Generally speaking, the assumption was that the more time elapsed, the more difficult it will be for the model to generate compounds similar to real late-stage project compounds. The results of this analysis are shown in Fig. to f (all the value of aSNN can be seen in Table ). It can be seen that the value of most aSNNs was lower than those in the middle stage (Fig. ). In the public projects, given all of 5,000 generated compounds, the aSNN of generated compounds to high/ultra-high activity compounds was higher than that to low/middle activity compounds (the average of aSNN values across projects for low/middle/high/ultra-high activity being 0.259/0.297/0.341/0.404, respectively). However, this was not the case with the in-house projects, with the average aSNN values across projects for low/middle/high/ultra-high activity being 0.376/0.357/0.361/0.311, respectively (Fig. ). Hence, we can conclude that again both types of projects behave differently; for the public dataset evolution towards the chemical space of higher-potency compounds was generally possible, but not so for the inhouse projects.