However, public and in-house projects behaved vastly different throughout the current analysis, which is understandable given the differences in how both datasets were constructed. For inhouse datasets, the aSNN were mostly higher than 0.3; however, the aSNN to the real high or ultra-high active compounds was across projects consistently lower (Fig. ) than to the real low or middle active compounds. This could be influenced by the somewhat artificial setup of this study, where we focused on a single objective, namely on-target activity; however, during any practical drug discovery project the consideration of multiple (and often competing) objectives is inevitable . This is supported by the analysis shown in Fig. , where it is clear that in real projects compound evolution does not simply follow an optimization of on-target activity.