Contribution of Major Metabolites toward Complex Drug-Drug Interactions of Deleobuvir: In Vitro Predictions and In Vivo Outcomes

Improving the Working Models for Drug-Drug Interactions: Impact on Preclinical and Clinical Drug Development

Background: Pharmacokinetic drug-drug interactions (DDIs) can be caused by the effect of a pharmaceutical compound on the activity of one or more subtypes of the Cytochrome P450 (CYP) family, UDP-glucuronosyltransferases (UGTs), and/or transporters. As the number of therapeutic areas with polypharmacy has increased, interest has grown in assessing the risk of DDIs during the early phases of drug development. Various lines of research have led to improved mathematical models to predict DDIs, culminating in the Food and Drug Administration's (FDA) guidelines on evaluating pharmacokinetic DDI risks. However, the recommended static models are highly conservative and often result in false positive predictions. The current research aims to improve the workflow for assessing CYP-mediated DDI risk using Boehringer Ingelheim (BI) proprietary compounds. Methods: The Drug-drug Interaction Risk Calculator (PharmaPendium) was used to evaluate the mechanistic static model, and predictions were correlated with human pharmacokinetic studies from Phase I clinical trials. Results: The results demonstrated that the FDA formula performed well in predicting DDIs for BI proprietary compounds. Furthermore, the integration of either human renal excretion or preclinical species total excretion data into the mechanistic static model enhanced the predictive performance for candidate drugs as victims in DDIs. Conclusions: The basic static models (BSMs) for drug interactions should be used in early drug discovery to "rule out" DDI risks because of the minimal inputs required and the low rate of false negative predictions. Mechanistic static models (MSMs) can then be implemented for compounds that require additional evaluation.

Screening of 16 major drug glucuronides for time-dependent inhibition of nine drug-metabolizing CYP enzymes - detailed studies on CYP3A inhibitors

Time-dependent inhibition of cytochrome P450 (CYP) enzymes has been observed for a few glucuronide metabolites of clinically used drugs. Here, we investigated the inhibitory potential of 16 glucuronide metabolites towards nine major CYP enzymes in vitro. Automated substrate cocktail methods were used to screen time-dependent inhibition of CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2J2 and 3A in human liver microsomes. Seven glucuronides (carvedilol β-D-glucuronide, diclofenac acyl-β-D-glucuronide, 4-hydroxyduloxetine β-D-glucuronide, ezetimibe phenoxy-β-D-glucuronide, raloxifene 4'-glucuronide, repaglinide acyl-β-D-glucuronide and valproic acid β-D-glucuronide) caused NADPH- and time-dependent inhibition of at least one of the CYPs investigated, including CYP2A6, CYP2C19 and CYP3A. In more detailed experiments, we focused on the glucuronides of carvedilol and diclofenac, which inhibited CYP3A. Carvedilol β-D-glucuronide showed weak time-dependent inhibition of CYP3A, but the parent drug carvedilol was found to be a more potent inhibitor of CYP3A, with the half-maximal inhibitor concentration (IC50) decreasing from 7.0 to 1.1 µM after a 30-min preincubation with NADPH. The maximal inactivation constant (kinact) and the inhibitor concentration causing half of kinact (KI) for CYP3A inactivation by carvedilol were 0.051 1/min and 1.8 µM, respectively. Diclofenac acyl-β-D-glucuronide caused time-dependent inactivation of CYP3A at high concentrations, with a 4-fold IC50 shift (from 400 to 98 µM after a 30-min preincubation with NADPH) and KI and kinact values of >2,000 µM and >0.16 1/min. In static predictions, carvedilol caused significant (>1.25-fold) increase in the exposure of the CYP3A substrates midazolam and simvastatin. In conclusion, we identified several glucuronide metabolites with CYP inhibitory properties. Based on detailed experiments, the inactivation of CYP3A by carvedilol may cause clinically significant drug-drug interactions.

