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MIT researchers automate drug design with machine learning
Developing and improving medications is typically a long and very involved process. Chemists build and tweak molecules, sometimes aiming to create a new treatment for a specific disease or symptom, other times working to improve a drug that already exists. But it takes a lot of time and a lot of expert knowledge, and attempts often end with a drug that doesn't work as hoped. But researchers at MIT are using machine learning to automate this process. "The motivation behind this was to replace the inefficient human modification process of designing molecules with automated iteration and assure the validity of the molecules we generate," Wengong Jin, a PhD student in MIT's Computer Science and Artificial Intelligence Laboratory, said in a statement.
