Researchers at MIT are using simulation 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 principle of being highly soluble and easily synthesised , the best molecule it generated was 30 % higher than those created using traditional methods . The team now intends testing the drug 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.