Impact of the CYP2C8 *3 polymorphism on the drug-drug interaction between gemfibrozil and pioglitazone

A genetic algorithm-based approach for the prediction of metabolic drug-drug interactions involving CYP2C8 or CYP2B6

BACKGROUND AND OBJECTIVES

A genetic algorithm (GA) approach was developed to predict drug-drug interactions (DDIs) caused by cytochrome P450 2C8 (CYP2C8) inhibition or cytochrome P450 2B6 (CYP2B6) inhibition or induction. Nighty-eight DDIs, obtained from published in vivo studies in healthy volunteers, have been considered using the area under the plasma drug concentration-time curve (AUC) ratios (i.e., ratios of AUC of the drug substrate administered in combination with a DDI perpetrator to AUC of the drug substrate administered alone) to describe the extent of DDI.

METHODS

The following parameters were estimated in this approach: the contribution ratios (CRCYP2B6 and CRCYP2C8, i.e., the fraction of the dose metabolized via CYP2B6 or CYP2C8, respectively) and the inhibitory or inducing potency of the perpetrator drug (IRCYP2B6, IRCYP2C8 and ICCYP2B6, for inhibition of CYP2B6 and CYP2C8, and induction of CYP2B6, respectively). The workflow consisted of three main phases. First, the initial estimates of the parameters were estimated through GA. Then, the model was validated using an external validation. Finally, the parameter values were refined via a Bayesian orthogonal regression using all data.

RESULTS

The AUC ratios of 5 substrates, 11 inhibitors and 19 inducers of CYP2B6, and the AUC ratios of 19 substrates and 23 inhibitors of CYP2C8 were successfully predicted by the developed methodology within 50-200% of observed values.

CONCLUSIONS

The approach proposed in this work may represent a useful tool for evaluating the suitable doses of a CYP2C8 or CYP2B6 substrates co-administered with perpetrators.

Meta-analysis of the global distribution of clinically relevant CYP2C8 alleles and their inferred functional consequences

BACKGROUND

CYP2C8 is responsible for the metabolism of 5% of clinically prescribed drugs, including antimalarials, anti-cancer and anti-inflammatory drugs. Genetic variability is an important factor that influences CYP2C8 activity and modulates the pharmacokinetics, efficacy and safety of its substrates.

RESULTS

We profiled the genetic landscape of CYP2C8 variability using data from 96 original studies and data repositories that included a total of 33,185 unrelated participants across 44 countries and 43 ethnic groups. The reduced function allele CYP2C8*2 was most common in West and Central Africa with frequencies of 16-36.9%, whereas it was rare in Europe and Asia (< 2%). In contrast, CYP2C8*3 and CYP2C8*4 were common throughout Europe and the Americas (6.9-19.8% for *3 and 2.3-7.5% for *4), but rare in African and East Asian populations. Importantly, we observe pronounced differences (> 2.3-fold) between neighboring countries and even between geographically overlapping populations. Overall, we found that 20-60% of individuals in Africa and Europe carry at least one CYP2C8 allele associated with reduced metabolism and increased adverse event risk of the anti-malarial amodiaquine. Furthermore, up to 60% of individuals of West African ancestry harbored variants that reduced the clearance of pioglitazone, repaglinide, paclitaxel and ibuprofen. In contrast, reduced function alleles are only found in < 2% of East Asian and 8.3-12.8% of South and West Asian individuals.

CONCLUSIONS

Combined, the presented analyses mapped the genetic and inferred functional variability of CYP2C8 with high ethnogeographic resolution. These results can serve as a valuable resource for CYP2C8 allele frequencies and distribution estimates of CYP2C8 phenotypes that could help identify populations at risk upon treatment with CYP2C8 substrates. The high variability between ethnic groups incentivizes high-resolution pharmacogenetic profiling to guide precision medicine and maximize its socioeconomic benefits, particularly for understudied populations with distinct genetic profiles.

An improved method for cytochrome p450 reaction phenotyping using a sequential qualitative-then-quantitative approach

Cytochrome P450 reaction phenotyping to determine the fraction of metabolism values (fm) for individual enzymes is a standard study in the evaluation of a new drug. However, there are technical challenges in these studies caused by shortcomings in the selectivity of P450 inhibitors and unreliable scaling procedures for recombinant P450 (rCYP) data. In this investigation, a two-step "qualitative-then-quantitative" approach to P450 reaction phenotyping is described. In the first step, each rCYP is tested qualitatively for potential to generate metabolites. In the second step, selective inhibitors for the P450s identified in step1 are tested for their effects on metabolism using full inhibition curves. Forty-eight drugs were evaluated in step 1 and there were no examples of missing an enzyme important to in vivo clearance. Five drugs (escitalopram, fluvastatin, pioglitazone, propranolol, and risperidone) were selected for full phenotyping in step2 to determine fm values, with findings compared to fm values estimated from single inhibitor concentration data and rCYP with intersystem-extrapolation-factor corrections. The two-step approach yielded fm values for major drug clearing enzymes that are close to those estimated from clinical data: escitalopram and CYP2C19 (0.42 vs 0.36-0.82), fluvastatin and CYP2C9 (0.76 vs 0.76), pioglitazone and CYP2C8 (0.72 vs 0.73), propranolol and CYP2D6 (0.68 vs 0.37-0.56) and risperidone and CYP2D6 (0.60 vs 0.66-0.88). Reaction phenotyping data generated in this fashion should offer better input to physiologically-based pharmacokinetic models for prediction of DDI and impact of genetic polymorphisms on drug clearance. The qualitative-then-quantitative approach is proposed as a replacement to standard reaction phenotyping strategies. Significance Statement P450 reaction phenotyping is important for projecting drug-drug interactions and interpatient variability in drug exposure. However, currently recommended practices can frequently fail to provide reliable estimates of the fractional contributions of specific P450 enzymes (fm) to drug clearance. In this report, we describe a two-step qualitative-then-quantitative reaction phenotyping approach that yields more accurate estimates of fm.

