
SynBioBeta Speaker
Andrew Chang
DeepSeq.AI
CEO
Andrew Chang, PhD, is the CEO and Co-founder of DeepSeq.AI. Originally trained in biophysics, Andrew developed an expertise in protein engineering at Genentech, where he integrated first-principles physical modeling with large-scale biological screening assays. A winner of multiple international machine learning competitions, he has built his career on the conviction that data quality and scale are the ultimate arbiters of AI power. Andrew is recognized as one of the earliest pioneers in protein language modeling using hyperscaled DNA sequencing data. Prior to founding DeepSeq, he held senior engineering and research roles at Synthego and Karius, where he helped establish their foundational AI platforms. Under his leadership, DeepSeq has secured backing from DARPA, NSF, Merck DSS, Illumina Ventures, Stanford StartX, and other prominent institutions to build the next generation of biologics discovery systems, with customers already including Genentech, Gilead, and other key biopharma players.
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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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