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Abstract:

In a continuously evolving landscape of in silico chemical intelligence and machine learning, computer assisted synthetic planning has come to the forefront of discussion in the cheminformatics space. Herein, we describe an experiment in which ³§³Û±·°Õ±á±õ´¡â„¢ (developed under the name ‘Chematica’), a retrosynthetic design software, was used to plan synthetic pathways of eight structurally diverse bioactive and natural products. In each instance, the computer-planned routes were not only executed successfully in the laboratory, but also offered significant improvements over previous routes, circumvented patented routes and/or produced targets not synthesized previously. Chematica’s unique approach to building their expert database of known reactions by hand coding each transformation has allowed this tool to become a bench chemist’s ally by ‘learning’ chemistry much like a chemist would themselves, and suggesting diverse pathways towards their targets, thus generating ideas and providing cost effective routes based on each user’s unique needs. As a product of over 15 years of research, this unique tool is poised to not only get better with time, but also revolutionize the way chemists approach designing pathways to their complex targets.

Bio:

Sarah Trice spent most of her early career as a research scientist in medicinal chemistry at Merck & Co., West Point PA. After earning her PhD in organic chemistry from the University of Pennsylvania, Sarah transitioned into a business role with an emphasis on chemical technology enablement at MilliporeSigma. She served as the Head of Chemical Synthesis Innovation for MilliporeSigma before moving on to manage the commercial development of Synthia, an advanced retrosynthesis design software for pharmaceutical chemists. She is currently the managing director of the Cheminformatics Business Unit.