A Quantitative Approach to the Prediction of Drug-Drug Interactions Mediated by Cytochrome P450 2C8 Inhibition

BACKGROUND

Ohno and Colleagues proposed an approach for predicting drug-drug interactions (DDIs) mediated by cytochrome P450 (CYP) 3A4 based on the use of the ratio of the inhibited to non-inhibited area under the plasma concentration time curve (AUC) of substrates to estimate the fraction of the dose metabolized via CYP3A4 (contribution ratio, CR) and the in vivo inhibitory potency of a perpetrator (inhibition ratio, IR). This study evaluated the performance of this approach on DDIs mediated by CYP2C8 inhibitors.

RESEARCH DESIGN AND METHODS

Initial estimates of CR and IR of CYP2C8 substrates and inhibitors were calculated for 33 DDI in vivo studies. The approach was externally validated with 17 additional studies. Bayesian orthogonal regression was used to refine the estimates of the parameters. Assessment of prediction success was conducted by plotting observed versus predicted AUC ratios.

RESULTS

Final estimates of CRs and IRs were obtained for 19 CYP2C8 substrates and 23 inhibitors, respectively. The method demonstrated good predictive capacity, with only two values outside of the prespecified limits.

CONCLUSIONS

The approach may help to adapt dose regimens for CYP2C8 substrates when given in combination with CYP2C8 inhibitors and to map the potential DDIs of new molecular entities.

Variability of CYP2C8 Polymorphisms in Three Jordanian Populations: Circassians, Chechens and Jordanian-Arabs

CYP2C8 is a member of Cytochrome P450 enzymes system. It plays an important role in metabolizing a wide range of exogenous and endogenous compounds. CYP2C8 is involved in the metabolism of more than 100 drugs, typical substrates include: anticancer agents, antidiabetic agents, antimalarial agents, lipid lowering drugs and many others that constitute 20% of clinically prescribed drugs. Genetic variations of CYP2C8 have been reported with different frequencies in different populations. These genetic polymorphisms can lead to differences in the efficacy and safety of different types of medications metabolized by CYP2C8. The aim of this study was to investigate the allele frequencies of CYP2C8*3 (rs10509681 and rs11572080) and CYP2C8*4 (rs1058930) polymorphisms in three populations living in Jordan; Circassians and Chechens and Jordanian-Arabs and compare those frequencies with other populations. A total of 200 healthy Jordanians, 93 Circassians and 88 Chechens were included in this study. Genotyping of CYP2C8*3 and CYP2C8*4 polymorphisms was done by using polymerase chain reaction (PCR) followed by Restriction Fragment Length Polymorphism (RFLP). Using the Chi-square test, we found that the prevalence of CYP2C8*3 and *4 among the three populations were significantly different. Moreover, the mutant allele CYP2C8*3 (416A) was only detected in the Jordanian-Arab population with an allele frequency of 0.082, while the mutant allele CYP2C8*4 (792G) was detected with frequencies of 0.065, 0.122, 0.017 in Jordanian-Arabs, Circassians and Chechens, respectively. As our results show, CYP2C8*3 was undetectable in our Circassians and Chechens samples, on the other hand, Circassians had the highest allele frequency of CYP2C8*4 compared to Chechens and Jordanian-Arabs. These genetic variations of the gene encoding the CYP2C8 drug metabolizing enzymes can lead to clinical differences in drug metabolism and ultimately variations in drug effectiveness and toxicities. This study provides evidence for the importance of personalized medicine in these populations and can be the foundation for future clinical studies.

Utilizing Large Electronic Medical Record Data Sets to Identify Novel Drug-Gene Interactions for Commonly Used Drugs

Real-world prescribing of drugs differs from the experimental systems, physiological-pharmacokinetic models, and clinical trials used in drug development and licensing, with drugs often used in patients with multiple comorbidities with resultant polypharmacy. The increasing availability of large biobanks linked to electronic healthcare records enables the potential to identify novel drug-gene interactions in large populations of patients. In this study we used three Scottish cohorts and UK Biobank to identify drug-gene interactions for the 50 most commonly used drugs and 162 variants in genes involved in drug pharmacokinetics. We defined two phenotypes based upon prescribing behavior-drug-stop or dose-decrease. Using this approach, we replicate 11 known drug-gene interactions including, for example, CYP2C9/CYP2C8 variants and sulfonylurea/thiazolidinedione prescribing and ABCB1/ABCG2 variants and statin prescribing. We identify eight novel associations after Bonferroni correction, three of which are replicated or validated in the UK Biobank or have other supporting results: The C-allele at rs4918758 in CYP2C9 was associated with a 25% (15-44%) lower odds of dose reduction of quinine, P = 1.6 × 10^-5 ; the A-allele at rs9895420 in ABCC3 was associated with a 46% (24-62%) reduction in odds of dose reduction with doxazosin, P = 1.2 × 10^-4 , and altered blood pressure response in the UK Biobank; the CYP2D6*2 variant was associated with a 30% (18-40%) reduction in odds of stopping ramipril treatment, P = 1.01 × 10^-5 , with similar results seen for enalapril and lisinopril and with other CYP2D6 variants. This study highlights the scope of using large population bioresources linked to medical record data to explore drug-gene interactions at scale.

Clopidogrel, a CYP2C8 inhibitor, causes a clinically relevant increase in the systemic exposure to the active metabolite of selexipag in healthy subjects

Aims

Selexipag is a prostacyclin receptor agonist approved for the treatment of pulmonary arterial hypertension. Cytochrome P450 (CYP) 2C8 is involved in the metabolism of selexipag and its active metabolite, ACT‐333679. This study evaluated the interaction of selexipag and clopidogrel, a CYP2C8 inhibitor.

