For generations, silkworm pupae were discarded as waste from silk production. Now, KAICO is proving these organisms can function as highly efficient protein factories—producing complex vaccine antigens at yields and costs that challenge conventional bioreactor-based manufacturing. With a PCV2 oral vaccine already registered in Vietnam and a human norovirus vaccine preparing for Phase I clinical trials, the silkworm platform is moving from proof-of-concept to commercial reality.

In Part 2, Masafumi Osawa, Business Development Lead at KAICO, walks us through the company's product pipeline, the regulatory landscape for this unprecedented platform, and why silkworm-based manufacturing could reshape global vaccine accessibility. From farm-scale validation to regulatory dialogue with Japan's PMDA, this episode bridges platform science with product development.

Stops along our Silk Road to biomanufacturing

• KAICO’s approach to expressing complex proteins, including oral and injectable vaccines for animals and clinical-stage human health products (00:40)
• Immune-enhancing feed additive for pigs against PCV2 (registered in Vietnam), companion animal products, and human norovirus vaccine entering Phase 1 trials (02:50)
• Advantages of silkworm-produced antigens for both injectable and oral vaccines, and comparison to plant-based systems (04:57)
• How silkworm production enables rapid scale-out and high-yield protein expression for global accessibility (05:34)
• Speed of vaccine development with the silkworm platform—example with SARS-CoV-2 recombinant protein produced in three months (08:08)
• Key regulatory differences between animal and human vaccine development, including country-specific classification and global harmonization efforts (09:14)
• Sustainability and distributed manufacturing potential of silkworm-based systems (11:10)
• Milestones toward the first human biologic produced in silkworms, with phase 1 trials starting soon (12:27)
• Protein yield per silkworm pupae—scalability advantages compared to conventional bioreactor approaches (14:04)
• Masafumi Osawa’s thoughts on the future of silkworm-based biologics: from democratized therapies to personalized medicines (15:15)

Want to know if silkworms can solve your tough protein expression problems? Tune in now to learn how KAICO’s biotech is set to redefine what’s possible for vaccine development, and how their distributed, cost-effective approach could open doors across sectors.

Connect with Masafumi Osawa,:

LinkedIn: www.linkedin.com/in/masa-osawa

KAICO Ltd.: www.kaicoltd.jp/en

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For over 4,000 years, silkworms have connected civilizations through ancient trade routes. Now, KAICO Ltd., a Japanese biotech spin-off from Kyushu University, is transforming these creatures into living bioreactors capable of producing complex recombinant proteins and vaccine antigens—without the bioreactors, expensive media, or massive water consumption of conventional platforms.

Masafumi Osawa, Business Development Lead at KAICO, brings an unconventional path to biotech. Trained in cultural anthropology with fieldwork experience in Indonesia, he witnessed firsthand the healthcare disparities that drive his current mission. After years in pharmaceutical business development at Towa Pharmaceutical, he joined KAICO to help scale a technology he believes could reshape global vaccine accessibility. His cross-cultural expertise now proves invaluable as KAICO expands internationally, with active partnerships in Vietnam and Thailand and growing interest from other regions.

Episode highlights:

• Masafumi’s transition from anthropology to biotech, and how cross-cultural expertise benefits global health collaborations. (04:15)
• The founding story of KAICO, spun out from Kyushu University and focused on recombinant proteins and vaccine antigen production (08:45)
• Step-by-step overview of the silkworm baculovirus expression system, including pupae handling and bioprocessing basics. (10:28)
• Practical differences between silkworms, E. coli, mammalian, and insect cell culture platforms—exploring advantages and drawbacks. (13:10)
• Strategies KAICO uses to control silkworm variability, including SPF grade sourcing, diet, environment, and documentation for pharmaceutical acceptance. (15:08)
• Production scalability: a single pupa can match 100–1000 ml of insect cell culture, with major implications for cost and environmental footprint. (16:42)
• Downstream harvesting and purification—how KAICO extracts and processes proteins from silkworm pupae, keeping methods largely familiar to traditional systems. (19:31)
• Regulatory and GMP challenges of using live organisms, and KAICO’s approach to satisfying authorities and ensuring product consistency. (21:43)

Whether you’re curious about alternative biomanufacturing methods or want a transparent look at silkworm-based protein expression from research to the clinic, this episode delivers practical insights and thoughtful discussion.

