Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list
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...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Article |
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Royal Society of Chemistry (RSC)
2020
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| Online Access: | https://hdl.handle.net/1721.1/123797 |
| _version_ | 1826216424088010752 |
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| author | Gao, Hanyu Coley, Connor Wilson Struble, Thomas J Li, Linyan Qian, Yujie Green Jr, William H Jensen, Klavs F |
| author2 | Massachusetts Institute of Technology. Department of Chemical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Chemical Engineering Gao, Hanyu Coley, Connor Wilson Struble, Thomas J Li, Linyan Qian, Yujie Green Jr, William H Jensen, Klavs F |
| author_sort | Gao, Hanyu |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T16:47:28Z |
| format | Article |
| id | mit-1721.1/123797 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T16:47:28Z |
| publishDate | 2020 |
| publisher | Royal Society of Chemistry (RSC) |
| record_format | dspace |
| spelling | mit-1721.1/1237972022-10-03T08:20:12Z Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list Gao, Hanyu Coley, Connor Wilson Struble, Thomas J Li, Linyan Qian, Yujie Green Jr, William H Jensen, Klavs F Massachusetts Institute of Technology. Department of Chemical Engineering Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory 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. United States. Army Research Office (Contract W911NF-16-2-0023) 2020-02-13T15:37:39Z 2020-02-13T15:37:39Z 2020-01 2019-08 Article http://purl.org/eprint/type/JournalArticle 2058-9883 https://hdl.handle.net/1721.1/123797 Gao, Hanyo et al. "Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list." Reaction Chemistry & Engineering 5, 2 (January 2020): 367-376 © 2020 Royal Society of Chemistry http://dx.doi.org/10.1039/c9re00348g Reaction Chemistry & Engineering Creative Commons Attribution 3.0 unported license https://creativecommons.org/licenses/by/3.0/ application/pdf Royal Society of Chemistry (RSC) Royal Society of Chemistry (RSC) |
| spellingShingle | Gao, Hanyu Coley, Connor Wilson Struble, Thomas J Li, Linyan Qian, Yujie Green Jr, William H Jensen, Klavs F Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list |
| title | Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list |
| title_full | Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list |
| title_fullStr | Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list |
| title_full_unstemmed | Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list |
| title_short | Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list |
| title_sort | combining retrosynthesis and mixed integer optimization for minimizing the chemical inventory needed to realize a who essential medicines list |
| url | https://hdl.handle.net/1721.1/123797 |
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