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- W2949064041 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. This Perspective discusses the challenges associated with the prediction of chemical synthesis, in particular the reaction conditions required for organic transformations, and the role of machine-learning approaches in the prediction process." @default.
- W2949064041 created "2019-06-27" @default.
- W2949064041 creator A5059734311 @default.
- W2949064041 date "2019-06-01" @default.
- W2949064041 modified "2023-10-03" @default.
- W2949064041 title "The digitization of organic synthesis" @default.
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- W2949064041 doi "https://doi.org/10.1038/s41586-019-1288-y" @default.
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