Ginkgo Datapoints and Apheris launched the Antibody Developability Consortium, aiming to build a standardized dataset to predict antibody manufacturability and developability risks earlier in the discovery pipeline. The initiative will aggregate proprietary antibody sequencing contributions from founding members including AbbVie, argenx, Lundbeck, and Takeda, with Ginkgo Datapoints coordinating scientific design and execution. Partners aim to compile data covering up to 10,000 antibodies. The consortium’s goal is to address limitations of smaller or convenience datasets by using federated infrastructure that keeps proprietary sequences private while enabling machine-learning-ready modeling of developability barriers. For biotech teams, early risk prediction is increasingly viewed as a lever to cut late-stage attrition driven by formulation, aggregation, and manufacturability issues, especially in complex therapeutic areas such as CNS discovery pipelines.