Construction of a fused grid-based CYP2C8-Template system and the application

A ligand-accessible space in the CYP2C8 active site was reconstituted as a fused grid-based Template∗ with the use of structural data of the ligands. An evaluation system of CYP2C8-mediated metabolism has been developed on Template with the introduction of the idea of Trigger-residue initiated ligand-movement and fastening. Reciprocal comparison of the data of simulation on Template with experimental results suggested a unified way of the interaction of CYP2C8 and its ligands through the simultaneous plural-contact with Rear-wall of Template. CYP2C8 was expected to have a room for ligands between vertically standing parallel walls termed Facial-wall and Rear-wall. Both the walls were separated by a distance corresponding to 1.5-Ring (grid) diameter size, which was termed Width-gauge. The ligand sittings were stabilized through contacts with Facial-wall and the left-side borders of Template including specific Position 29, left-side border of Rings I/J, or Left-end, after Trigger-residue initiated ligand-movement. Trigger-residue movement is suggested to force ligands to stay firmly in the active site and then to initiate CYP2C8 reactions. Simulation experiments for over 350 reactions of CYP2C8 ligands supported the system established.

Inhibitory Mechanisms of Lekethromycin in Dog Liver Cytochrome P450 Enzymes Based on UPLC-MS/MS Cocktail Method

Lekethromycin (LKMS) is a synthetic macrolide compound derivative intended for use as a veterinary medicine. Since there have been no in vitro studies evaluating its potential for drug-drug interactions related to cytochrome P450 (CYP450) enzymes, the effect of the inhibitory mechanisms of LKMS on CYP450 enzymes is still unclear. Thus, this study aimed to evaluate the inhibitory effects of LKMS on dog CYP450 enzymes. A cocktail approach using ultra-performance liquid chromatography-tandem mass spectrometry was conducted to investigate the inhibitory effect of LKMS on canine CYP450 enzymes. Typical probe substrates of phenacetin, coumarin, bupropion, tolbutamide, dextromethorphan, chlorzoxazone, and testosterone were used for CYP1A2, CYP2A6, CYP2B6, CYP2C9, CYP2D6, CYP2E1, and CYP3A4, respectively. This study showed that LKMS might not be a time-dependent inhibitor. LKMS inhibited CYP2A6, CYP2B6, and CYP2D6 via mixed inhibition. LKMS exhibited mixed-type inhibition against the activity of CYP2A6 with an inhibition constant (Ki) value of 135.6 μΜ. LKMS inhibited CYP2B6 in a mixed way, with Ki values of 59.44 μM. A phenotyping study based on an inhibition assay indicated that CYP2D6 contributes to the biotransformation of LKMS. A mixed inhibition of CYP2D6 with Ki values of 64.87 μM was also observed. Given that this study was performed in vitro, further in vivo studies should be conducted to identify the interaction between LKMS and canine CYP450 enzymes to provide data support for the clinical application of LKMS and the avoidance of adverse interactions between other drugs.

Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions: Research Methods and Applications

Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.

Characterization of Correction Factors to Enable Assessment of Clinical Risk from In Vitro CYP3A4 Induction Data and Basic Drug-Drug Interaction Models

Background and Objective

Induction of drug-metabolizing enzymes can lead to drug-drug interactions (DDIs); therefore, early assessment is often conducted. Previous reports focused on true positive cytochrome P450 3A (CYP3A) inducers leaving a gap in translation for in vitro inducers which do not manifest in clinical induction. The goal herein was to expand the in vitro induction dataset by including true negative clinical inducers to identify a correction factor to basic DDI models, which reduces false positives without impacting false negatives.

Methods

True negative clinical inducers were identified through a literature search, in vitro induction parameters were generated in three human hepatocyte donors, and the performance of basic induction models proposed by regulatory agencies, concentration producing twofold induction (F2), basic static model (R3) and relative induction score (RIS), was used to characterize clinical induction risk.

Results

The data demonstrated the importance of correcting for in vitro binding and metabolism to derive induction parameters. The aggregate analysis indicates that the RIS with a positive cut-off of < 0.7-fold area under the curve ratio (AUCR) provides the best quantitative prediction. Additionally, correction factors of ten and two times the unbound peak plasma concentration at steady state (C_max,ss,u) can be confidently used to identify true positive inducers when referenced against the concentration resulting in twofold increase in messenger ribonucleic acid (mRNA) or using the R3 equation, respectively.