Connect with Masafumi Osawa:

LinkedIn: www.linkedin.com/in/masa-osawa

KAICO Ltd.: www.kaicoltd.jp/en

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One bad CDMO decision can cost you two years and your Series A. If you're navigating tech transfer, CDMO selection, or IND prep, let's talk before it gets expensive. Two slots open this month.

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Biomanufacturing has always dealt with the challenge of turning vast, complex datasets and intricate production steps into life-changing therapies. But when batch records multiply and process deviations loom, how do biotech teams make sense of it all? In this episode, we move beyond theory to the nuts and bolts of how AI - when thoughtfully deployed - can turn bioprocessing chaos into actionable intelligence, paving the way for the factory of the future.

Our guest, Ilya Burkov, Global Head of Healthcare and Life Sciences Growth at Nebius AI, doesn’t just talk about data wrangling and algorithms—he’s spent years building tools and strategies to help scientists organize, contextualize, and leverage real-world datasets. Having worked across tech innovation and pharmaceuticals, Ilya Burkov bridges cutting-edge computation with the practical realities of CMC development and manufacturing, making him a trusted voice on how bioprocessing is rapidly changing.

Highlights from the episode:

• Advice for biotech scientists on learning from innovations in other industries (00:02:21)
• Tackling the complexities of organizing huge and often unstructured datasets in bioprocessing (03:08)
• Techniques and tools to structure, label, and prepare data for AI—including Nebius’s in-house tool, Tracto AI (06:24)
• Strategies for startups and small teams—how to begin implementing AI and what areas of bioprocessing to focus on first (10:12)
• The vision for the “factory of the future”: AI-driven, interconnected, and self-learning manufacturing environments (08:11)
• Navigating the decision between on-premise and cloud computing for scalable, cost-effective AI workloads (12:32)
• The importance of partnership between scientists and AI, emphasizing collaboration and data-driven decisions (00:15:47)

Wondering how to kick off your own AI-enabled bioprocessing project, or what to insource versus outsource as you scale? This episode gives you a grounded starting point—minus the buzzwords and empty promises.

Connect with Ilya Burkov:

LinkedIn: www.linkedin.com/in/ilyaburkov

Contact email: ilya.burkov@nebius.com

Nebius: www.nebius.com

If this topic grabbed you, you'll love these related episodes focusing on advanced modeling, continuous manufacturing, and Digital Twins

• Episodes 213 - 214: From Developability to Formulation: How In Silico Methods Predict Stability Issues Before the Lab with Giuseppe Licari
• Episodes 85 - 86: Bioprocess 4.0: Integrated Continuous Biomanufacturing with Massimo Morbidelli
• Episodes 05 - 06: Hybrid Modeling: The Key to Smarter Bioprocessing with Michael Sokolov
• Episode 153 - 154: The Future of Bioprocessing: Industry 4.0, Digital Twins, and Continuous Manufacturing Strategies with Tiago Matos
• Episodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist Gernaey

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Across biotech labs, researchers swim in oceans of process data: sensor streams, run records, engineering logs, and still, crucial decisions get stuck in spreadsheets or scribbled into fading notebooks. The challenge isn’t having enough information, it's knowing which actions actually move the needle in cell culture productivity, process stability, and faster timelines.

This episode, David Brühlmann brings on Ilya Burkov, Global Head of Healthcare and Life Sciences Growth at Nebius AI. With a career spanning NHS medicine, regenerative research, and cloud infrastructure, Ilya Burkov has lived the leap from microscope to server room. He’s seen firsthand how digital twins, autonomous experimentation, and cloud-first strategies are shifting the way biologics are developed and scaled.

Topics discussed:

• Shifting from experimental-based to computational bioprocess development, and the evolving role of human expertise vs. AI (02:48)
• Ilya Burkov's journey from medicine and orthopedics to AI and cloud infrastructure (04:15)
• Solving data silos and making real-time decisions with digital twins and automated analytics (06:36)
• The impact of AI-driven lab automation and robotics on drug discovery timelines (08:51)
• Using AI to accelerate cell line selection, cloning, and protein sequence optimization (10:12)
• Why wet lab experimentation is still essential, and how predictive modelling can reduce failure rates (11:15)
• Reducing costs and accelerating development by leveraging AI in process screening and optimization (12:32)
• Strategies for smaller companies to effectively store and manage bioprocess data, including practical advice on cloud adoption and security (14:30)
• Application of AI and digital twins in scale-up processes, and connecting diverse data types like CFD simulations and process data (17:18)
• The ongoing need for human expertise in interpreting and qualifying data, even as machine learning advances (19:09)

Wondering how to stop your own data from gathering dust? This episode unpacks practical strategies for storing and leveraging your experimental records - whether you’re in a major pharma or a small startup with limited tech resources.

