In ChEMBL, identical or similar biological assays are currently not grouped together. However, such a grouping could be useful to obtain a clear overview of how the data in a dataset was derived, and for modeling purposes. Therefore, one of the objectives of our study was to use neural topic modeling with TF-IDF to cluster similar records, which was successful. Overall, the best clustering was obtained for models with a minimum cluster size of 128 (see Table ) and using outlier reduction (see Figure ).