Conclusions

These iterative improvements, which reduce the number of false positives, could aid regulatory recommendations and limit unnecessary clinical explorations into CYP3A induction.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13318-022-00763-y.

In Vitro Assessment of the Drug-Drug Interaction Potential of Verinurad and Its Metabolites as Substrates and Inhibitors of Metabolizing Enzymes and Drug Transporters

Verinurad is a selective uric acid transporter 1 (URAT1) inhibitor in development for the treatment of chronic kidney disease and heart failure. In humans, two major acyl glucuronide metabolites have been identified: direct glucuronide M1 and N-oxide glucuronide M8. Using in vitro systems recommended by regulatory agencies, we evaluated the interactions of verinurad, M1, and M8 with major drug-metabolizing enzymes and transporters and the potential for clinically relevant drug-drug interactions (DDIs). The IC50 for inhibition of CYP2C8, CYP2C9, and CYP3A4/5 for verinurad was ≥14.5 µM, and maximum free plasma concentration (Iu,max)/IC50 was <0.02 at the anticipated therapeutic Cmax and therefore not considered a DDI risk. Verinurad was not an inducer of CYP1A2, CYP2B6, or CYP3A4/5. Verinurad was identified as a substrate of the hepatic uptake transporter organic anion-transporting polypeptide (OATP) 1B3. Since verinurad hepatic uptake involved both active and passive transport, there is a low risk of clinically relevant DDIs with OATP, and further study is warranted. Verinurad was a substrate of the efflux transporters P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP), and renal transporter organic anion transporter 1 (OAT1), although it is not considered a DDI risk in vivo because of dose-proportional pharmacokinetics (P-gp and BCRP) and limited renal excretion of verinurad (OAT1). M1 and M8 were substrates of multidrug resistance-associated protein (MRP) 2 and MRP4 and inhibitors of MRP2. Apart from verinurad being a substrate of OATP1B3 in vitro, the potential for clinically relevant DDIs involving verinurad and its metabolites as victims or perpetrators of metabolizing enzymes or drug transporters is considered low. SIGNIFICANCE STATEMENT: Drug transporters and metabolizing enzymes have an important role in the absorption and disposition of a drug and its metabolites. Using in vitro systems recommended by regulatory agencies, we determined that, apart from verinurad being a substrate of organic anion-transporting polypeptide 1B3, the potential for clinically relevant drug-drug interactions involving verinurad and its metabolites M1 and M8 as victims or perpetrators of metabolizing enzymes or drug transporters is considered low.

Recent developments in predicting CYP-independent metabolism

As lead optimization efforts have successfully reduced metabolic liabilities due to cytochrome P450 (CYP)-mediated metabolism, there has been an increase in the frequency of involvement of non-CYP enzymes in the metabolism of investigational compounds. Although there have been numerous notable advancements in the characterization of non-CYP enzymes with respect to their localization, reaction mechanisms, species differences and identification of typical substrates, accurate prediction of non-CYP-mediated clearance, with a particular emphasis with the difficulties in accounting for any extrahepatic contributions, remains a challenge. The current manuscript comprehensively summarizes the recent advancements in the prediction of drug metabolism and the in vitro to in vitro extrapolation of clearance for substrates of non-CYP drug metabolizing enzymes.

Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidance from Regulatory Agencies: Guidelines on Model Fitting and Recommendations on Time Course for In Vitro Cytochrome P450 Induction Studies Including Impact on Drug Interaction Risk Assessment

