AI for Drug Discovery

The latest meeting in the RSC BMCS Hot Topics series is AI for Drug Discovery.

Artificial intelligence (AI) is becoming an increasingly important part of the drug discovery toolkit, with applications spanning target discovery, molecular design, protein modelling, and clinical development. As the field advances, AI is not only offering new technical capabilities but also changing how researchers approach the challenges of drug discovery. This meeting will highlight recent progress in AI-driven drug discovery, bringing together perspectives from industry and academia. Talks will explore enabling technologies and practical applications of AI across the drug discovery pipeline.

There is a fantastic lineup of speakers for real leaders in the field. Registration details are here https://www.rscbmcs.org/events/hottopicsai26/

Chair: Hannah Fowler, RSC
12:30Opening Remarks
12:35Andreas Bender, Khalifa University
Title TBC
13:20Keishi Kohara, AstraZeneca
Embedding AI-Assisted Design at AstraZeneca
13:50 – 14:05Break
Chair: Silvia Bonomo, Astex
14:05Astrid Stroobants, Novartis
Title TBC
14:35Fraser Cunningham, Recursion
Title TBC
15:05Kenneth Atz, Roche
RingAnalyzer reveals widespread high-energy ring conformations across structure-based drug design workflows
15:35 – 15:50Break
Chair: TBC
15:50Alex Rich, Inductive Bio
Dose-Driven Lead Optimization in the AI Era
16:20Maria Castellanos, OpenADMET, Open Molecular Software Foundation (OMSF)
Democratizing AI for ADMET: Open Data, Community Models, and Live Benchmarks
16:50Closing Remarks
17:00Close of Conference

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