The Position of ADME Predictions in Multi-Objective QSAR

Abstract

ADME properties and toxicity predictions play an essential role in prioritization and optimization of drug molecules. According to recent statistics, drug efficacy and safety are principal reasons for drug failure. In this perspective, the position of ADME predictions in the evolution of traditional QSAR from the single objective of biological activity to a multi-task concept is discussed. The essential features of ADME and toxicity QSAR models are highlighted. Since such models are applied to prioritize existing or virtual project compounds with already established or predicted target affinity, a mechanistic interpretation, although desirable, is not a primary goal. However, a broad applicability domain is crucial. A future challenge with multi-objective QSAR is to adapt to the realm of big data by integrating techniques for the exploitation of the continuously increasing number of ADME data and the huge amount of clinical development endpoints for the sake of efficacy and safety of new drug candidates.