Translational and ADME Sciences Leadership Group Induction Working Group (IWG) presents an analysis on the time course for cytochrome P450 induction in primary human hepatocytes. Induction of CYP1A2, CYP2B6, and CYP3A4 was evaluated by seven IWG laboratories after incubation with prototypical inducers (omeprazole, phenobarbital, rifampicin, or efavirenz) for 6-72 hours. The effect of incubation duration and model-fitting approaches on induction parameters (Emax and EC50) and drug-drug interaction (DDI) risk assessment was determined. Despite variability in induction response across hepatocyte donors, the following recommendations are proposed: 1) 48 hours should be the primary time point for in vitro assessment of induction based on mRNA level or activity, with no further benefit from 72 hours; 2) when using mRNA, 24-hour incubations provide reliable assessment of induction and DDI risk; 3) if validated using prototypical inducers (>10-fold induction), 12-hour incubations may provide an estimate of induction potential, including characterization as negative if <2-fold induction of mRNA and no concentration dependence; 4) atypical dose-response ("bell-shaped") curves can be addressed by removing points outside an established confidence interval and %CV; 5) when maximum fold induction is well defined, the choice of nonlinear regression model has limited impact on estimated induction parameters; 6) when the maximum fold induction is not well defined, conservative DDI risk assessment can be obtained using sigmoidal three-parameter fit or constraining logistic three- or four-parameter fits to the maximum observed fold induction; 7) preliminary data suggest initial slope of the fold induction curve can be used to estimate Emax/EC50 and for induction risk assessment. SIGNIFICANCE STATEMENT: Regulatory agencies provide inconsistent guidance on the optimum length of time to evaluate cytochrome P450 induction in human hepatocytes, with EMA recommending 72 hours and FDA suggesting 48-72 hours. The Induction Working Group analyzed a large data set generated by seven member companies and determined that induction response and drug-drug risk assessment determined after 48-hour incubations were representative of 72-hour incubations. Additional recommendations are provided on model-fitting techniques for induction parameter estimation and addressing atypical concentration-response curves.

2020 FDA Drug-drug Interaction Guidance: A Comparison Analysis and Action Plan by Pharmaceutical Industrial Scientists

Background:

In January 2020, the US FDA published two final guidelines, one entitled “In vitro Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry” and the other entitled “Clinical Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry”. These were updated from the 2017 draft in vitro and clinical DDI guidance.

Methods:

This study is aimed to provide an analysis of the updates along with a comparison of the DDI guidelines published by the European Medicines Agency (EMA) and Japanese Pharmaceuticals and Medical Devices Agency (PMDA) along with the current literature.

Results:

The updates were provided in the final FDA DDI guidelines and explained the rationale of those changes based on the understanding from research and literature. Furthermore, a comparison among the FDA, EMA, and PMDA DDI guidelines are presented in Tables 1, 2 and 3.

Conclusion:

The new 2020 clinical DDI guidance from the FDA now has even higher harmonization with the guidance (or guidelines) from the EMA and PMDA. A comparison of DDI guidance from the FDA 2017, 2020, EMA, and PMDA on CYP and transporter based DDI, mathematical models, PBPK, and clinical evaluation of DDI is presented in this review.

In Vitro Drug-Drug Interaction Evaluation of GalNAc Conjugated siRNAs Against CYP450 Enzymes and Transporters

Small interfering RNAs (siRNAs) represent a new class of medicines that are smaller (∼16,000 Da) than biologic therapeutics (>150,000 Da) but much larger than small molecules (<900 Da). Current regulatory guidance on drug-drug interactions (DDIs) from the European Medicines Agency, Food and Drug Administration, and Pharmaceutical and Medical Devices Agency provides no recommendations for oligonucleotide therapeutics including siRNAs; therefore, small molecule guidance documents have historically been applied. Over ∼10 years, in vitro DDI investigations with siRNAs conjugated to a triantennary N-acetylgalactosamine [(GalNAc)-siRNA] ligand have been conducted during nonclinical drug development to elucidate the potential clinical DDI liability. GalNAc siRNAs were evaluated as substrates, inhibitors, or inducers of major cytochrome P450s (P450s) and as substrates and inhibitors of transporters. Aggregate analysis of these data demonstrates a low potential for DDI against P450s. Zero of five, 10, and seven are inducers, time-dependent inhibitors, or substrates, respectively, and nine of 12 do not inhibit any P450 isoform evaluated. Three GalNAc siRNAs inhibited CYP2C8 at supratherapeutic concentrations, and one mildly inhibited CYP2B6. The lowest K i value of 28 µM is >3000-fold above the therapeutic clinical C max at steady state, and importantly no clinical inhibition was projected. Of four GalNAc siRNAs tested none were substrates for transporters and one caused inhibition of P-glycoprotein, calculated not to be clinically relevant. The pharmacological basis for DDIs, including consideration of the target and/or off-target profiles for GalNAc siRNAs, should be made as part of the overall DDI risk assessment. If modulation of the target protein does not interfere with P450s or transporters, then in vitro or clinical investigations into the DDI potential of the GalNAc siRNAs are not warranted. SIGNIFICANCE STATEMENT: Recommendations for evaluating DDI potential of small molecule drugs are well established; however, guidance for novel modalities, particularly oligonucleotide-based therapeutics are lacking. Given the paucity of published data in this field, in vitro DDI investigations are often conducted. The aggregate analysis of GalNAc-siRNA data reviewed herein demonstrates that, like new biological entities, these oligonucleotide-based therapeutic drugs are unlikely to result in DDIs; therefore, it is recommended that the need for in vitro or clinical investigations similarly be determined on a case-by-case basis. Given the mechanism of siRNA action, special consideration should be made in cases where there may be a pharmacological basis for DDIs.

Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidances from Regulatory Agencies: Focus on CYP3A4 mRNA In Vitro Response Thresholds, Variability, and Clinical Relevance

The Innovation and Quality Induction Working Group presents an assessment of best practice for data interpretation of in vitro induction, specifically, response thresholds, variability, application of controls, and translation to clinical risk assessment with focus on CYP3A4 mRNA. Single concentration control data and Emax/EC50 data for prototypical CYP3A4 inducers were compiled from many human hepatocyte donors in different laboratories. Clinical CYP3A induction and in vitro data were gathered for 51 compounds, 16 of which were proprietary. A large degree of variability was observed in both the clinical and in vitro induction responses; however, analysis confirmed in vitro data are able to predict clinical induction risk. Following extensive examination of this large data set, the following recommendations are proposed. a) Cytochrome P450 induction should continue to be evaluated in three separate human donors in vitro. b) In light of empirically divergent responses in rifampicin control and most test inducers, normalization of data to percent positive control appears to be of limited benefit. c) With concentration dependence, 2-fold induction is an acceptable threshold for positive identification of in vitro CYP3A4 mRNA induction. d) To reduce the risk of false positives, in the absence of a concentration-dependent response, induction ≥ 2-fold should be observed in more than one donor to classify a compound as an in vitro inducer. e) If qualifying a compound as negative for CYP3A4 mRNA induction, the magnitude of maximal rifampicin response in that donor should be ≥ 10-fold. f) Inclusion of a negative control adds no value beyond that of the vehicle control.

Chemo-Enzymatic Synthesis, Structural and Stereochemical Characterization, and Intrinsic Degradation Kinetics of Diastereomers of 1-β-O-Acyl Glucuronides Derived from Racemic 2-{4-[(2-Methylprop-2-en-1-yl)amino]phenyl}propanoic Acid

Alminoprofen, (RS)-2-{4-[(2-methylprop-2-en-1-yl)amino]phenyl}propanoic acid (ALP) 1, is a racemic drug categorized as a 2-arylpropanoic acid-class nonsteroidal anti-inflammatory drug. Pharmacokinetic studies of 1 in patients have revealed that the corresponding acyl glucuronide 5 is a major urinary metabolite, but little is known about the structure and stereochemistry of 5. The present work describes the synthesis of a diastereomeric mixture of 1-β-O-acyl glucuronides (2RS)-5 from 1 and methyl 2,3,4-tri-O-acetyl-1-bromo-1-deoxy-α-d-glucopyranuronate 2 using our chemo-enzymatic method that has complete specificity for the β-configuration. The structure of (2RS)-5 was characterized by ¹H and ¹³C NMR spectroscopy and high-resolution mass spectrometry as well as by complete hydrolysis by β-glucuronidase. The absolute stereochemistry of (2RS)-5 was determined by comparison with (2R)-5 synthesized alternatively from (2R)-1 and 2. Compound (2R)-1 was prepared in two steps starting from chiral (R)-2-(4-nitrophenyl)propanoic acid (2R)-6. Chiral resolution of (2RS)-1 was achieved using a chiral high-performance liquid chromatography column, and its stereochemistry was determined by comparison with (2R)-1. The intrinsic degradation rate constant of (2R)-5 was 0.405 ± 0.002 h^-1, which is approximately twice that of (2S)-5 (the k value was 0.226 ± 0.002 h^-1) under physiological conditions (pH 7.40, 37 °C).

