Machine Learning in Drug Discovery - Lightning Talks

Watch a collection of lightning talks from the Machine Learning in Drug Discovery Symposium held at the Broad Institute, featuring cutting-edge research presentations on AI applications in pharmaceutical development. Explore F.A.D.E. (Fully Agentic Drug Engine), a conversational AI platform designed to streamline drug discovery processes, presented by researchers from Georgia Institute of Technology. Learn about PostaNet, an innovative AI-based framework for predicting protein stability with experimental validation from the University of Pittsburgh team. Discover how genomic language models can decode regulatory splicing patterns to predict drug sensitivity, as presented by University of Rochester researchers. Examine ATLAS, a breakthrough system that overcomes data scaling limitations in machine learning through high-throughput synthesis and screening techniques, developed by Kimia Therapeutics. These rapid-fire presentations showcase the latest advances in applying machine learning to target validation, hit identification and optimization, clinical trial design, biologics development, and other critical areas of pharmaceutical research, providing insights into how AI is transforming the drug discovery pipeline.