Content area

Abstract

Synthetic organic chemistry underpins several areas of chemistry, including drug discovery, chemical biology, materials science and engineering. However, the execution of complex chemical syntheses in itself requires expert knowledge, usually acquired over many years of study and hands-on laboratory practice. The development of technologies with potential to streamline and automate chemical synthesis is a half-century-old endeavour yet to be fulfilled. Renewed interest in artificial intelligence (AI), driven by improved computing power, data availability and algorithms, is overturning the limited success previously obtained. In this Review, we discuss the recent impact of AI on different tasks of synthetic chemistry and dissect selected examples from the literature. By examining the underlying concepts, we aim to demystify AI for bench chemists in order that they may embrace it as a tool rather than fear it as a competitor, spur future research by pinpointing the gaps in knowledge and delineate how chemical AI will run in the era of digital chemistry.

Artificial intelligence has recently seen numerous applications in synthetic organic chemistry. Advanced pattern-recognition heuristics may facilitate the access to chemical matter of interest and complement chemical intuition in the near future.

Details

Title
Synthetic organic chemistry driven by artificial intelligence
Author
de Almeida A Filipa 1   VIAFID ORCID Logo  ; Moreira, Rui 1 ; Rodrigues Tiago 2   VIAFID ORCID Logo 

 Universidade de Lisboa, Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Lisboa, Portugal (GRID:grid.9983.b) (ISNI:0000 0001 2181 4263) 
 Faculdade de Medicina da Universidade de Lisboa, Instituto de Medicina Molecular (iMM) João Lobo Antunes, Lisboa, Portugal (GRID:grid.9983.b) (ISNI:0000 0001 2181 4263) 
Pages
589-604
Publication year
2019
Publication date
Oct 2019
Publisher
Nature Publishing Group
e-ISSN
23973358
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2389698722
Copyright
© Springer Nature Limited 2019.