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.shinyapps.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.
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The summary of the manufacturing data that was used to support the PMI Predictor can be downloaded as an Excel spreadsheet. The full scale-up data are not publicly available due to internal restrictions of ACS GCIPR.
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We thank M. Hay and S. Vaidheeswaran for productive discussions and review of the manuscript.
The authors declare no competing interests.
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Borovika, A., Albrecht, J., Li, J. et al. The PMI Predictor app to enable green-by-design chemical synthesis. Nat Sustain 2, 1034–1040 (2019). https://doi.org/10.1038/s41893-019-0400-5
Organic Process Research & Development (2020)