Integrated in Vitro Analysis for the in Vivo Prediction of Cytochrome P450-Mediated Drug-Drug Interactions

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.

Section: Fig 2 Docking Resultsmentioning

confidence: 57%

Section: Introductionmentioning

confidence: 99%

Prediction of CYP2D6 Drug Interactions from In Vitro Data: Evidence for Substrate-Dependent Inhibition

VandenBrink¹,

Foti²,

Rock³

et al. 2011

“…Many of the key experiments and details have been reviewed (Lu et al, 2003;Zhang et al, 2007;McGinnity et al, 2008). However, even with the application of careful technique, the current practices are hindered by the incomplete P450 inhibition obtained with commercial antibodies.…”

Section: Discussionmentioning

confidence: 99%

The Combination of Chemical and Antibody Inhibitors for Superior P450 3A Inhibition in Reaction Phenotyping Studies

Rock¹,

Foti²,

Pearson³

2008

ABSTRACT:Cytochrome P450 (P450) reaction phenotyping is a key process toward accurately determining the contribution of different P450s to the metabolism of new chemical entities. The significance of P450s to drug disposition has led to the identification of selective chemical and antibody inhibitors for individual P450 enzymes. Despite these advances, the maximal inhibition attainable is limited by the use of inhibitor concentrations that maintain selectivity for the individual P450s. Thus, most commercially available inhibitors produce a maximal inhibition of ϳ80%. Herein, the combination of chemical plus antibody inhibitors is explored to find whether P450 3A could be selectively and completely (>99%) inhibited by using both inhibitors simultaneously.The majority of marketed drugs are metabolized by members of the cytochrome P450 (P450) superfamily of enzymes (Wienkers and Heath, 2005). Given the limited number of P450 enzymes that contribute to the clearance of commercial therapeutics, P450s represent the primary source of clinically observed drug interactions in patients. In vitro techniques have evolved to enable the early estimation of drug interaction potential with preclinical drug candidates either as perpetrator or victim prior to clinical evaluation (Lu et al., 2003).The improved extrapolation of in vitro data to humans over the last decade is partially attributed to the inclusion of additional parameters that impact the scaling of in vitro data. For example, considering unbound fraction of drug during in vitro microsomal incubations and attempts to approximate the most appropriate inhibitor concentration in vivo can improve in vitro extrapolations (Margolis and Obach, 2003;Obach et al., 2005Obach et al., , 2006. Furthermore, a retrospective analysis of disparate in vitro estimates of drug interactions compared with clinically observed interactions illustrates that predictions can be improved when the fraction of drug metabolized through individual P450 pathways is accurately determined (Fig. 1) (Ito et al., 2005). P450 reaction phenotyping is used to determine fraction of drug metabolized by P450s and is possible in part because of the accumulation of compounds identified as selective inhibitors of individual P450 enzymes (Cai et al., 2004;Stresser et al., 2004;Walsky et al., 2005b). Additionally, the introduction of selective antibody inhibitors has expanded the diversity of inhibitors available to determine the involvement of different P450 pathways to a drug's clearance. However, commercial antibodies and chemical inhibitors typically do not yield complete inhibition of the P450 enzymes, especially at concentrations that maintain selectivity for the individual P450 enzymes. In the balance to achieve maximal yet selective inhibition of individual P450 enzymes the effective inhibitor concentrations typically result in inhibition up to 80%. The remaining 20% activity reduces the predictive nature of in vitro extrapolation techniques and increases the uncertainty regarding the potential activity from...

“…The commercially available physiologically based pharmacokinetics software package Simcyp (version 13.1.61.0; Simcyp Ltd., Sheffield, UK) was widely used for drug DDI prediction (McGinnity et al, 2008;Youdim et al, 2008;Xu et al, 2009;Shardlow et al, 2013). In this study, the DDI potential of GFA on substrate of CYP2D6 in humans was predicted based on a physiologically based pharmacokinetics model simulated by Simcyp at 4 mg/kg according to clinical dose.…”

Section: Downloaded Frommentioning

confidence: 99%

Guanfu Base A, an Antiarrhythmic Alkaloid ofAconitum coreanum, Is a CYP2D6 Inhibitor of Human, Monkey, and Dog Isoforms

Sun

Peng

et al. 2015

Guanfu base A (GFA) is a novel heterocyclic antiarrhythmic drug isolated from Aconitum coreanum (Lèvl.) rapaics and is currently in a phase IV clinical trial in China. However, no study has investigated the influence of GFA on cytochrome P450 (P450) drug metabolism. We characterized the potency and specificity of GFA CYP2D inhibition based on dextromethorphan O-demethylation, a CYP2D6 probe substrate of activity in human, mouse, rat, dog, and monkey liver microsomes. In addition, (+)-bufuralol 19-hydroxylation was used as a CYP2D6 probe for the recombinant form (rCYP2D6), 2D1 (rCYP2D1), and 2D2 (rCYP2D2) activities. Results show that GFA is a potent noncompetitive inhibitor of CYP2D6, with inhibition constant K i = 1.20 6 0.33 mM in human liver microsomes (HLMs) and K i = 0.37 6 0.16 mM for the human recombinant form (rCYP2D6). GFA is also a potent competitive inhibitor of CYP2D in monkey (K i = 0.38 6 0.12 mM) and dog (K i = 2.4 6 1.3 mM) microsomes. However, GFA has no inhibitory activity on mouse or rat CYP2Ds. GFA did not exhibit any inhibition activity on human recombinant CYP1A2, 2A6, 2C8, 2C19, 3A4, or 3A5, but showed slight inhibition of 2B6 and 2E1. Preincubation of HLMs and rCYP2D6 resulted in the inactivation of the enzyme, which was attenuated by GFA or quinidine. Beagle dogs treated intravenously with dextromethorphan (2 mg/ml) after pretreatment with GFA injection showed reduced CYP2D metabolic activity, with the C max of dextrorphan being one-third that of the saline-treated group and area under the plasma concentration-time curve half that of the saline-treated group. This study suggests that GFA is a specific CYP2D6 inhibitor that might play a role in CYP2D6 medicated drug-drug interaction.