In addition to CV during model building with the TS (3050 formulations), the performance of the final models was assessed via the external HS (650 formulations) filtered out at the beginning of the modeling workflow (Table , bottom half). Statistics and AUC curves (Figure ) are very similar to the CV results, further validating that the models can provide a similar predictive performance when encountering new data. High Acc HS values around 0.8 are retained, which indicates that the models reach a similar performance to those of Alves et al. , which were tested on eight additionally performed experimental data points instead of a pre-filtered HS and reached a correct classification rate of 75 %. In addition to the selected final models, predictions for the best subset-model type combination determined above (RF models with the RDK7 subset, termed RDK7-RF) are listed in Table in the beginning. These models reach nearly the same degree of accuracy (Acc HS = 0.75 -0.83, see Table ) while requiring calculation of only one descriptor type and avoiding the complexity of gradient-based XGB models.