Synthesis-planning program relies on human-machine partnership

Abstract

Computer-aided synthesis-planning (CASP) programs aim to replicate what synthetic chemists do when tackling a synthesis: start with a target molecule and then work backward to trace a synthetic route, including an efficient and achievable series of reactions and reagents. Work in this field goes back 50 years, but successful examples have emerged only in the past several years. These rely either on chemistry rules written by human chemists or on machine-learning algorithms that have assimilated synthesis knowledge from databases of reactions. Researchers now report that one CASP program that combines human knowledge and machine learning performs better than one that uses only artificial intelligence, particularly for synthetic routes involving rarely used reactions (Angew. Chem., Int. Ed. 2019, DOI: 10.1002/anie.201912083). The program is an update to Chematica, which was developed by Bartosz A. Grzybowski of the Ulsan National Institute of Science and Technology and the Polish Academy of Sciences and is