Connect with Ilya Burkov:

LinkedIn: www.linkedin.com/in/ilyaburkov

Contact email: ilya.burkov@nebius.com

Nebius: www.nebius.com

If this topic grabbed you, you'll love these related episodes focusing on advanced modeling, continuous manufacturing, and Digital Twins

• Episodes 213 - 214: From Developability to Formulation: How In Silico Methods Predict Stability Issues Before the Lab with Giuseppe Licari
• Episodes 85 - 86: Bioprocess 4.0: Integrated Continuous Biomanufacturing with Massimo Morbidelli
• Episodes 05 - 06: Hybrid Modeling: The Key to Smarter Bioprocessing with Michael Sokolov
• Episode 153 - 154: The Future of Bioprocessing: Industry 4.0, Digital Twins, and Continuous Manufacturing Strategies with Tiago Matos
• Episodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist Gernaey

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Support the show

Computational methods can predict stability issues before the lab. But how do you actually implement these approaches in your formulation workflow? From excipient selection to long-term stability prediction, in silico tools are transforming how biotech teams develop robust formulations while reducing costly trial-and-error cycles.

In Part 2, Giuseppe Licari, Principal Scientist in Computational Structural Biology at Merck KGaA, returns to share practical implementation strategies for integrating computational methods into biologics formulation development. Giuseppe reveals how molecular dynamics simulations guide excipient selection, where current methods hit their limits, and how emerging AI capabilities are expanding what's possible in formulation prediction.

Whether you're at a well-resourced pharma company or a lean startup, Giuseppe offers actionable guidance for leveraging computational tools to predict protein behavior, optimize formulations, and accelerate your development timeline.

Topics covered:

• Predicting protein aggregation and excipient interactions before manufacturing (00:45)
• Using molecular dynamics to understand protein behavior over time and in different environments (03:03)
• The interplay between computational predictions and experimental stability studies (04:49)
• The limitations of current in silico methods for predicting long-term stability (05:08)
• Emerging use of AI and machine learning to predict protein properties and improve developability (06:36)
• Future possibilities: Generative AI for protein design and formulation prediction (08:06)
• Advice for small companies: leveraging software-as-a-service and external partners to access computational tools (09:55)
• The impact of increasing computational power on the field's evolution (11:12)
• Most important takeaway: being open and curious about new computational techniques in biotech formulation (12:08)

Discover how to bridge computational predictions with experimental validation, navigate the current limitations of in silico stability forecasting, and position your organization to benefit from AI-driven formulation development, regardless of your resource constraints.

Connect with Giuseppe Licari to continue the conversation and explore how computational approaches can solve your formulation challenges before you ever step into the lab.

Connect with Giuseppe Licari:

LinkedIn: www.linkedin.com/in/giuseppe-licari

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What if you could predict formulation failures before ever touching a pipette? Computational approaches are revolutionizing biologics development, replacing trial-and-error experimentation with predictive intelligence that catches stability issues early and accelerates your path from candidate selection to clinic.

In this episode, David Brühlmann welcomes Giuseppe Licari, Principal Scientist in Computational Structural Biology at Merck KGaA. A chemist by training, Giuseppe transitioned from wet lab experimentation to the predictive power of in silico modeling. Today, he operates at the intersection of computational biology and CMC development, using digital tools to screen candidates for developability, predict formulation challenges, and de-risk development programs before committing resources to the lab.

Discover how computational methods are transforming the way biotech companies approach developability assessment and formulation strategy:

• Why maximizing shelf life isn’t always necessary in early development phases (02:56)
• The critical role of communication between computational and bench scientists (06:46)
• Core properties to assess for developability, including hydrophobicity, aggregation, charge, and immunogenicity (11:06)
• How accurate are in silico predictions, and where do they add the most value? (13:23)
• The limitations and strengths of machine learning and physics-based models in predicting protein behavior (15:19)
• The differences between developability, formulation development, and formulatability, and the value of early cross-functional collaboration (17:17)
• When to use platform formulations and when tailored approaches are needed for complex molecules (19:25)
• The advantages of using computational methods at any stage, especially for de-risking strategies (20:13)

Listen in for practical strategies for integrating in silico predictions into your developability and CMC workflows, catching stability issues before the lab, and making smarter development decisions that save time, material, and money.

