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Applying Active Learning in Drug Discovery | Pat Walters & James Thompson

Try datamol.io - the open source toolkit that simplifies molecular processing and featurization workflows for machine learning scientists working in drug discovery: https://datamol.io/ Never miss another M2D2 talk, add the schedule to your calendar: https://m2d2.io/talks/m2d2/about/ Also consider joining the M2D2 Slack: https://m2d2group.slack.com/join/shar... Full Title: There’s no Free Lunch, but you can get a Discount – Applying Active Learning in Drug Discovery Abstract: While computational methods have become a mainstay in drug discovery programs, many calculations are too time-consuming to be applied to large datasets. Active learning (AL), a machine learning method used to direct a search iteratively, can enable the application of computationally expensive methods such as relative binding free energy (RBFE) calculations to sets containing thousands of molecules. Moreover, AL can also be applied to virtual screening, enabling the rapid processing of billions of molecules. This presentation will provide an overview of active learning and highlight some applications in drug discovery. Speakers: Pat Walters - https://relaytx.com/our-team/pat-walt... James Thompson -   / james-thompson-26865165   Twitter Prudencio:   / tossouprudencio   Twitter Therence:   / therence_mtl   Twitter Jonny:   / hsu_jonny   Twitter datamol.io:   / datamol_io   ~ Chapters: 00:00 - Intro 04:49 - Active Learning Example 09:44 - Prioritizing Molecules for Synthesis 11:34 - Free Energy Perturbation (FEP): Transformation 14:37 - Active Learning Cycle 21:15 - Effect of Parameter Settings on Recall of Active Learning 25:54 - Virtual Screening as a Hit Identification Strategy 30:03 - Thompson Sampling - One Armed Bandits 34:09 - Large Libraries can be Decomposed Into Reagents 35:28 - Searching for Molecules: A Multi-Armed Bandit Problem 37:24 - Experiment 38:56 - Collaborative Work on SARS-Cov-2 Nsp3 Macrodomain 45:50 - ML has Impact Across the Drug Discovery Process 47:16 - Q+A