Methods

The study had a 2‐treatment, 1‐sequence, crossover design. Pharmacokinetics (PK) and CYP2C8 genotype were assessed in healthy male subjects administered selexipag (200 μg twice daily [b.i.d.]) alone or with clopidogrel (300 mg single dose or 75 mg once daily [o.d.]). PK modelling and simulation were conducted to support dosing recommendations.

Results

Clopidogrel had a comparatively small effect on selexipag (<1.5‐fold difference in any PK variable). For ACT‐333679, the major contributor to the drug effect, the area under the plasma concentration–time curve during a dose interval and the maximum plasma concentration increased 2.25‐fold (90% confidence interval [CI] 2.06, 2.46) and 1.69‐fold (90% CI 1.55, 1.84), respectively with clopidogrel 300 mg and 2.70‐fold (90% CI 2.45, 2.96) and 1.90‐fold (90% CI 1.72, 2.11), respectively with clopidogrel 75 mg. The effect of clopidogrel on selexipag and ACT‐333679 exposure was comparable for all identified CYP2C8 genotypes. PK simulations predicted comparable exposure to ACT‐333679 following selexipag 400 μg b.i.d., 400 μg o.d. in combination with clopidogrel 75 mg o.d and 200 μg b.i.d. with clopidogrel 75 mg o.d.

Conclusion

Results suggest that ACT‐333679 exposure can be maintained within the therapeutic range by reducing selexipag dosing frequency to o.d. or dose to half, when selexipag is coadministered with clopidogrel.

Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine

Type 2 diabetes mellitus (T2DM) is a chronic disease that has reached the levels of a global epidemic. In order to achieve optimal glucose control, it is often necessary to rely on combination therapy of multiple drugs or insulin because uncontrolled glucose levels result in T2DM progression and enhanced risk of complications and mortality. Several antihyperglycemic agents have been developed over time, and T2DM pharmacotherapy should be prescribed based on suitability for the individual patient's characteristics. Pharmacogenetics is the branch of genetics that investigates how our genome influences individual responses to drugs, therapeutic outcomes, and incidence of adverse effects. In this review, we evaluated the pharmacogenetic evidences currently available in the literature, and we identified the top informative genetic variants associated with response to the most common anti-diabetic drugs: metformin, DPP-4 inhibitors/GLP1R agonists, thiazolidinediones, and sulfonylureas/meglitinides. Overall, we found 40 polymorphisms for each drug class in a total of 71 loci, and we examined the possibility of encouraging genetic screening of these variants/loci in order to critically implement decision-making about the therapeutic approach through precision medicine strategies. It is possible then to anticipate that when the clinical practice will take advantage of the genetic information of the diabetic patients, this will provide a useful resource for the prevention of T2DM progression, enabling the identification of the precise drug that is most likely to be effective and safe for each patient and the reduction of the economic impact on a global scale.

Understanding the relevance of herb-drug interaction studies with special focus on interplays: a prerequisite for integrative medicine

Integrative medicine refers to the blending of conventional and evidence-based complementary medicines and therapies with the aim of using the most appropriate of either or both modalities for ultimate patient benefits. One of the major hurdles for the same is the chances of potential herb–drug interactions (HDIs). These HDIs could be beneficial or harmful, or even fatal; therefore, a thorough understanding of the eventualities of HDIs is essential so that a successful integration of the modern and complementary alternative systems of medicine could be achieved. Here, we summarize all the important points related to HDIs, including types, tools/methods for study, and prediction of the HDIs, along with a special focus on interplays between drug metabolizing enzymes and transporters. In addition, this article covers future perspective, with a focus on background endogenous players of interplays and approaches to predict the drug–disease–herb interactions so as to fetch the desired effects of these interactions.

Patients carrying CYP2C8*3 have shorter systemic paclitaxel exposure

AIM

First, evaluate if patients carrying putatively diminished activity CYP2C8 genotype have longer paclitaxel exposure (e.g., time above threshold concentration of 0.05 μM [T_{c >0.05}]). Second, screen additional pharmacogenes for associations with T_{c >0.05}. Methods: Pharmacogene panel genotypes were translated into genetic phenotypes for associations with T_{c >0.05} (n = 58).

RESULTS

Patients with predicted low-activity CYP2C8 had shorter T_{c >0.05} after adjustment for age, body surface area and race (9.65 vs 11.03 hrs, β = 5.47, p = 0.02). This association was attributed to CYP2C8*3 (p = 0.006), not CYP2C8*4 (p = 0.58). Patients with predicted low-activity SLCO1B1 had longer T_{c >0.05} (12.12 vs 10.15 hrs, β = 0.85, p = 0.012).

CONCLUSION

Contrary to previous publications, CYP2C8*3 may confer increased paclitaxel metabolic activity. SLCO1B1 and CYP2C8 genotype may explain some paclitaxel pharmacokinetic variability.

Use of Physiologically Based Pharmacokinetic Modeling to Evaluate the Effect of Chronic Kidney Disease on the Disposition of Hepatic CYP2C8 and OATP1B Drug Substrates

Chronic kidney disease (CKD) differentially affects the pharmacokinetics (PK) of nonrenally cleared drugs via certain pathways (e.g., cytochrome P450 (CYP)2D6); however, the effect on CYP2C8‐mediated clearance is not well understood because of overlapping substrate specificity with hepatic organic anion‐transporting polypeptides (OATPs). This study used physiologically based pharmacokinetic (PBPK) modeling to delineate potential changes in CYP2C8 or OATP1B activity in patients with CKD. Drugs analyzed are predominantly substrates of CYP2C8 (rosiglitazone and pioglitazone), OATP1B (pitavastatin), or both (repaglinide). Following initial model verification, pharmacokinetics (PK) of these drugs were simulated in patients with severe CKD considering changes in glomerular filtration rate (GFR), plasma protein binding, and activity of either CYP2C8 and/or OATP1B in a stepwise manner. The PBPK analysis suggests that OATP1B activity could be decreased up to 60% in severe CKD, whereas changes to CYP2C8 are negligible. This improved understanding of CKD effect on clearance pathways could be important to inform the optimal use of nonrenally eliminated drugs in patients with CKD.

