As random splitting led to an MAE of ca. 0.52, our models seemed to compete with previously reported models which used this training / testing set design. Fortunately, the code for MolGpKa was available and allowed us to make a fair comparison. As the full data set used to train MolGpKa was not available, we trained and tested it using our own sets (Table , entry 2). Additionally, we compared the performance of our models and MolGpKa to reported data using the Novartis set, although we do not know the similarity between the training sets used to derive these MolGpKa and other models shown in Table and this benchmark set. In our original development discussed above, molecules from the Novartis set appeared in both the training and testing sets and our sets had to be redesigned. In addition, as most of the existing models do not consider carbon atoms as ionization centers, those were removed from our sets.