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Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list

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Abstract

The access to essential medicines remains a problem in many low-income countries for logistic and expiration limits, among other factors. Enabling flexible replenishment and easier supply chain management by on demand manufacturing from stored starting materials provides a solution to this challenge. Recent developments in computer-aided chemical synthesis planning have benefited from machine learning in different aspects. In this manuscript, we use those techniques to perform a combined analysis of a WHO essential medicines list to identify synthetic routes that minimize chemical inventory that would be required to synthesize the all the active pharmaceutical ingredients. We use a synthesis planning tool to perform retrosynthetic analyses for 99 targets and solve a mixed-integer programming problem to select a combination of pathways that uses the minimal number of chemicals. This work demonstrates the technical feasibility of reducing storage of active pharmaceutical ingredients to a minimal inventory of starting materials.

Graphical abstract: Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list

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Article information


Submitted
23 Aug 2019
Accepted
02 Jan 2020
First published
02 Jan 2020

This article is Open Access

React. Chem. Eng., 2020, Advance Article
Article type
Paper

Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list

H. Gao, C. W. Coley, T. J. Struble, L. Li, Y. Qian, W. H. Green and K. F. Jensen, React. Chem. Eng., 2020, Advance Article , DOI: 10.1039/C9RE00348G

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