To enable the development of an open, end-to-end framework for data generation and automated binder discovery using DEL-ML, the Structural Genomics Consortium (SGC) recently formed a public-private partnership with leading DEL providers . Unlike previous DEL-ML studies, this partnership allows the public release of both data and methods used for model development, helping to drive open science. This endpoint is achieved through a framework that masks the explicit structures of DEL compounds, replacing them with chemical fingerprints representations commonly used in ML for small molecules . For the first time, this approach allows us to provide ML-ready DEL data for commercial-size libraries to the scientific community, supporting broader edorts to improve DEL-ML methods and model development. To facilitate data sharing, we have developed a new Artificial Intelligence Ready Chemical Knowledge (AIRCHECK) database for machine-readable datasets and have placed it in the public domain .