These second generation datasets were sourced from molecules of interest from our industry partners. A large compendium of molecules was curated using fingerprint based clustering. MACCS keys fingerprints with a default path length of four bonds were generated for all, and a matrix of graph similarity scores (Tanimoto) was evaluated. For each of the bonded parameters, clustering with DBSCAN based on these graph similarity scores was done, with cluster sizes of at least 5 molecules, and representative molecules were picked randomly from each cluster, with the goal of ensuring that if multiple training set molecules used the same parameter, these molecules would be chemically diverse. The tautomeric and isomeric states were expanded for the filtered molecules using the CMILES and Fragmenter packages. The final list of molecules we see in the optimization datasets listed in Table were generated following these steps.