Recent advances in computational prediction of drug absorption and permeability in drug discovery.
Approximately 40%-60% of developing drugs failed during the clinical trials because of ADME/Tox deficiencies. Virtual screening should not be restricted to optimize binding affinity and improve selectivity; and the pharmacokinetic properties should also be included as important filters in virtual screening. Here, the current development in theoretical 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 absorption, and the relevance of predictive models in the evaluation of passive drug absorption are discussed. Recent developments 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.
Hou
Tingjun
T
Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, University of California at San Diego, La Jolla, CA 92093, USA.
Wang
Junmei
J
Zhang
Wei
W
Wang
Wei
W
Xu
Xiaojie
X
D003198:Computer Simulation; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D006801:Humans; D007408:Intestinal Absorption; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000378:metabolism*
D004364:Pharmaceutical Preparations