Drug Discovery ML Platform

Drug discovery ML is applying machine learning to predict molecular properties and accelerate the identification of drug candidates. The traditional pipeline: chemists synthesize compounds → lab tests measure efficacy/toxicity/solubility → weeks/months to test hundreds. ML alternative: predict properties for millions of compounds computationally → lab tests the top 100 → weeks to test. Core tasks: molecular representation (how to encode molecules), property prediction (binding affinity, toxicity, ADME), and optimization (find new molecules with better properties).