PT  - JOURNAL ARTICLE
AU  - Bi, Yi-an
AU  - Kimoto, Emi
AU  - Sevidal, Samantha
AU  - Jones, Hannah M.
AU  - Barton, Hugh A.
AU  - Kempshall, Sarah
AU  - Whalen, Kevin M.
AU  - Zhang, Hui
AU  - Ji, Chengjie
AU  - Fenner, Katherine S.
AU  - El-Kattan, Ayman F.
AU  - Lai, Yurong
TI  - In Vitro Evaluation of Hepatic Transporter-Mediated Clinical Drug-Drug Interactions: Hepatocyte Model Optimization and Retrospective Investigation
AID  - 10.1124/dmd.111.043489
DP  - 2012 Jun 01
TA  - Drug Metabolism and Disposition
PG  - 1085--1092
VI  - 40
IP  - 6
4099  - http://dmd.aspetjournals.org/content/40/6/1085.short
4100  - http://dmd.aspetjournals.org/content/40/6/1085.full
SO  - Drug Metab Dispos2012 Jun 01; 40
AB  - To assess the feasibility of using sandwich-cultured human hepatocytes (SCHHs) as a model to characterize transport kinetics for in vivo pharmacokinetic prediction, the expression of organic anion-transporting polypeptide (OATP) proteins in SCHHs, along with biliary efflux transporters, was confirmed quantitatively by liquid chromatography-tandem mass spectrometry. Rifamycin SV (Rif SV), which was shown to completely block the function of OATP transporters, was selected as an inhibitor to assess the initial rates of active uptake. The optimized SCHH model was applied in a retrospective investigation of compounds with known clinically significant OATP-mediated uptake and was applied further to explore drug-drug interactions (DDIs). Greater than 50% inhibition of active uptake by Rif SV was found to be associated with clinically significant OATP-mediated DDIs. We propose that the in vitro active uptake value therefore could serve as a cutoff for class 3 and 4 compounds of the Biopharmaceutics Drug Disposition Classification System, which could be integrated into the International Transporter Consortium decision tree recommendations to trigger clinical evaluations for potential DDI risks. Furthermore, the kinetics of in vitro hepatobiliary transport obtained from SCHHs, along with protein expression scaling factors, offer an opportunity to predict complex in vivo processes using mathematical models, such as physiologically based pharmacokinetics models.