The Effect of In Silico Classification Model Accuracy on Rediscovery and aSNN Next, we investigated the relationship between in silico classification model predictivity, learning curves and rediscovery/aSNN, to evaluate whether better bioactivity models also lead to higher values across these performance measures. The results of this analysis are shown in Figure , where balanced accuracies were acceptable for use in practice. We also investigated the relationship between the classification accuracy and rediscovery/aSNN (to the late stage compounds with high/ultra-high activity) in Figure . It can be seen that there is a positive correlation to aSNN (r 2 values from 0.249 to 0.463), therefore, a more accurate classification model is more likely to result in higher aSNN of de novo compounds than a less accurate one.