Recent Advances in Computational Prediction of Drug Absorption and Permeability in Drug Discovery

Abstract: Approximately 40%-60 % of developing drugs failed during the clinical trials because of ADME/Tox deficien-cies. Virtual screening should not be restricted to optimize binding affinity and improve selectivity; and the pharmacoki-netic properties should also be included as important filters in virtual screening. Here, the current development in theo-retical models to predict drug absorption-related properties, such as intestinal absorption, Caco-2 permeability, and blood-brain partitioning are reviewed. The important physicochemical properties used in the prediction of drug absorp-tion, and the relevance of predictive models in the evaluation of passive drug absorption are discussed. Recent develop-ments in the prediction of drug absorption, especially with the application of new machine learning methods and newly developed software are also discussed. Future directions for research are outlined