Cerivastatin and repaglinide are substrates of cytochrome P450 (CYP)2C8, CYP3A4, and organic anion-transporting polypeptide (OATP)1B1. A recent study revealed an increased risk of rhabdomyolysis in patients using cerivastatin with clopidogrel, warranting further studies on clopidogrel interactions. In healthy volunteers, repaglinide area under the concentration-time curve (AUC(0-∞)) was increased 5.1-fold by a 300-mg loading dose of clopidogrel and 3.9-fold by continued administration of 75 mg clopidogrel daily. In vitro, we identified clopidogrel acyl-β-D-glucuronide as a potent time-dependent inhibitor of CYP2C8. A physiologically based pharmacokinetic model indicated that inactivation of CYP2C8 by clopidogrel acyl-β-D-glucuronide leads to uninterrupted 60-85% inhibition of CYP2C8 during daily clopidogrel treatment. Computational modeling resulted in docking of clopidogrel acyl-β-D-glucuronide at the CYP2C8 active site with its thiophene moiety close to heme. The results indicate that clopidogrel is a strong CYP2C8 inhibitor via its acyl-β-D-glucuronide and imply that glucuronide metabolites should be considered potential inhibitors of CYP enzymes.

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Many drug–drug interactions ( DDI s) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter‐mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life‐threatening consequences. There has been tremendous progress in the predictability and modeling of DDI s. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDI s involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically‐based pharmacokinetic modeling, complex DDI s, methodological pitfalls, and interpretation of DDI information.