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Identifying Green Pathways in Organic Synthesis Planning




10: Chemical Engineering

Faculty Supervisor:

Klavs F. Jensen

Faculty email:


Apply by:

May 31, 2020


Hanyu Gao, hanyugao@mit.edu

Project Description

Recent years have seen tremendous progress in computer aided organic synthesis planning. With the help of computer programs, thousands of potential reaction pathways can be generated in a short amount of time. It has thus become impractical to rely on manual effort to screen these pathways for desired features. One important aspect that has an urgent demand involves the consideration of green chemistry. Process chemists would like to quickly identify synthetic pathways that avoid toxic solvents or reagents, which could greatly facilitate chemical process development. The goal of the project is to develop a filter for green pathways to be incorporated into the retrosynthetic platform ASKCOS (http://askcos.mit.edu). We will define a list of solvents and reagents to be recommended or avoided. Using this information, a data-driven model will be developed to highlight reactions that are likely to use green solvents/reagents and reactions that are likely to use undesirable solvents/reagents. This filter will be incorporated in an interactive reaction pathway visualization tool in ASKCOS (https://www.youtube.com/watch?v=JpIiKwnGAWE) and is expected to be extensively used by practitioners in the pharmaceutical industry to support process chemistry development. The student’s role will be obtaining and summarizing information about green chemistry, developing the filter and merging it into the current web based application, with the help and guidance from postdocs in the lab.


The project involves Python programming, so at least a moderate level of Python familiarity is preferred. Passion about process chemistry and sustainability is a plus.