Quantitative prediction of pharmacokinetic properties of drugs in humans: Recent advance in in vitro models to predict the impact of efflux transporters in the small intestine and blood-brain barrier

Efflux transport systems are essential to suppress the absorption of xenobiotics from the intestinal lumen and protect the critical tissues at the blood-tissue barriers, such as the blood-brain barrier. The function of drug efflux transport is dominated by various transporters. Accumulated clinical evidences have revealed that genetic variations of the transporters, together with coadministered drugs, affect the expression and/or function of transporters and subsequently the pharmacokinetics of substrate drugs. Thus, in the preclinical stage of drug development, quantitative prediction of the impact of efflux transporters as well as that of uptake transporters and metabolic enzymes on the pharmacokinetics of drugs in humans has been performed using various in vitro experimental tools. Various kinds of humanderived cell systems can be applied to the precise prediction of drug transport in humans. Mathematical modeling consisting of each intrinsic metabolic or transport process enables us to understand the disposition of drugs both at the organ level and at the level of the whole body by integrating a variety of experimental results into model parameters. This review focuses on the role of efflux transporters in the intestinal absorption and brain distribution of drugs, in addition to recent advances in predictive tools and methodologies. (c) 2021 The Authors. Production and hosting by Elsevier B.V. on behalf of Japanese Pharmacological Society. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

Automated summary

Efflux transport systems play a crucial role in inhibiting the absorption and distribution of drugs in the human body, with genetic variations and coadministered drugs affecting transporter expression and function. Utilizing in vitro experimental tools and mathematical modeling allows for accurate prediction of drug pharmacokinetics.