Scientists use machine learning to speed up long-acting drug formulation
University of Toronto researchers just proved that machine learning can drastically cut the trial-and-error out of formulating long-acting injectables. By extracting design criteria from a LightGBM model, the team hit their target slow-release rate for an ovarian cancer drug on the very first try. The entire dataset and codebase have been open-sourced on Zenodo.