SynBioBeta Speaker
Leah Briscoe
Bayer
Data Scientist
Leah Briscoe is a Data Scientist at Bayer Crop Science working at the intersection of AI and trait development for next-generation crop products. She partners with gene expression scientists to develop strategies for engineering transgene expression, enabling robust and precise gene expression in crops. Her work applies genomic foundation models and machine learning to biological sequence design, accelerating the path from computational prediction to field-ready traits.Prior to Bayer, Leah earned her Ph.D. in Bioinformatics from UCLA as an NSF Graduate Research Fellow, where she developed novel statistical and computational methods for large-scale biological sequence data. Her doctoral research included model development for DNA-based microbial forensics and statistical approaches to reduce false positive rates in disease prediction from metagenomics data.Leah is passionate about bridging AI-driven biodesign with real-world agricultural challenges and driving cross-functional collaboration between data science and domain experts to bring engineered biology from concept to crop.
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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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