ABSTRACT:Understanding the potential for cytochrome P450 (P450)-mediated drug-drug interactions is a critical step in the drug discovery process. Although in vitro studies with CYP3A4, CYP2C9, and CYP2C19 have suggested the presence of multiple binding regions within the P450 active site based on probe substrate-dependent inhibition profiles, similar studies have not been performed with CYP2C8. The ability to understand CYP2C8 probe substrate sensitivity will enable appropriate in vitro and in vivo probe selection. To characterize the potential for probe substrate-dependent inhibition with CYP2C8, the inhibition potency of 22 known inhibitors of CYP2C8 were measured in vitro using four clinically relevant CYP2C8 probe substrates (montelukast, paclitaxel, repaglinide, and rosiglitazone) and amodiaquine. Repaglinide exhibited the highest sensitivity to inhibition in vitro. In vitro phenotyping indicated that montelukast is an appropriate probe for CYP2C8 inhibition studies. The in vivo sensitivities of the CYP2C8 probe substrates cerivastatin, fluvastatin, montelukast, pioglitazone, and rosiglitazone were determined in relation to repaglinide on the basis of clinical drug-drug interaction (DDI) data. Repaglinide exhibited the highest sensitivity in vivo, followed by cerivastatin, montelukast, and pioglitazone. Finally, the magnitude of in vivo CYP2C8 DDI caused by gemfibrozil-1-O-␤-glucuronide was predicted. Comparisons of the predictions with clinical data coupled with the potential liabilities of other CYP2C8 probes suggest that montelukast is an appropriate CYP2C8 probe substrate to use for the in vivo situation.

Three secondary amines desipramine (DES), (S)-fluoxetine [(S)-

ABSTRACT:Predicting the magnitude of potential drug-drug interactions is important for underwriting patient safety in the clinical setting. Substrate-dependent inhibition of cytochrome P450 enzymes may confound extrapolation of in vitro results to the in vivo situation. However, the potential for substrate-dependent inhibition with CYP2D6 has not been well characterized. The inhibition profiles of 20 known inhibitors of CYP2D6 were characterized in vitro against four clinically relevant CYP2D6 substrates (desipramine, dextromethorphan, metoprolol, and thioridazine) and bufuralol. Dextromethorphan exhibited the highest sensitivity to in vitro inhibition, whereas metoprolol was the least sensitive. In addition, when metoprolol was the substrate, inhibitors with structurally constrained amino moieties (clozapine, debrisoquine, harmine, quinidine, and yohimbine) exhibited at least a 5-fold decrease in inhibition potency when results were compared with those for dextromethorphan. Atypical inhibition kinetics were observed for these and other inhibitor-substrate pairings. In silico docking studies suggested that interactions with Glu216 and an adjacent hydrophobic binding pocket may influence substrate sensitivity and inhibition potency for CYP2D6. The in vivo sensitivities of the clinically relevant CYP2D6 substrates desipramine, dextromethorphan, and metoprolol were determined on the basis of literature drug-drug interaction (DDI) outcomes. Similar to the in vitro results, dextromethorphan exhibited the highest sensitivity to CYP2D6 inhibition in vivo. Finally, the magnitude of in vivo CYP2D6 DDIs caused by quinidine was predicted using desipramine, dextromethorphan, and metoprolol. Comparisons of the predictions with literature results indicated that the marked decrease in inhibition potency observed for the metoprolol-quinidine interaction in vitro translated to the in vivo situation.

CYP3A4-mediated biotransformation of (R)-N-(1-(3-(4-ethoxyphenyl)-4-oxo-3,4-dihydropyrido[2,3-d]pyrimidin-2-yl)ethyl)-N-(pyridin-3). TDI investigations using an IC 50 shift method successfully produced inhibition attributable to AMG 487, but only when preincubations were extended from 30 to 90 min. The shift magnitude was ϳ3؋ for midazolam activity, but no shift was observed for testosterone activity. Subsequent partition ratio determinations conducted for M2 using recombinant CYP3A4 showed that inactivation was a relatively inefficient process (r ‫؍‬ 36

Recent guidance on drug-drug interaction (DDI) testing recommends evaluation of circulating metabolites. However, there is little consensus on how to quantitatively predict and/or assess the risk of in vivo DDIs by multiple time-dependent inhibitors (TDIs) including metabolites from in vitro data. Fluoxetine was chosen as the model drug to evaluate the role of TDI metabolites in DDI prediction because it is a TDI of both CYP3A4 and CYP2C19 with a circulating N-dealkylated inhibitory metabolite, norfluoxetine. In pooled human liver microsomes, both enantiomers of fluoxetine and norfluoxetine were TDIs of CYP2C19, (S)-norfluoxetine was the most potent inhibitor with time-dependent inhibition affinity constant (K I ) of 7 mM, and apparent maximum time-dependent inhibition rate (k inact,app ) of 0.059 min 21. Only (S)-fluoxetine and (R)-norfluoxetine were TDIs of CYP3A4, with (R)-norfluoxetine being the most potent (K I = 8 mM, and k inact,app = 0.011 min 21).Based on in-vitro-to-in-vivo predictions, (S)-norfluoxetine plays the most important role in in vivo CYP2C19 DDIs, whereas (R)-norfluoxetine is most important in CYP3A4 DDIs. Comparison of two multiple TDI prediction models demonstrated significant differences between them in in-vitro-to-in-vitro predictions but not in in-vitro-to-in-vivo predictions. Inclusion of all four inhibitors predicted an in vivo decrease in CYP2C19 (95%) and CYP3A4 (60-62%) activity. The results of this study suggest that adequate worst-case risk assessment for in vivo DDIs by multiple TDI systems can be achieved by incorporating time-dependent inhibition by both parent and metabolite via simple addition of the in vivo time-dependent inhibition rate/cytochrome P450 degradation rate constant (l/k deg ) values, but quantitative DDI predictions will require a more thorough understanding of TDI mechanisms.