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216: From Data Silos to Autonomous Biomanufacturing: Digital Twins and AI-Driven Scale-Up with Ilya Burkov - Part 2
Manage episode 524824264 series 3525243
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: [email protected]
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
Next step:
Need fast CMC guidance? → Get rapid CMC decision support here
217 episodes
Manage episode 524824264 series 3525243
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: [email protected]
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
Next step:
Need fast CMC guidance? → Get rapid CMC decision support here
217 episodes
All episodes
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