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 Sokolov
• Episodes 173 - 174: Mastering Hybrid Model Digital Twins: From Lab Scale to Commercial Bioprocessing with Krist Gernaey
• Episodes 277 - 278: Your Bioprocess Data Already Holds 35% More Yield: From End-to-End Models to Digital Twins with Ignasi Bofarull-Manzano
• Episodes 215 - 216: From Data Silos to Autonomous Biomanufacturing: Digital Twins and AI-Driven Scale-Up with Ilya Burkov
Connect with Moritz von Stosch:
Website: www.hinabioventures.com (hinabioventures.com)
LinkedIn: linkedin.com/in/movosto
Support the show (buzzsprout.com/2263581/support)