SynBioBeta Speaker
Tommaso Biancalani
Lila Sciences
SVP
Tommaso Biancalani is Senior Vice President of Generative Biology at Lila Sciences, where he focuses on building frontier AI models to streamline biological discovery. Prior to LILA, Tommaso led AI for biology at Genentech, where his department spearheaded the development and application of machine learning to various stages of the drug discovery pipeline, including target identification, hit finding, and lead optimization. Earlier in his career, Tommaso was a group leader at the Broad Institute, focusing on deep learning for genomics. Tommaso holds a PhD from the University of Manchester and completed postdoctoral fellowships at MIT and the Carl R. Woese Institute for Genomic Biology.
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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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