While we observed only a small drop in performance between the random and out-of-distribution validation sets, there was a significant drop when comparing the model's accuracy using DEL data for in silico validation versus its performance in identifying active compounds from small molecule catalogs in in vitro validation. Notably, the precision of predictions dropped from 85% to approximately 15%. Previous studies that included in vitro experiments have noted similar results . Several factors could contribute to this discrepancy, including the generalizability issues discussed above, but the most likely culprits are the high noise content of DEL data inflating in-silico performance, and the small size of the in-vitro validation set (50 compounds), which limits the accuracy of in-vitro performance estimates.