(499d) Combined Synthesis Planning for Synthetic Drugs on the WHO Essential Medicines List
- Conference: AIChE Annual Meeting
- Year: 2019
- Proceeding: 2019 AIChE Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
- Time: Wednesday, November 13, 2019 - 1:45pm-2:10pm
In this work, we take advantage of the recent development in artificial intelligence applied in synthetic planning to explore solutions to the above challenge. Using a state-of-the-art synthesis planning tool, we try to minimize the chemical inventory needed to access the synthetic drug compounds in the WHO EML. The problem is solved in two stages. In the first stage, retrosynthesis analysis is performed for all the target molecules. Machine learning models are used to help find synthetic pathways, propose reaction conditions, and evaluate the feasibility of the suggested reactions. In the second stage, a multi-objective mixed-integer programming problem is solved to minimize the chemicals used in all the syntheses while maximizing the likelihood of success for all the pathways. Results show that by planning the syntheses in a combined manner we can reduce the number of chemicals by 30% compared to planning the syntheses separately, without significantly sacrificing the likelihood of success of the syntheses. In the meantime, this work demonstrates the potential benefit of simultaneously planning the syntheses for multiple targets, which can also be applied to other multitarget lists, e.g., a compound library during drug discovery.
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