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The digitization of organic synthesis

Abstract

Organic chemistry has largely been conducted in an ad hoc manner by academic laboratories that are funded by grants directed towards the investigation of specific goals or hypotheses. Although modern synthetic methods can provide access to molecules of considerable complexity, predicting the outcome of a single chemical reaction remains a major challenge. Improvements in the prediction of ‘above-the-arrow’ reaction conditions are needed to enable intelligent decision making to select an optimal synthetic sequence that is guided by metrics including efficiency, quality and yield. Methods for the communication and the sharing of data will need to evolve from traditional tools to machine-readable formats and open collaborative frameworks. This will accelerate innovation and require the creation of a chemistry commons with standardized data handling, curation and metrics.

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Nature thanks Ian Churcher, Jacob Janey and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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The author declares no competing interests.

Correspondence to Ian W. Davies.

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Fig. 1: Above-the-arrow conditions and the digitization of organic synthesis.
Fig. 2: Optimizing one step in the total synthesis of maoecrystal V.
Fig. 3: Reaction prediction of a deoxyfluorination, a high-value transformation in medicinal chemistry, using machine learning.
Fig. 4: Accelerated reaction development in flow and reaction prediction.

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