For this small case study, we chose a bioactivity data set of 4 adenosine receptors (A1, A2A, A2B and A3). The adenosine receptors are a highly conserved family of enzymes that share many similarities and selective modulators of adenosine receptors are of interest in drug discovery. Therefore, many compounds that share structural similarities are often tested against multiple or all of these receptors. This makes multitask modeling an eligible method to consider when creating a QSAR model for these receptors. The data set used in this study was assembled by querying the Papyrus data set (version 05.6) on the respective UniProt accession keys (P30542, P29274, P29275 and P0DMS8) using QSPRpred's integration. Only minor modifications to the adapter were made through inheritance to facilitate multi-task modeling and the adapted implementation is available in the qsp-bench repository. Compounds in this data set were represented by Morgan fingerprints with radius 3 and bit length of 2048 (as implemented in RDKit ).