A Genetic Score Associates With Pioglitazone Response in Patients With Non-alcoholic Steatohepatitis

Pioglitazone is used effectively to treat non-alcoholic steatohepatitis (NASH), but there is marked variability in response. This study examined whether genetic variation contributes to pioglitazone response variability in patients with NASH. This genetic substudy includes 55 participants of a randomized controlled trial designed to determine the efficacy of long-term pioglitazone treatment in patients with NASH. The primary outcome of the clinical trial was defined as ≥2-point reduction in the non-alcoholic fatty liver disease activity score (NAS). In this substudy, single nucleotide polymorphisms (SNPs) in putative candidate genes were tested for association with primary and secondary outcomes. A genetic response score was constructed based on the sum of response alleles for selected genes. The genetic response score was significantly associated with achievement of the primary outcome (odds ratio 1.74; 95% CI 1.27–2.54; p = 0.0015). ADORA1 rs903361 associated with resolution of NASH (p = 0.0005) and change in the ballooning score among Caucasian and Hispanic patients (p = 0.0005). LPL rs10099160 was significantly associated with change in ALT (p = 0.0005). The CYP2C8^∗3 allele, which confers faster pioglitazone clearance in allele carriers, was associated with change in fibrosis score (p = 0.026). This study identified key genetic factors that explain some of the inter-individual variability in response to pioglitazone among patients with NASH.

Direct and quantitative evaluation of the major human CYP contribution (fmCYP) to drug clearance using the in vitro Silensomes™ model

1. We have applied the concept of using MBIs to produce CYP-Silensomes to quantify the contribution of the major CYPs to drug metabolism (fmCYP). 2. The target CYPs were extensively and selectivity inhibited by the selected MBIs, while non-target CYPs were inhibited by less than 20% of the homologous control activities. Only CYP2D6-Silensomes exhibited a CYP2B6 inhibition that could be easily and efficiently encountered by subtracting the fm_CYP2B6 measured using CYP2B6-Silensomes to adjust the fm_CYP2D6. 3. To validate the use of a panel of 6 CYP-Silensomes, we showed that the fmCYP values of mono- and multi-CYP metabolised drugs were well predicted, with 70% within ± 15% accuracy. Moreover, the correlation with observed fmCYP values was higher than that for rhCYPs, which were run in parallel using the same drugs (<45% within ±15% accuracy). Moreover, the choice of the RAF substrate in rhCYP predictions was shown to affect the accuracy of the fmCYP measurement. 4. These results support the use of CYP1A2-, CYP2B6-, CYP2C8-, CYP2C9-, CYP2D6 and CYP3A4-Silensomes to accurately predict fmCYP values during the in vitro enzyme phenotyping assays in early, as well as in development, phases of drug development.

Clopidogrel but Not Prasugrel Significantly Inhibits the CYP2C8-Mediated Metabolism of Montelukast in Humans

The oxidation of montelukast is mainly mediated by cytochrome P450 (CYP) 2C8, but other mechanisms may contribute to its disposition. In healthy volunteers, we investigated the effects of two widely used P2Y₁₂ inhibitors on montelukast pharmacokinetics. Clopidogrel (300 mg on day 1 and 75 mg on day 2) increased the area under the plasma concentration–time curve (AUC) of montelukast 2.0‐fold (90% confidence interval (CI) 1.72–2.28, P < 0.001) and decreased the M6:montelukast AUC_0‐7h ratio to 45% of control (90% CI 40–50%, P < 0.001). Prasugrel (60 mg on day 1 and 10 mg on day 2) had no clinically meaningful effect on montelukast pharmacokinetics. Our results imply that clopidogrel is at least a moderate inhibitor of CYP2C8, but prasugrel is not a clinically relevant CYP2C8 inhibitor. The different interaction potentials of clopidogrel and prasugrel are important to consider when antiplatelet therapy is planned for patients at risk for polypharmacy with CYP2C8 substrates.

Effects of functional CYP2C8,CYP2C9,CYP3A5,and ABCB1 genetic variants on the pharmacokinetics of insulin sensitizer pioglitazone in Chinese Han individuals

BACKGROUND AND OBJECTIVES

Pioglitazone is a thiazolidinedione antihyperglycemic drug with insulin-sensitizing properties. We investigated whether the variant genotypes of cytochrome P450 2C8 (CYP2C8), CYP2C9, CYP3A5 and transporter ABCB1 influence the pharmacokinetic phenotype of the substrate pioglitazone in Chinese individuals.

PARTICIPANTS AND METHODS

Single-nucleotide polymorphisms were determined by the PCR-restriction fragment length polymorphism method in 244 (CYP2C8 and CYP2C9) healthy Chinese Han individuals. After a single oral dose of 30 mg pioglitazone, the plasma concentrations of the parent drug and of two major active metabolites M-III and M-IV were measured using a validated LC-MS/MS in 21 (genotyping CYP3A5 and ABCB1) of these 244 volunteers.

RESULTS

The results confirmed that the unique frequencies of CYP2C8*2 (0.0%), CYP2C8*3 (0.0%), and CYP2C9*2 (0.0%) alleles were significantly different from those reported in Whites and Africans, and there were only 10 variant CYP2C9*1/*3 heterozygous (CYP2C9*3 carriers) among 244 Chinese individuals. These results were similar to those reported in Asian ethnic populations, including the Chinese. Unexpectedly, the pioglitazone AUC0-48 in CYP2C9*3 carriers was lower (50.8%), whereas the AUC0-48 ratios of metabolites M-III/pioglitazone and M-IV/pioglitazone increased to 134.3 and 155.8%, respectively, compared with the wild-type CYP2C9*1/*1 homozygous. Moreover, this phenomenon was not observed in individuals with genetic variants of CYP3A5*3 and ABCB1 (C1236T).

