SynBioBeta Speaker
Surge Biswas
Nabla Bio
Co-founder & CEO
Surge is cofounder/CEO at Nabla Bio, a protein design company developing AI and wet-lab technologies for drug discovery. Surge created the first protein language model as a graduate student in George Church's lab at Harvard, where he got his PhD. Outside of work Surge likes hanging out with his wife and Nabla co-founder Frances, and their two dogs Archie and Riley.
SynBioBeta 2026 Tickets are Live
Confirmed Speakers
Sessions Featuring
Surge
This Year
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Human Health
Build, Buy, or Partner: The New AI Operating Model from Biologics Discovery to Clinical Assets
AI is reshaping how biopharma discovers, develops, and advances therapeutic agents across the full lifecycle, from early design to translational strategy and clinical asset development. But with dozens of platforms and models emerging, R&D leaders face a strategic crossroads: should they build internal AI capabilities, buy turnkey software, or partner with integrated platforms that connect computational design, experimental validation, and clinical decision-making? This session brings together Biotech R&D executives and AI platform leaders to explore how software-first, closed-loop AI workflows are transforming not only discovery speed, but also translational success and clinical outcomes. Speakers will share real-world perspectives on integrating AI into portfolio strategy, advancing assets toward the clinic, repositioning clinically validated assets, and redefining the operating model for biologics development.
Get a Ticket
Featuring
Surge Biswas
Nabla Bio
Co-founder & CEO
Protein language-model pioneer building AI-plus-wet-lab antibody design.
Jen Asher
1910
Founder & CEO
AI-native drug discovery founder blending wet-lab automation and models.
Yves Falanga
NOETIK
Corporate Strategy & BD
Business-development lead helping broker NOETIK’s big-pharma deals.
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Human Health
Build, Buy, or Partner: The New AI Operating Model from Biologics Discovery to Clinical Assets
AI is reshaping how biopharma discovers, develops, and advances therapeutic agents across the full lifecycle, from early design to translational strategy and clinical asset development. But with dozens of platforms and models emerging, R&D leaders face a strategic crossroads: should they build internal AI capabilities, buy turnkey software, or partner with integrated platforms that connect computational design, experimental validation, and clinical decision-making? This session brings together Biotech R&D executives and AI platform leaders to explore how software-first, closed-loop AI workflows are transforming not only discovery speed, but also translational success and clinical outcomes. Speakers will share real-world perspectives on integrating AI into portfolio strategy, advancing assets toward the clinic, repositioning clinically validated assets, and redefining the operating model for biologics development.
Get a Ticket
Featuring
Surge Biswas
Nabla Bio
Co-founder & CEO
Protein language-model pioneer building AI-plus-wet-lab antibody design.
Jen Asher
1910
Founder & CEO
AI-native drug discovery founder blending wet-lab automation and models.
Yves Falanga
NOETIK
Corporate Strategy & BD
Business-development lead helping broker NOETIK’s big-pharma deals.
Session lineup still growing
Get a Ticket
Featuring
Speaker Coming Soon
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Human Health
From Cells to Patients: Solving the Scale Mismatch in Virtual Biology
Drug discovery often measures biology at the cell level while interventions work at the tissue, organ, or whole-patient scale. This mismatch can make accurate cell-level predictions irrelevant in the clinic. This session dives into strategies to bridge that gap: multiscale modeling that nests single-cell dynamics within organ-level simulations, spatial transcriptomics that preserve context, and surrogate models that translate cell-level outputs into clinical biomarkers. Speakers will ask: how do we ensure virtual biology reflects not just what cells do in isolation, but how biology behaves in the real complexity of patients?
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Featuring
Speaker Coming Soon
