Recent advances in chemical synthesis, biological testing, and artificial intelligence (AI) allow for greater automation in the drug discovery process. AI systems that generate novel design suppositions, as well as, cope with multiple design objectives provide a basis for further automation in some aspects of drug discovery. Automation could potentially accelerate timeframes for compound design and optimization. It could also enable better decision making in early-stage pharmaceutical discovery that translates into late-stage clinical validation. However, such approaches also raise considerable conceptual, technical, and organizational challenges.

This symposium aims to address the latest advances of this rapidly progressing field of science, by bringing together leading researchers to present the state-of-the-art in drug discovery. Together they will make daring predictions surrounding the possibilities and limitations of drug discovery using machine intelligence.