Connect with Giuseppe Licari:

LinkedIn: www.linkedin.com/in/giuseppe-licari

Next step:

Need fast CMC guidance? → Get rapid CMC decision support here

One bad CDMO decision can cost you two years and your Series A. If you're navigating tech transfer, CDMO selection, or IND prep, let's talk before it gets expensive. Two slots open this month.

Support the show

What happens when cell therapy innovation meets real patient urgency? In this conversation, the barriers between scientist and patient all but vanish, bringing clarity—and a new sense of mission—to some of the biggest problems facing advanced therapy manufacturing and delivery.

Meet Jesús Zurdo, a biotech leader whose three decades of experience in innovation took on a whole new perspective when he became a leukemia patient himself. Seamlessly straddling the worlds of industry and patient care, Jesús Zurdo brings a refreshingly honest, systems-level view to cell therapies, manufacturing bottlenecks, and the realities of getting therapies from the lab to bedside.

Topics discussed:

• Experiences and lessons from stem cell registries and point-of-care manufacturing models (03:15)
• Challenges and potential of autologous and allogeneic cell therapies, including scalability and accessibility (06:08)
• The promise and limitations of in vivo cell therapy, delivery risks and patient safety (07:06)
• Reflections on current trends in manufacturing automation, delivery platforms, and the risk of overengineering (09:49)
• Barriers to wider adoption of advanced cell therapies, including hospital infrastructure and economic constraints (13:31)
• The case for earlier lines of treatment with new modalities and value in learning from actual patient experiences (14:30)
• The importance of integrating voices of patients, clinicians, and developers when solving complex problems (17:31)
• Why urgency and remembering our future roles as patients should guide therapy development (18:51)

Ready for bioprocessing to serve patients, yours included? For more insights and hands-on support, please subscribe so you never miss the next perspective-shifting episode.

Connect with Jesús Zurdo:

LinkedIn: https://www.linkedin.com/in/jesuszurdo

Email: jesus.zurdo@gmail.com

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Real progress in cell and gene therapy shouldn’t be measured solely by scientific innovation, but by whether those innovations actually reach the patients who need them most.

In this episode, David Brühlmann sits down with Jesús Zurdo, a scientist who’s spent three decades engineering life-changing biotechnologies, but whose outlook on the field shifted dramatically after becoming a leukemia patient himself.

With experience on both sides of the system, Jesús Zurdo brings a rare, unfiltered perspective to the persistent gap between scientific promise and real-world patient access.

Here’s why this conversation will reshape the way you think about bioprocessing, scale-up, and the meaning of “patient-centric” innovation:

• The challenges of scaling up advanced therapies beyond just volume: shifting from “how much can we make” to “how many patients can we reach?” (00:21)
• Jesús Zurdo’s personal journey—from biotech innovator to patient—and how it reshaped his thinking on product design and patient needs (04:12)
• How the biotech industry often overemphasizes automation, cost of goods, and new technologies at the expense of true patient access (08:02)
• The importance of designing products and manufacturing processes with patients’ lived experience in mind—not just clinical metrics (05:43)
• Why the business model and value proposition of therapies may need to change to address the high cost and limited accessibility of new treatments (12:09)
• Lessons from point-of-care manufacturing and real-world delivery of cell therapies—speed versus perfection (09:11)
• How patient involvement in both development and long-term outcome tracking could drive better treatments and wider adoption (15:10)
• The limitations of current clinical trial endpoints and the need to integrate patient-reported outcomes and new data sources like wearables (17:10)

Real progress in biotech isn’t just about scientific breakthroughs, it’s about ensuring those advances reach the millions who need them most.

Let’s rethink our business models and deployment strategies to bridge this gap for real-world impact

Connect with Jesús Zurdo:

LinkedIn: https://www.linkedin.com/in/jesuszurdo

Email: jesus.zurdo@gmail.com

Next step:

Need fast CMC guidance? New on-demand CMC advisory → Learn more here

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