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  • Review Article
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Synthetic organic chemistry driven by artificial intelligence

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.

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Fig. 1: Variability in chemical reaction data available from patents (1976–2016).
Fig. 2: Similarity search for in silico retrosynthesis analysis.
Fig. 3: Artificial intelligence tools for retrosynthetic analysis.
Fig. 4: Comparison of two methods for the prediction of reaction products.
Fig. 5: Active learning for the optimization of reaction conditions.
Fig. 6: Automated discovery of new chemistry.
Fig. 7: Networking robots.

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Acknowledgements

A.F.A. acknowledges Fundação para a Ciência e Tecnologia (FCT) Portugal for financial support through a PhD grant (PD/BD/143125/2019). T.R. is an investigador auxiliar supported by FCT Portugal (CEECIND/00887/2017). T.R. acknowledges FCT/FEDER (02/SAICT/2017, grant 28333) for funding. The authors thank the reviewers for their comments.

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Correspondence to Tiago Rodrigues.

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de Almeida, A.F., Moreira, R. & Rodrigues, T. Synthetic organic chemistry driven by artificial intelligence. Nat Rev Chem 3, 589–604 (2019). https://doi.org/10.1038/s41570-019-0124-0

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