The number of SD compounds after each filtering step is reported for all datasets in Supplementary Table , and the number of DR compounds in Supplementary Table . Generally, the filtering steps that removed the most compounds are largest fragment selection and stereoisomer removal. With a few exceptions, the filtering pipeline did not radically change the size of the dataset. However, one important issue was observed for the DR datasets that originated in different PubChem bioassays. Although the confirmatory bioassays contain partial experimental measurements for all the compounds listed in Supplementary Table , actual DR values such as the IC50 are often reported only for a fraction of the dataset, for example only for active compounds. Although some DR datasets do not suffer from this issue, for example AID 1445, others are at the other extreme of the spectrum, with up to 97.8% of filtered compounds lacking explicit XC50 measurements (AID 1117362). On average, 35.57% of compounds do not possess experimentally-derived XC50 labels due to being insufficiently active at the top concentration. To address this limitation, we associated the compounds missing this information with the lowest activity value recorded in each dataset ('Minimum pXC50' in Figure ), providing a training target for machine learning models. This is done to provide a consistent value for inactive molecules and should be interpreted as an upper bound on the pX50 value. We maintain a flag for each molecule indicating if its confirmatory activity was experimentally-derived or set to a default value.