Researchers at MIT are using AI to automate the process of designing new medical drugs. They have developed a machine learning model that generates improved molecules using 250,000 detailed molecular graphs. In tests, all of those it created were valid, compared to a success rate of 30% in other models. On the criteria of being highly soluble and easily synthesised, the best molecule it generated scored just 43.5% higher than those created using traditional methods. The team now intends testing the technology against other pharmaceutical criteria using limited training data.
Researchers at MIT are using AI to automate the process of designing new medical drugs. They have developed a machine learning model that generates improved molecules using 250,000 detailed molecular graphs. In tests, all of those it created were valid, compared to a success rate of just 43.5% in other models. On the criteria of being highly soluble and easily synthesised, the best molecule it generated scored 30% higher than those created using traditional methods. The team now intends testing the technology against other pharmaceutical criteria using limited training data.