SynBioBeta Speaker
Divy Thakkar
Google DeepMind
Research Program Lead
Divy is a research program lead at Google DeepMind where he's building the next paradigm for Human-AI collaboration. He currently focusses on advancing Gemini for scientific research. He received his Ph.D in Computer Science from City St George's, University of London.
Sessions Featuring
Divy
This Year
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Tools & Tech
Decoding the Dark Proteome: From Discovery Gap to Drug Pipeline
The proteome holds the answers to some of biology's most persistent questions — yet the vast majority of proteins remain functionally uncharacterized. This working session brings together leaders from pharma, biotech, and the emerging protein sequencing field to explore what it would actually take to close the gap. What are the real bottlenecks in moving from dark proteome discovery to actionable drug targets? What sequencing and annotation infrastructure needs to exist? And where are the first credible opportunities for pharma to engage? A candid, technical conversation for those already building toward this frontier.
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Tools & Tech
Decoding the Dark Proteome: From Discovery Gap to Drug Pipeline
The proteome holds the answers to some of biology's most persistent questions — yet the vast majority of proteins remain functionally uncharacterized. This working session brings together leaders from pharma, biotech, and the emerging protein sequencing field to explore what it would actually take to close the gap. What are the real bottlenecks in moving from dark proteome discovery to actionable drug targets? What sequencing and annotation infrastructure needs to exist? And where are the first credible opportunities for pharma to engage? A candid, technical conversation for those already building toward this frontier.
Session lineup still growing
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?
Featuring
Speaker Coming Soon
