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The PMI Predictor - a Web App Enabling Green-by-Design Chemical Synthesis

Publication Date
Authors
Author Name
Alina Borovika
Author Name
Jacob Albrecht
Author Name
Jun Li
Author Name
Andrew S. Wells
Author Name
Christiana Briddell
Author Name
Barry R. Dillon
Author Name
Louis J. Diorazio
Author Name
James R. Gage
Author Name
Fabrice Gallou
Author Name
Stefan G. Koenig
Author Name
Michael E. Kopach
Author Name
David K. Leahy
Author Name
Isamir Martinez
Author Name
Martin Olbrich
Author Name
Jared L. Piper
Author Name
Frank Roschangar
Author Name
Edward Sherer
Author Name
Martin D. Eastgate

The development of sustainable processes for the synthesis of new clinical candidates is a priority for every pharmaceutical company. The ultimate efficiency of a molecule’s synthesis results from a combination of the sequence of steps to assemble the molecule and the efficiency of each of the steps. While multiple approaches are available to aid the development of efficient processes, far fewer methods to guide route innovation have been described. Here we present a ‘green-by-design’ approach to route selection and development, assisted by predictive analytics and historical data. To aid the selection of more efficient strategies, we created a user-friendly web application, the ‘PMI Predictor’ (accessible from https://acsgcipr-predictpmi.shin-yapps.io/pmi_calculator/), to predict the probable efficiencies of proposed synthetic routes before their evaluation in the laboratory. We expect that use of this app will bring greater awareness of sustainability during the initial phase of route design and will contribute to a reduced environmental impact of pharmaceutical production.

Source
Nature Sustainability
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