Cell cultures in drug discovery and development: The need of reliable in vitro-in vivo extrapolation for pharmacodynamics and pharmacokinetics assessment

For ethical and cost-related reasons, use of animals for the assessment of mode of action, metabolism and/or toxicity of new drug candidates has been increasingly scrutinized in research and industrial applications. Implementation of the 3 "Rs"¹; rule (Reduction, Replacement, Refinement) through development of in silico or in vitro assays has become an essential element of risk assessment. Physiologically based pharmacokinetic (PBPK²) modeling is the most potent in silico tool used for extrapolation of pharmacokinetic parameters to animal or human models from results obtained in vitro. Although, many types of in vitro assays are conducted during drug development, use of cell cultures is the most reliable one. Two-dimensional (2D) cell cultures have been a part of drug development for many years. Nowadays, their role is decreasing in favor of three-dimensional (3D) cell cultures and co-cultures. 3D cultures exhibit protein expression patterns and intercellular junctions that are closer to in vivo states in comparison to classical monolayer cultures. Co-cultures allow for examinations of the mutual influence of different cell lines. However, the complexity and high costs of co-cultures and 3D equipment exclude such methods from high-throughput screening (HTS).³In vitro absorption, distribution, metabolism, and excretion assessment, as well as drug-drug interaction (DDI), are usually performed with the use of various cell culture based assays. Progress in in silico and in vitro methods can lead to better in vitro-in vivo extrapolation (IVIVE⁴) outcomes and have a potential to contribute towards a significant reduction in the number of laboratory animals needed for drug research. As such, concentrated efforts need to be spent towards the development of an HTS in vitro platform with satisfactory IVIVE features.

Role of gemfibrozil as an inhibitor of CYP2C8 and membrane transporters

INTRODUCTION

Cytochrome P450 (CYP) 2C8 is a drug metabolizing enzyme of major importance. The lipid-lowering drug gemfibrozil has been identified as a strong inhibitor of CYP2C8 in vivo. This effect is due to mechanism-based inhibition of CYP2C8 by gemfibrozil 1-O-β-glucuronide. In vivo, gemfibrozil is a fairly selective CYP2C8 inhibitor, which lacks significant inhibitory effect on other CYP enzymes. Gemfibrozil can, however, have a smaller but clinically meaningful inhibitory effect on membrane transporters, such as organic anion transporting polypeptide 1B1 and organic anion transporter 3. Areas covered: This review describes the inhibitory effects of gemfibrozil on CYP enzymes and membrane transporters. The clinical drug interactions caused by gemfibrozil and the different mechanisms contributing to the interactions are reviewed in detail. Expert opinion: Gemfibrozil is a useful probe inhibitor of CYP2C8 in vivo, but its effect on membrane transporters has to be taken into account in study design and interpretation. Moreover, gemfibrozil could be used to boost the pharmacokinetics of CYP2C8 substrate drugs. Identification of gemfibrozil 1-O-β-glucuronide as a potent mechanism-based inhibitor of CYP2C8 has led to recognition of glucuronide metabolites as perpetrators of drug-drug interactions. Recently, also acyl glucuronide metabolites of clopidogrel and deleobuvir have been shown to strongly inhibit CYP2C8.

Clopidogrel Markedly Increases Plasma Concentrations of CYP2C8 Substrate Pioglitazone

