Synthetic organic chemistry is one of the cornerstones of the drug discovery process and is crucial for rapid navigation of increasingly complex druggable chemical space. It is also critical in determining discovery cycle times and development speeds associated with drug candidates. The knowledge and experience of researchers has always been the key to combining chemical reactions into successful synthetic schemes. However, chemical synthesis and route design is still a significant challenge. Merck quotes that 55% of the time, a benchmarked reaction fails. Therefore, a radical and innovative step change in synthesis is needed. Computer-aided retrosynthesis would be a valuable tool but until recently it was slow and provided results of unsatisfactory quality. Further to this, software that devise effective schemes for synthetic chemistry have depended on the input of rules from researchers. Waller and Segler et al. in collaboration with Elsevier have developed a ‘deep learning’ computer program that produces blueprints for the sequences of reactions needed to create small organic molecules, such as drug compounds. This artificial-intelligence tool has digested nearly every reaction ever published (&gt; 15 million) and has the potential to transform the way synthetic & medicinal chemists work in the future. Segler & Waller et al. tested the synthetic routes that the program generated in a double-blind trial with 45 organic chemists from two institutes in China and Germany and the routes have proven scientifically sound and robust. Increasing the success rate in synthetic chemistry would have a huge benefit in terms of speed and efficiency on drug-discovery projects, as well as cost reduction. Reaxys-PAI Predictive Retrosynthesis solution developed in collaboration between Elsevier and Waller and Segler et al. deploys next generation technologies to augment chemical synthesis and chemist knowledge helping drive innovation, time and cost savings. This talk will discuss the solution and with feedback from chemists demonstrating its utility with some examples from recent drug development programs.

Reaxys-PAI predictive retrosynthesis: Rewiring chemistry and redesigning synthetic routes

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.