Industrializing Machine Learning Workflows in Drug Discovery

Learn how Recursion Pharmaceuticals is revolutionizing drug discovery through automated machine learning workflows in this 28-minute conference talk from the Toronto Machine Learning Series. Explore how ML Engineer Estefania Barreto and her team leverage large-scale chemical assay datasets to predict crucial compound properties like Absorption, Distribution, Metabolism, Excretion (ADME), Potency, and Toxicity. Gain valuable insights into standardized solutions for training and deploying predictive models on a weekly basis, accelerating early-stage drug discovery processes. Discover practical approaches to data management and model deployment using both cloud and supercomputing resources, demonstrating how machine learning can be effectively industrialized in pharmaceutical research.