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Virtual Assays for Target Discovery: Bridging Human Biology, Functional Genomics, and Machine Learning.
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Early drug discovery is undergoing rapid transformation, with innovative strategies emerging to address current challenges such as attrition rates, development timelines, and the need for greater human translational relevance. Virtual Assays offer a transformative framework by integrating human genetics to inform causal cell types and mechanisms, alongside in vitro human platforms, and genome engineering for rigorous hypothesis testing, combined with AI/ML-driven multi-omics profiling. Together, this approach enables scalable, predictive, and biologically relevant target identification and validation.
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This session will detail the foundational elements and key enablers of the Virtual Assay approach, discuss practical considerations for its adoption, and illustrate how high-dimensional data can drive more effective target discovery — ultimately increasing experimental throughput and strengthening the human relevance of early-stage research for future translational studies.