CONCLUSION

The present research suggests that the CYP2C8, CYP3A5, and ABCB1 genes play no significant role in the interindividual variation of pioglitazone pharmacokinetics, whereas CYP2C9*3 carriers are likely to accelerate the metabolism of this antidiabetic drug in the Chinese Han ethnic population.

Prediction of inter-individual variability on the pharmacokinetics of CYP2C8 substrates in human

Inter-individual variability in pharmacokinetics can lead to unexpected side effects and treatment failure, and is therefore an important factor in drug development. CYP2C8 is a major drug-metabolizing enzyme known to be involved in the metabolism of over 100 drugs. In this study, we predicted the inter-individual variability in AUC/Dose of CYP2C8 substrates in healthy volunteers using the Monte Carlo simulation. Inter-individual variability in the hepatic intrinsic clearance of CYP2C8 substrates (CL_int,h,2C8) was estimated from the inter-individual variability in pharmacokinetics of pioglitazone, which is a major CYP2C8 substrate. The coefficient of variation (CV) of CL_int,h,2C8 was estimated to be 40%. Using this value, the CVs of AUC/Dose of other major CYP2C8 substrates, rosiglitazone and amodiaquine, were predicted to validate the estimated CV of CL_int,h,2C8. As a result, the reported CVs of both substrates were within the 2.5-97.5 percentile range of the predicted CVs. Furthermore, the CVs of AUC/Dose of the CYP2C8 substrates loperamide and chloroquine, which are affected by renal clearance, were also successfully predicted. Combining this value with previously reported CVs of other CYPs, we were able to successfully predict the inter-individual variability in pharmacokinetics of various drugs in clinical.

Rosiglitazone Metabolism in Human Liver Microsomes Using a Substrate Depletion Method

Background

Elimination of rosiglitazone in humans is via hepatic metabolism. The existing studies suggest that CYP2C8 is the major enzyme responsible, with a minor contribution from CYP2C9; however, other studies suggest the involvement of additional cytochrome P450 enzymes and metabolic pathways. Thus a full picture of rosiglitazone metabolism is unclear.

Objective

This study aimed to improve the current understanding of potential drug–drug interactions and implications for therapy by evaluating the kinetics of rosiglitazone metabolism and examining the impact of specific inhibitors on its metabolism using the substrate depletion method.

Methods

In vitro oxidative metabolism of rosiglitazone in human liver microsomes obtained from five donors was determined over a 0.5–500 µM substrate range including the contribution of CYP2C8, CYP2C9, CYP3A4, CYP2E1, and CYP2D6.

Results

The maximum reaction velocity was 1.64 ± 0.98 nmol·mg⁻¹·min⁻¹. The CYP2C8 (69 ± 20%), CYP2C9 (42 ± 10%), CYP3A4 (52 ± 23%), and CEP2E1 (41 ± 13%) inhibitors all significantly inhibited rosiglitazone metabolism.

Conclusion

The results suggest that other cytochrome P450 enzymes, including CYP2C9, CYP3A4, and CEP2E1, in addition to CYP28, also play an important role in the metabolism of rosiglitazone. This example demonstrates that understanding the complete metabolism of a drug is important when evaluating the potential for drug–drug interactions and will assist to improve the current therapeutic strategies.

Quantitative Prediction of Drug-Drug Interactions Involving Inhibitory Metabolites in Drug Development: How Can Physiologically Based Pharmacokinetic Modeling Help?

This subteam under the Drug Metabolism Leadership Group (Innovation and Quality Consortium) investigated the quantitative role of circulating inhibitory metabolites in drug-drug interactions using physiologically based pharmacokinetic (PBPK) modeling. Three drugs with major circulating inhibitory metabolites (amiodarone, gemfibrozil, and sertraline) were systematically evaluated in addition to the literature review of recent examples. The application of PBPK modeling in drug interactions by inhibitory parent-metabolite pairs is described and guidance on strategic application is provided.

Projecting ADME Behavior and Drug-Drug Interactions in Early Discovery and Development: Application of the Extended Clearance Classification System

PURPOSE

To assess the utility of Extended Clearance Classification System (ECCS) in understanding absorption, distribution, metabolism, and elimination (ADME) attributes and enabling victim drug-drug interaction (DDI) predictions.

METHODS

A database of 368 drugs with relevant ADME parameters, main metabolizing enzymes, uptake transporters, efflux transporters, and highest change in exposure (%AUC) in presence of inhibitors was developed using published literature. Drugs were characterized according to ECCS using ionization, molecular weight and estimated permeability.

RESULTS

Analyses suggested that ECCS class 1A drugs are well absorbed and systemic clearance is determined by metabolism mediated by CYP2C, esterases, and UGTs. For class 1B drugs, oral absorption is high and the predominant clearance mechanism is hepatic uptake mediated by OATP transporters. High permeability neutral/basic drugs (class 2) showed high oral absorption, with metabolism mediated generally by CYP3A, CYP2D6 and UGTs as the predominant clearance mechanism. Class 3A/4 drugs showed moderate absorption with dominant renal clearance involving OAT/OCT2 transporters. Class 3B drugs showed low to moderate absorption with hepatic uptake (OATPs) and/or renal clearance as primary clearance mechanisms. The highest DDI risk is typically seen with class 2/1B/3B compounds manifested by inhibition of either CYP metabolism or active hepatic uptake. Class 2 showed a wider range in AUC change likely due to a variety of enzymes involved. DDI risk for class 3A/4 is small and associated with inhibition of renal transporters.

CONCLUSIONS

ECCS provides a framework to project ADME profiles and further enables prediction of victim DDI liabilities in drug discovery and development.

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.

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.

