First we investigate how the optimization score (OS) and data control score (DCS) evolve during optimization for the EGFR task (see Fig. ). For GA, we show the scores of molecules in the population at different iterations, while for the LSTM we sample molecules in each iteration. Starting from random ChEMBL compounds the optimization process increases the OS more dominantly than the DCS. This behaviour is also present for the DRD2 and JAK2 data sets, for which the corresponding plots can be found in Fig. . For all of the tasks considered here, there is a mismatch between OS and DCS, which shows that the optimization procedure suffers from model and/or data specific biases.