Investigation of feature importance shows that assay embeddings are amongst the most important features for achieving an RMSE decrease during model training (Figure ). For all targets, the MT models performed worse than the control, indicating that using our assay categories as separate outputs does not improve performance. Overall these results indicate that assay context can improve model performance and that assay embeddings best represent this context. 298 299 Discussion 300 In this research we set out to address the question whether employment of aggregated bioactivity 301 data from different biological assays can be improved by taking this experimental context into account. 302