 - 232: From IND to BLA: The Biologics CMC Decisions That Determine Regulatory Success with Henri Kornmann
• Episodes 89 - 90: Scale-Up Secrets: Cracking the Code of AAV Production with Ahmed Youssef
• Episodes 71 - 72: Effective Outsourcing: How Small Biotech Companies Can Thrive with Mark Melville

Connect with Jitendra Kumar:

• LinkedIn: www.linkedin.com/in/jkumar2
• Email: [email protected]
• Website: www.entospharma.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

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Gene therapy only works if the cargo reaches the right cells intact. Adeno-associated viruses (AAV) and lipid nanoparticles have carried the field this far, but both share a constraint: the particle is taken up into an endosome, and the payload has to escape that compartment before it is degraded. Endosomal escape is where a large share of the dose is lost, and it is why delivery, not the genetic construct, is usually the thing that limits the therapy. Lipid nanoparticles carry a second constraint, since they tend to accumulate in the liver, which narrows the diseases they can reach. What if the particle never entered that way at all?

Jitendra Kumar, Lead Scientist for Chemistry and Process Development at Entos Pharmaceuticals, works on a platform that fuses directly with the cell membrane and releases its cargo straight into the cytosol. He came to nanoparticle design the long way, through fifteen years of structural biology on the prion protein in Frankfurt and Edmonton, which is why he thinks about particle size, packaging and diffusion the way he does.

Key topics discussed:

• Jitendra’s career background in structural biology and journey to Entos Pharmaceuticals (03:18)
• The scientific motivation and challenges of working with prion proteins and breaking down complex diseases (04:55)
• Genetic medicine approaches: gain-of-function vs. loss-of-function, and the role of siRNA, ASOs, and gene delivery (06:27)
• The FAST protein platform: origins, function, and advantages for drug delivery (07:56)
• Manufacturing differences compared to LNPs, including the introduction of recombinant membrane protein production and related CMC complexity (09:55)
• Scale-up and production challenges for membrane proteins, and strategies for clinical supply (11:21)
• Clinical development progress: Phase 1/2 studies with the platform, especially for COVID vaccine delivery (12:23)
• Focus areas for the technology, including selective lung delivery and leptin therapy for lipodystrophy (13:12)
• Lessons for small biotech companies in phase 1/2 manufacturing strategy, technology transfer, and the value of an experienced network (14:31)
• Balancing process robustness with speed in new biotech ventures (16:02)
• The importance of identifying “pause steps” and must-have vs. nice-to-have features in early manufacturing processes (17:15)

Smart insight: Jitendra’s takeaway for startups: for early phases, find a partner who genuinely understands your tech and can move at your pace rather than defaulting to a big CDMO, treat your network as infrastructure, and build the ability to run production in-house. The one thing that's never up for negotiation is process robustness. The real question isn't robustness vs. speed, but how many checkpoints and safe pause points you build in so you can have both.

If this conversation got you thinking about how novel delivery vehicles reach the cell — and what it takes to carry one from bench through CMC, scale-up, and regulatory review — these four episodes go deeper:

• Episodes 125 - 126: How to Enhance Cell Engineering Using Mechanical Intracellular Delivery with Armon Sharei
• Episodes 231 - 232: From IND to BLA: The Biologics CMC Decisions That Determine Regulatory Success with Henri Kornmann
• Episodes 89 - 90: Scale-Up Secrets: Cracking the Code of AAV Production with Ahmed Youssef
• Episodes 71 - 72: Effective Outsourcing: How Small Biotech Companies Can Thrive with Mark Melville

Connect with Jitendra Kumar:

• LinkedIn: www.linkedin.com/in/jkumar2
• Email: [email protected]
• Website: www.entospharma.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