Ginkgo Datapoints and Apheris announced founding members of a new Antibody Developability Consortium aimed at predicting antibody manufacturability and developability risks earlier in discovery. The collaboration seeks to build a standardized antibody dataset for machine learning models. Founding participants include AbbVie, argenx, Lundbeck, and Takeda, with the consortium targeting a total dataset of 10,000 antibodies. The partners said each member will contribute proprietary antibody sequencing while keeping sequences private through federated infrastructure. The consortium’s focus on developability—biophysical properties that impact manufacturing, formulation, and progression—targets a known development bottleneck. By concentrating standardized data early, the initiative aims to reduce late-stage candidate attrition and speed decision-making across antibody programs.