The multidrug resistance protein 1 (MDR1) is known to limit brain penetration of drugs and play a key role in drug-drug interactions (DDIs). Theoretical cut-offs from regulatory guidelines are used to extrapolate MDR1 interactions from in vitro to in vivo. However, these cut-offs do not account for interlaboratory variability. Our aim was to calibrate our experimental system to allow better in vivo predictions. We selected 166 central nervous system (CNS) and non-CNS drugs to calibrate the MDR1 transport screening assay using Lewis lung cancer porcine kidney 1 epithelial cells overexpressing MDR1 (L-MDR1). A threshold efflux ratio (ER) of 2 was established as one parameter to assess brain penetration in lead optimization. The inhibitory potential of 57 molecules was evaluated using IC 50 values based on the digoxin ER-IC 50 (ER)-or apparent permeability-IC 50 (P app )-in L-MDR1 cells. Published clinical data for 68 DDIs involving digoxin as the victim drug were collected. DDI risk assessments were based on intestinal concentrations ([I 2 ]) as well as unbound [I 1u ] and total plasma [I 1T ] concentrations. A receiver operating characteristic analysis identified an [I 2 ]/IC 50 (ER) of 6.5 as the best predictor of a potential interaction with digoxin in patients. The model was further evaluated with a test set of 11 digoxin DDIs and 16 nondigoxin DDIs, resulting in only one false negative for each test set, no false positives among the digoxin DDIs, and two among the nondigoxin DDIs. Future refinements might include using cerebrospinal fluid to unbound plasma concentration ratios rather than therapeutic class, better estimation of [I 2 ], and dynamic modeling of MDR1-mediated DDIs.
Although the multiplicity in transport proteins assessed during drug development is continuously increasing, the clinical relevance of the breast cancer resistance protein (BCRP) is still under debate. Here, our aim is to rationalize the need to consider BCRP substrate and inhibitor interactions and to define optimum selection and acceptance criteria between cell-based and vesicle-based assays in vitro. Information on the preclinical and clinical pharmacokinetics (PK), drug-drug interactions, and pharmacogenomics data was collated for 13 marketed drugs whose PK is reportedly associated with BCRP interaction. Clinical examples where BCRP impacts drug PK and efficacy appear to be rare and confounded by interactions with other transporters. Thirty-seven compounds were selected to be tested as BCRP substrates in a cell-based assay using MDCKII cells (Madin-Darby canine kidney cells) and 18 in membrane vesicles. Depending on the physicochemical compound properties, we observed both in vitro systems to give false-negative readouts. In addition, the inhibition potential of 19 compounds against BCRP was assessed in vesicles and in MDCKII cells, where we observed significant system and substrate-dependent IC 50 values. Therefore, neither of the two test systems is superior to the other. Instead, one system may offer advantages under certain situations (e.g., low permeability) and thus should be selected based on the physicochemical compound properties. Finally, given the clinical relevance of BCRP, we propose that its evaluation should remain issue-driven: for low permeable, low bioavailable drugs, in particular when other more common processes do not allow a mechanistic understanding of any unexpected absorption or brain disposition, and for drugs with a low therapeutic window.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.