Artificial Intelligence (AI)/Machine Learning (ML) for Early Drug Discovery is a two-part conference that brings together a diverse group of experts from chemistry, target discovery, pharmacology, and bioinformatics to talk about the increasing use of computational tools, models, algorithms, and data analytics for drug development. The talks will highlight the pros and cons of AI/ML-driven decision-making using relevant case studies from small molecule and peptide drug development. The first part of the conference will focus on how AI/ML can help improve drug design, hit identification, predict PK/PD and drug-like properties, and lead optimization. The second part will focus on emerging computational tools and models for target identification, deconvoluting cellular pathways, and to drive niche applications by exploring chemical space for various therapeutic areas.