Clarification of the Mechanism of Clopidogrel-Mediated Drug-Drug Interaction in a Clinical Cassette Small-dose Study and Its Prediction Based on In Vitro Information

Clopidogrel is reported to be associated with cerivastatin-induced rhabdomyolysis, and clopidogrel and its metabolites are capable of inhibiting CYP2C8 and OATP 1B1 in vitro. The objective of the present study was to identify the mechanism of clopidogrel-mediated drug-drug interactions (DDIs) on the pharmacokinetics of OATP1B1 and/or CYP2C8 substrates in vivo. A clinical cassette small-dose study using OATPs, CYP2C8, and OATP1B1/CYP2C8 probe drugs (pitavastatin, pioglitazone, and repaglinide, respectively) with or without the coadministration of either 600 mg rifampicin (an inhibitor for OATPs), 200 mg trimethoprim (an inhibitor for CYP2C8), or 300 mg clopidogrel was performed, and the area under the concentration-time curve (AUC) ratios (AUCRs) for probe substrates were predicted using a static model. Clopidogrel increased the AUC of pioglitazone (2.0-fold) and repaglinide (3.1-fold) but did not significantly change the AUC of pitavastatin (1.1-fold). In addition, the AUC of pioglitazone M4, a CYP2C8-mediated metabolite of pioglitazone, was reduced to 70% of the control by coadministration of clopidogrel. The predicted AUCRs using the mechanism-based inhibition of CYP2C8 by clopidogrel acyl-β-glucuronide were similar to the observed AUCRs, and the predicted AUCR (1.1) of repaglinide using only the inhibition of OATP1B1 did not reach the observed AUCR (3.1). In conclusion, a single 300 mg of clopidogrel mainly inhibits CYP2C8-mediated metabolism by clopidogrel acyl-β-glucuronide, but its effect on the pharmacokinetics of OATP1B1 substrates is negligible. Clopidogrel is expected to have an effect not only on CYP2C8 substrates, but also dual CYP2C8/OATP1B1 substrates as seen in the case of repaglinide.

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.

Pharmacogenetics in type 2 diabetes: influence on response to oral hypoglycemic agents

Type 2 diabetes is one of the leading causes of morbidity and mortality, consuming a significant proportion of public health spending. Oral hypoglycemic agents (OHAs) are the frontline treatment approaches after lifestyle changes. However, huge interindividual variation in response to OHAs results in unnecessary treatment failure. In addition to nongenetic factors, genetic factors are thought to contribute to much of such variability, highlighting the importance of the potential of pharmacogenetics to improve therapeutic outcome. Despite the presence of conflicting results, significant progress has been made in an effort to identify the genetic markers associated with pharmacokinetics, pharmacodynamics, and ultimately therapeutic response and/or adverse outcomes to OHAs. As such, this article presents a comprehensive review of current knowledge on pharmacogenetics of OHAs and provides insights into knowledge gaps and future directions.

The Role of CYP2C8 and CYP2C9 Genotypes in Losartan-Dependent Inhibition of Paclitaxel Metabolism in Human Liver Microsomes

The aim of the present study was to further investigate a previously identified metabolic interaction between losartan and paclitaxel, which is one of the marker substrates of CYP2C8, by using human liver microsomes (HLMs) from donors with different CYP2C8 and CYP2C9 genotypes. Although CYP2C8 and CYP2C9 exhibit genetic linkage, previous studies have yet to determine whether losartan or its active metabolite, EXP-3174 which is specifically generated by CYP2C9, is responsible for CYP2C8 inhibition. Concentrations of 6α-hydroxypaclitaxel and EXP-3174 were measured by high-performance liquid chromatography after incubations with paclitaxel, losartan or EXP-3174 in HLMs from seven donors with different CYP2C8 and CYP2C9 genotypes. The half maximal inhibitory concentration (IC50 ) values were not fully dependent on CYP2C8 genotypes. Although the degree of inhibition was small, losartan significantly inhibited the production of 6α-hydroxypaclitaxel at a concentration of 1 μmol/L in only HL20 with the CYP2C8*3/*3 genotype. HLMs with either CYP2C9*2/*2 or CYP2C9*1/*3 exhibited a lower losartan intrinsic clearance (Vmax /Km ) than other HLMs including those with CYP2C9*1/*1 and CYP2C9*1/*2. Significant inhibition of 6α-hydroxypaclitaxel formation by EXP-3174 could only be found at levels that were 50 times higher (100 μmol/L) than the maximum concentration generated in the inhibition study using losartan. These results suggest that the metabolic interaction between losartan and paclitaxel is dependent on losartan itself rather than its metabolite and that the CYP2C8 inhibition by losartan is not affected by the CYP2C9 genotype. Further study is needed to define the effect of CYP2C8 genotypes on losartan-paclitaxel interaction.

Pharmacogenomics and pharmacogenetics of thiazolidinediones: role in diabetes and cardiovascular risk factors

The most important goal in the treatment of patients with diabetes is to prevent the risk of cardiovascular disease (CVD), the first cause of mortality in these subjects. Thiazolidinediones (TZDs), a class of antidiabetic drugs, act as insulin sensitizers increasing insulin-dependent glucose disposal and reducing hepatic glucose output. TZDs including pioglitazone, rosiglitazone and troglitazone, by activating PPAR-γ have shown pleiotropic effects in reducing vascular risk factors and atherosclerosis. However, troglitazone was removed from the market due to its hepatoxicity, and rosiglitazone and pioglitazone both have particular warnings due to being associated with heart diseases. Specific genetic variations in genes involved in the pathways regulated by TDZs have demonstrated to modify the variability in treatment with these drugs, especially in their side effects. Therefore, pharmacogenomics and pharmacogenetics are an important tool in further understand intersubject variability per se but also to assess the therapeutic potential of such variability in drug individualization and therapeutic optimization.