The glucose-lowering drug pioglitazone undergoes hepatic CYP2C8-mediated biotransformation to its main metabolites. The antiplatelet drug clopidogrel is metabolized to clopidogrel acyl-β-d-glucuronide, which was recently found to be a strong time-dependent inhibitor of CYP2C8 in humans. Therefore, we studied the effect of clopidogrel on the pharmacokinetics of pioglitazone. In a randomized crossover study, 10 healthy volunteers ingested either 300 mg of clopidogrel on day 1, and 75 mg on days 2 and 3, or placebo. Pioglitazone 15 mg was administered 1 hour after placebo and clopidogrel on day 1. Plasma concentrations of pioglitazone, clopidogrel, and their main metabolites were measured up to 72 hours. Clopidogrel increased the area under the plasma concentration-time curve (AUC0-∞) of pioglitazone 2.1-fold [P < 0.001, 90% confidence interval (CI) 1.8-2.6] and prolonged its half-life from 6.7 to 11 hours (P = 0.002). The peak concentration of pioglitazone was unaffected but the concentration at 24 hours was increased 4.5-fold (range 1.6-9.8; P < 0.001, 90% CI 3.17-6.45) by clopidogrel. The M-IV-to-pioglitazone AUC0-∞ ratio was 49% (P < 0.001, 90% CI 0.40-0.59) of that during the control phase, indicating that clopidogrel inhibited the CYP2C8-mediated biotransformation of pioglitazone. Clopidogrel increases the exposure to pioglitazone by inhibiting its CYP2C8-mediated biotransformation. In consequence, use of clopidogrel may increase the risk of fluid retention and other concentration-related adverse effects of pioglitazone.

Cytochrome P450 and Non-Cytochrome P450 Oxidative Metabolism: Contributions to the Pharmacokinetics, Safety, and Efficacy of Xenobiotics

The drug-metabolizing enzymes that contribute to the metabolism or bioactivation of a drug play a crucial role in defining the absorption, distribution, metabolism, and excretion properties of that drug. Although the overall effect of the cytochrome P450 (P450) family of drug-metabolizing enzymes in this capacity cannot be understated, advancements in the field of non-P450-mediated metabolism have garnered increasing attention in recent years. This is perhaps a direct result of our ability to systematically avoid P450 liabilities by introducing chemical moieties that are not susceptible to P450 metabolism but, as a result, may introduce key pharmacophores for other drug-metabolizing enzymes. Furthermore, the effects of both P450 and non-P450 metabolism at a drug's site of therapeutic action have also been subject to increased scrutiny. To this end, this Special Section on Emerging Novel Enzyme Pathways in Drug Metabolism will highlight a number of advancements that have recently been reported. The included articles support the important role of non-P450 enzymes in the clearance pathways of U.S. Food and Drug Administration-approved drugs over the past 10 years. Specific examples will detail recent reports of aldehyde oxidase, flavin-containing monooxygenase, and other non-P450 pathways that contribute to the metabolic, pharmacokinetic, or pharmacodynamic properties of xenobiotic compounds. Collectively, this series of articles provides additional support for the role of non-P450-mediated metabolic pathways that contribute to the absorption, distribution, metabolism, and excretion properties of current xenobiotics.

Role of Cytochrome P450 2C8 in Drug Metabolism and Interactions

During the last 10-15 years, cytochrome P450 (CYP) 2C8 has emerged as an important drug-metabolizing enzyme. CYP2C8 is highly expressed in human liver and is known to metabolize more than 100 drugs. CYP2C8 substrate drugs include amodiaquine, cerivastatin, dasabuvir, enzalutamide, imatinib, loperamide, montelukast, paclitaxel, pioglitazone, repaglinide, and rosiglitazone, and the number is increasing. Similarly, many drugs have been identified as CYP2C8 inhibitors or inducers. In vivo, already a small dose of gemfibrozil, i.e., 10% of its therapeutic dose, is a strong, irreversible inhibitor of CYP2C8. Interestingly, recent findings indicate that the acyl-β-glucuronides of gemfibrozil and clopidogrel cause metabolism-dependent inactivation of CYP2C8, leading to a strong potential for drug interactions. Also several other glucuronide metabolites interact with CYP2C8 as substrates or inhibitors, suggesting that an interplay between CYP2C8 and glucuronides is common. Lack of fully selective and safe probe substrates, inhibitors, and inducers challenges execution and interpretation of drug-drug interaction studies in humans. Apart from drug-drug interactions, some CYP2C8 genetic variants are associated with altered CYP2C8 activity and exhibit significant interethnic frequency differences. Herein, we review the current knowledge on substrates, inhibitors, inducers, and pharmacogenetics of CYP2C8, as well as its role in clinically relevant drug interactions. In addition, implications for selection of CYP2C8 marker and perpetrator drugs to investigate CYP2C8-mediated drug metabolism and interactions in preclinical and clinical studies are discussed.