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Making Better Decisions During Synthetic Route Design: Leveraging Prediction to Achieve Greenness-by-Design

preprint
submitted on 17.01.2019 and posted on 21.01.2019 by Jun Li, Martin Eastgate
This paper expands our work predicting Process Mass Intensity (PMI), as a methodology for exploring the potential efficiency of proposed synthetic routes. In the present work, we integrate a method for predicting the PMI contributions of high complexity reagents, needed to enable certain transformations. We focus on ligands for metal catalyzed reactions - and develop an approach for predicting which ligands may function in CN couplings - as a proof of concept. We leverage this to enable the integration of the PMI contribution of the ligands into a predictions of a routes efficiency, enabling an understanding of the holistic impact of a route decision..

Funding

none

History

Email Address of Submitting Author

martin.eastgate@bms.com

Institution

Bristol-Myers Squibb

Country

USA

ORCID For Submitting Author

0000-0002-6487-3121

Declaration of Conflict of Interest

none

Version Notes

submission version

Exports