This research set out with the hypothesis that different biological assays give significantly deviating outcomes. To evaluate if this hypothesis holds, we established the average deviation between measurements on the same protein-compound combinations. In general, there was a substantial variance between bioactivity values within the same protein-compound pair (MAE 0.83). This variance was clearly lower when the assay context was considered. Prior studies have also found that results from different assays vary. An interesting finding is that a larger variation in outcomes occurred for the kinase dataset than for the GPCRs and SLCs. This seemed to mainly be due to assay effects, as the variation within the same assay -as approximated by assay clusters -exhibited a marked decrease especially for the kinase dataset. One possible explanation for this finding could be that IC50 values reported for kinase inhibitors that are ATP-competitive are affected by the ATP-concentration used in the assay. Another explanation could be that for kinase inhibitors the binding site of the molecule influences its biological effect, in this work the kinase inhibitor type was not taken into account. It should be noted that we did not look for systematic trends between different assay outcomes. Instead, we focused on using machine learning models to correct for assay specific outcomes.