https://events.3ds.com/predicting-antibody-developability-from-sequence-using-machine-learning

On Friday, May 8th, students from BIOVIA's Harvey Mudd College clinic team will be presenting the work they've done over the last school year building and refining a machine learning model in Pipeline Pilot to predict antibody developability from sequence. An antibody's Developability Index (DI) can be calculated in Discovery Studio, but it requires a structure. With the machine learning model, the students hope to accelerate antibody development by providing a fast way to screen antibody sequences that may have developability issues further downstream.