A stewardship intervention program for safe medication management and use of antidiabetic drugs

Background

Diabetes patients are complex due to considerations of polypharmacy, multimorbidities, medication adherence, dietary habits, health literacy, socioeconomic status, and cultural factors. Meanwhile, insulin and oral hypoglycemic agents are high-alert medications. Therefore it is necessary to require a multidisciplinary team’s integrated endeavors to enhance safe medication management and use of antidiabetic drugs.

Methods

A 5-year stewardship intervention program, including organizational measures and quality improvement activities in storage, prescription, dispensing, administration, and monitoring, was performed in the Second Affiliated Hospital of Zhejiang University, People’s Republic of China, a 3,200-bed hospital with 3.5 million outpatient visits annually.

Results

The Second Affiliated Hospital of Zhejiang University has obtained a 100% implementation rate of standard storage of antidiabetic drugs in the Pharmacy and wards since August 2012. A zero occurrence of dispensing errors related to highly “look-alike” and “sound-alike” NovoMix 30^® (biphasic insulin aspart) and NovoRapid^® (insulin aspart) has been achieved since October 2011. Insulin injection accuracy among ward nurses significantly increased from 82% (first quarter 2011) to 96% (fourth quarter 2011) (P<0.05). The number of medication administration errors related to insulin continuously decreased from 20 (2011) to six (2014). The occurrence rate of hypoglycemia in non–endocrinology ward diabetes inpatients during 2011–2013 was significantly less than that in 2010 (5.03%–5.53% versus 8.27%) (P<0.01). Percentage of correct management of hypoglycemia by nurses increased from 41.5% (April 2014) to 67.2% (August 2014) (P<0.01). The percentage of outpatient diabetes patients receiving standard insulin injection education increased from 80% (April 2012) to 95.2% (October 2012) (P<0.05). Insulin injection techniques among diabetes outpatients who started to receive insulin were better than indicated in data from two questionnaire surveys in the literature, including the percentage checking injection sites prior to injection (85.6%), priming before injection (98.1%), rotation of injecting sites (98.1%), remixing before use (94.5%), keeping the pen needle under the skin for >10 seconds (99.4%), and using the pen needle only once (88.7%). On-site inspection indicated of great improvement in the percentage of drug-related problems in the antidiabetes regimen between the first and second quarter of 2014 (1.08% versus 0.28%) (P<0.05).

Conclusion

Quality improvements in safe medication management and use of antidiabetic drugs can be achieved by multidisciplinary collaboration among pharmacists, nurses, physicians, and information engineers.

Quantitative Rationalization of Gemfibrozil Drug Interactions: Consideration of Transporters-Enzyme Interplay and the Role of Circulating Metabolite Gemfibrozil 1-O-β-Glucuronide

Gemfibrozil has been suggested as a sensitive cytochrome P450 2C8 (CYP2C8) inhibitor for clinical investigation by the U.S. Food and Drug Administration and the European Medicines Agency. However, gemfibrozil drug-drug interactions (DDIs) are complex; its major circulating metabolite, gemfibrozil 1-O-β-glucuronide (Gem-Glu), exhibits time-dependent inhibition of CYP2C8, and both parent and metabolite also behave as moderate inhibitors of organic anion transporting polypeptide 1B1 (OATP1B1) in vitro. Additionally, parent and metabolite also inhibit renal transport mediated by OAT3. Here, in vitro inhibition data for gemfibrozil and Gem-Glu were used to assess their impact on the pharmacokinetics of several victim drugs (including rosiglitazone, pioglitazone, cerivastatin, and repaglinide) by employing both static mechanistic and dynamic physiologically based pharmacokinetic (PBPK) models. Of the 48 cases evaluated using the static models, about 75% and 98% of the DDIs were predicted within 1.5- and 2-fold of the observed values, respectively, when incorporating the interaction potential of both gemfibrozil and its 1-O-β-glucuronide. Moreover, the PBPK model was able to recover the plasma profiles of rosiglitazone, pioglitazone, cerivastatin, and repaglinide under control and gemfibrozil treatment conditions. Analyses suggest that Gem-Glu is the major contributor to the DDIs, and its exposure needed to bring about complete inactivation of CYP2C8 is only a fraction of that achieved in the clinic after a therapeutic gemfibrozil dose. Overall, the complex interactions of gemfibrozil can be quantitatively rationalized, and the learnings from this analysis can be applied in support of future predictions of gemfibrozil DDIs.

Pharmacokinetics and clinical evaluation of the alogliptin plus pioglitazone combination for type 2 diabetes

INTRODUCTION

Type 2 diabetes is a complex disease with multiple defects, which generally requires a combination of several pharmacological approaches to reach glucose control targets. A unique fixed-dose combination combines a thiazolidinedione (pioglitazone) and a dipeptidyl peptidase-4 inhibitor (alogliptin).

AREA COVERED

An extensive literature search was performed to analyze the pharmacokinetics of pioglitazone and alogliptin when used separately and in combination as well as to summarize clinical and toxicological considerations about the combined therapy.

EXPERT OPINION

Pioglitazone, a potent insulin sensitizer, and alogliptin, an incretin-based agent that potentiates post-meal insulin secretion and reduces glucagon secretion, have complementary mechanisms of action. The clinical efficacy of a combined therapy is superior to any single therapy in patients treated with diet or with metformin (with or without sulphonylurea). These two drugs can be administered once daily, with or without a meal. No clinically relevant pharmacokinetic interactions between the two agents have been described and the fixed-dose combination has shown bioequivalence with alogliptin and pioglitazone given separately. Combining alogliptin with pioglitazone does not alter the safety profile of each compound. Weight gain observed with pioglitazone may be limited with the addition of alogliptin. The concern of an increased risk of heart failure remains to be better investigated.

