Artificial Intelligence for Chemical Synthesis: Improving the Workflow of Medicinal Chemists using Computer-Aided Synthesis Planning - Haywood, Alexe L. (2024)
Machine learning techniques have numerous applications in modern drug discovery. Advances in computing power, machine learning algorithms and data availability have inspired renewed interest in artificial intelligence and automation in chemical synthesis. The field of Computer-Aided Synthesis Planning (CASP) aims to improve chemists’ workflow by shortening the time required to synthesise compounds, giving them more time to analyse and design future experiments. In this thesis, we review contemporary CASP methodologies before developing machine learning models to predict reaction yield. State-of-the-art approaches to forward reaction prediction and retrosynthetic analysis tasks are outlined and compared using quantitative metrics.