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

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 Castan
• Episodes 183 - 184: From Lab to Market: Secrets to Commercializing Cutting-Edge Biotech Innovations with Chervee Ho
• Episodes 259 - 260: Why Strong Science Isn't Enough to Get Funded: What Investors Actually Look For with Michael Rome
• Episodes 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

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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 Castan
• Episodes 183 - 184: From Lab to Market: Secrets to Commercializing Cutting-Edge Biotech Innovations with Chervee Ho
• Episodes 259 - 260: Why Strong Science Isn't Enough to Get Funded: What Investors Actually Look For with Michael Rome
• Episodes 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 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

Support the show

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

Support the show

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

Support the show

“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

Support the show

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

Support the show