Application of routine electronic health record databases for pharmacogenetic research

Inter-individual variability in drug responses is a common problem in pharmacotherapy. Several factors (non-genetic and genetic) influence drug responses in patients. When aiming to obtain an optimal benefit-risk ratio of medicines and with the emergence of genotyping technology, pharmacogenetic studies are important for providing recommendations on drug treatments. Advances in electronic healthcare information systems can contribute to increasing the quality and efficiency of such studies. This review describes the definition of pharmacogenetics, gene selection and study design for pharmacogenetic research. It also summarizes the potential of linking pharmacoepidemiology and pharmacogenetics (along with its strengths and limitations) and provides examples of pharmacogenetic studies utilizing electronic health record databases.

Impact of CYP2C9 polymorphisms on the vulnerability to pharmacokinetic drug-drug interactions during acenocoumarol treatment

AIM

The objective of this study was to investigate the impact of CYP2C9 polymorphisms and drug-drug interactions on the risk of overanticoagulation in patients treated with acenocoumarol, a vitamin K antagonist.

MATERIALS & METHODS

A prospective observational study was performed on patients starting acenocoumarol (n = 115). CYP2C9 genotypes were assessed. Data on International Normalized Ratio, comedications and doses of acenocoumarol were collected during the first 35 days of therapy. Overanticoagulation was defined as the occurrence of at least one International Normalized Ratio ≥4.

RESULTS

The presence of a CYP2C9 inhibitor or a CYP2C9 polymorphisms statistically increased the risk of overanticoagulation (hazard ratio [HR]: 2.8, p < 0.001 and HR: 1.7, p = 0.04, respectively). The presence of CYP2C9 polymorphisms almost tripled the risk of overanticoagulation (HR: 2.91, p = 0.01) in the presence of a clinically significant drug-drug interaction.

CONCLUSION

These findings support the fact that CYP2C9 genotyping could be useful to identify patients requiring closer monitoring, especially when a drug-drug interaction is expected.

Current clinical evidence on pioglitazone pharmacogenomics

Pioglitazone is the most widely used thiazolidinedione and acts as an insulin-sensitizer through activation of the Peroxisome Proliferator-Activated Receptor-γ (PPARγ). Pioglitazone is approved for use in the management of type 2 diabetes mellitus (T2DM), but its use in other therapeutic areas is increasing due to pleiotropic effects. In this hypothesis article, the current clinical evidence on pioglitazone pharmacogenomics is summarized and related to variability in pioglitazone response. How genetic variation in the human genome affects the pharmacokinetics and pharmacodynamics of pioglitazone was examined. For pharmacodynamic effects, hypoglycemic and anti-atherosclerotic effects, risks of fracture or edema, and the increase in body mass index in response to pioglitazone based on genotype were examined. The genes CYP2C8 and PPARG are the most extensively studied to date and selected polymorphisms contribute to respective variability in pioglitazone pharmacokinetics and pharmacodynamics. We hypothesized that genetic variation in pioglitazone pathway genes contributes meaningfully to the clinically observed variability in drug response. To test the hypothesis that genetic variation in PPARG associates with variability in pioglitazone response, we conducted a meta-analysis to synthesize the currently available data on the PPARG p.Pro12Ala polymorphism. The results showed that PPARG 12Ala carriers had a more favorable change in fasting blood glucose from baseline as compared to patients with the wild-type Pro12Pro genotype (p = 0.018). Unfortunately, findings for many other genes lack replication in independent cohorts to confirm association; further studies are needed. Also, the biological functionality of these polymorphisms is unknown. Based on current evidence, we propose that pharmacogenomics may provide an important tool to individualize pioglitazone therapy and better optimize therapy in patients with T2DM or other conditions for which pioglitazone is being used.

Influence of CYP2C8*2 on the pharmacokinetics of pioglitazone in healthy African-American volunteers

STUDY OBJECTIVES

To determine the influence of the Cytochrome P450 (CYP) 2C8*2 polymorphism on pioglitazone pharmacokinetics in healthy African-American volunteers.

DESIGN

Prospective, open-label, single-dose pharmacokinetic study.

SETTING

University of Colorado Hospital Clinical and Translational Research Center.

PARTICIPANTS

Healthy African-American volunteers between 21 and 60 years of age were enrolled in the study based on CYP2C8 genotype: CYP2C8*1/*1 (9 participants), CYP2C8*1/*2 (7 participants), and CYP2C8*2/*2 (1 participant).

INTERVENTION

Participants received a single 15-mg dose of pioglitazone in the fasted state, followed by a 48-hour pharmacokinetic study.

MEASUREMENTS AND MAIN RESULTS

Plasma concentrations of pioglitazone and its M-III (keto) and M-IV (hydroxy) metabolites were compared between participants with the CYP2C8*1/*1 genotype and CYP2C8*2 carriers. Pioglitazone area under the plasma concentration-time curve (AUC)0-∞ and half-life (t1/2 ) did not differ significantly between CYP2C8*1/*1 and CYP2C8*2 carriers (AUC0-∞ 7331 ± 2846 vs 10431 ± 5090 ng*h/ml, p=0.15, t1/2 7.4 ± 2.7 vs 10.5 ± 4.0 h, p=0.07). M-III and M-IV AUC0-48 also did not differ significantly between genotype groups. However, the M-III:pioglitazone AUC0-48 ratio was significantly lower in CYP2C8*2 carriers than CYP2C8*1 homozygotes (0.70 ± 0.15 vs 1.2 ± 0.37, p=0.006). Similarly, CYP2C8*2 carriers had a significantly lower M-III:M-IV AUC0-48 ratio than participants with the CYP2C8*1/*1 genotype (0.82 ± 0.26 vs 1.22 ± 0.26, p=0.006).

CONCLUSION

These data suggest that CYP2C8*2 influences pioglitazone pharmacokinetics in vivo, particularly the AUC0-48 ratio of M-III:parent drug, and the AUC0-48 ratio of M-III:M-IV. Larger studies are needed to further investigate the impact of CYP2C8*2 on the pharmacokinetics of CYP2C8 substrates in individuals of African descent.