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Title: “Transformation in drug discovery through human-focused learning cycles”
Speakers: Prashant Desai, Ph.D. and Erik Hembre, Ph.D.
Drug discovery is a rather challenging task requiring iterative learning cycle through compound design, synthesis and characterization of thousands of compounds to identify the clinical candidate. Traditionally decisions for progressing compounds were mainly based on empirical preclinical behavior of compounds. With the advent of ABC principles and NGR the discovery philosophy has pivoted to driving decisions based on estimated human properties. In this presentation we will share the impact of a transformative cross-functional approach involving the integration of mechanistic PK principles with structure-property relationship machine learning ADME models and pharmacodynamics models to efficiently drive the discovery engine focused on optimizing estimated performance in human.