These patents are automatically loaded into HTML-based forms which display a preliminary curation, including association of compounds with tabular data. A trained curator compares the preliminary curation with the patent document, correcting data for curatable patents as needed, and rejecting patents that turn out not to have suitable data. (For example, as of mid-2024, patents containing only binned affinity data, such as "IC50 < 1 μM", will be rejected.) Curated data from this step are loaded into a staging server, where they are compared against the patent documents by a second curator and any concerns are resolved in consultation with the first curator. BindingDB curation software is then used to annotate the curated data by, for example, identifying appropriate links to the PDB and UniProt, and the data are then migrated to the public database server. The compounds are submitted to PubChem and, a week later the resulting PubChem Substance IDs and Compound IDs are obtained and associated with the BindingDB data. This largely automated process allows a small staff to curate substantially all suitable newly granted US patents and new pending patent applications in each weekly download. This level of efficiency is essential, because the average number of data per patent in BindingDB is 160, while the average number per article is 40. This difference is reflected in Table , where BindingDB curation of about 1,500 patents yielded about twice as many affinity data as ChEMBL curation of about 2,600 articles. Figure provides a more detailed look at the distributions of binding data per article and per patent (left) and of compounds curated per article and per patent (right), across all of BindingDB's holdings. Articles with very high data counts may include, for example, very large reports of new structure-activity relationships for a given protein target ; reports of new data for many compounds against a panel of kinases ; large ADME-related studies ; publications associated with datasets within the PDSP database ; and review articles or articles with large datasets assembled for quantitative structure-activity studies .