The next frontier in ADME science: Predicting transporter-based drug disposition, tissue concentrations and drug-drug interactions in humans

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作者
Flavia Storelli,Mengyue Yin,Aditya R. Kumar,Mayur K. Ladumor,Raymond Evers,Paresh P. Chothe,Osatohanmwen J. Enogieru,Xiaomin Liang,Yurong Lai,Jashvant D. Unadkat
出处
期刊:Pharmacology & Therapeutics [Elsevier BV]
卷期号:238: 108271-108271 被引量:43
标识
DOI:10.1016/j.pharmthera.2022.108271
摘要

Predicting transporter-based drug clearance (CL) and tissue concentrations (TC) in humans is important to reduce the risk of failure during drug development. In addition, when transporters are present at the tissue:blood interface (e.g., in the liver, blood-brain barrier), predicting TC is important to predict the drug's efficacy and safety. With the advent of quantitative targeted proteomics, in vitro to in vivo extrapolation (IVIVE) of transporter-based drug CL and TC is now possible using transporter-expressing models (cells lines, membrane vesicles) and the in vivo to in vitro relative expression of transporters (REF) as a scaling factor. Unlike other approaches based on physiological scaling, the REF approach is not dependent on the availability of primary cells. Here, we review the REF approach and compare it with other IVIVE approaches such as the relative activity factor approach and physiological scaling. For each of these scaling approaches, we review their underlying principles, assumptions, methodology, predictive performance, as well as advantages and limitations. Finally, we discuss current gaps in IVIVE of transporter-based CL and TC and propose possible reasons for these gaps as well as areas to investigate to bridge these gaps.
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