"Artificial Intelligence: The Future for Organic Chemistry?"

by Peiretti, Franck; Brunel, Jean Michel (2018)

Abstract

On the basis of a recent article "Predicting reaction performance in C-N cross-coupling using machine learning" that appeared in Science, we had decided to highlight the way forward for artificial intelligence in chemistry. Synthesis of molecules remains one of the most important challenges in organic chemistry, and the standard approach involved by a chemist to solve a problem is based on experience and constitutes a repetitive, time-consuming task, often resulting in nonoptimized solutions. Thus, considering the recent phenomenal progresses that have been made in machine learning, there is little doubt that these systems, once fully operational in organic chemistry, will dramatically speed up development of new drugs and will constitute the future of chemistry.

Links to Reference

• http://dx.doi.org/10.1021/acsomega.8b01773
• https://www.ncbi.nlm.nih.gov/pubmed/31458044
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6645362
• https://pubs.acs.org/doi/abs/10.1021/acsomega.8b01773
• https://pubs.acs.org/doi/pdf/10.1021/acsomega.8b01773

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