Generative models are being increasingly used in drug discovery, very often coupled with absorption, distribution, metabolism, and excretion (ADME) bioassays or quantitative structure–activity relationship (QSAR) models to optimize a given set of properties. The molecules proposed by these algorithms are often revealed to be false positives; that is, they are predicted to be active and turn out to be inactive after synthesis and testing, mostly due to overoptimization of the predicted scores, which leads to an actual decrease or stagnation of the real scores. Follow the link for full article.