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Artificial Intelligence: The Future for Organic Chemistry?

Year: 2018

Type: article

Abstract: High Resolution Image Download MS PowerPoint Slide 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.

Source: ACS Omega

DOI: 10.1021/acsomega.8b01773

Authors: Franck Peiretti, Jean Michel Brunel

Institutions: Inserm, Aix-Marseille Université, Institut National de la Recherche Agronomique, Centre de Recherche en CardioVasculaire et Nutrition, Membranes et Cibles Thérapeutiques

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,935

OpenAlex ID: W2895896993

FWCI: 2.799

Cites: 23

Cited by: 50

Related to: 10