For the embedding approach, the pre-trained biomedical language representation model BioBERT was used. The resulting embeddings can capture relevant information as is shown by the concurrence of their mapping with other assay characteristics annotated in ChEMBL. A clear division was apparent for the categories assay type, taxonomy, assay format and ChEMBL confidence score. Note that this confidence score reflects the specificity and characterization of the target used for the measurement, hence records with a similar description are indeed expected to have a similar confidence score. The separation based on standard type (i.e. the type of readout) was less strict. This could be caused by the fact that the standard type is not dependent on assay properties like the meta target or detection method but instead on the perturbagen concentration. This information may not be prominently mentioned in the assay descriptions. In general, despite these minor shortcomings these results