So Many Studies, Too Few Subjects: Establishing Functional Relevance of Genetic Polymorphisms on Pharmacokinetics

Glossary and tutorial of xenobiotic metabolism terms used during small molecule drug discovery and development (IUPAC Technical Report)

This project originated more than 15 years ago with the intent to produce a glossary of drug metabolism terms having definitions especially applicable for use by practicing medicinal chemists. A first-draft version underwent extensive beta-testing that, fortuitously, engaged international audiences in a wide range of disciplines involved in drug discovery and development. It became clear that the inclusion of information to enhance discussions among this mix of participants would be even more valuable. The present version retains a chemical structure theme while expanding tutorial comments that aim to bridge the various perspectives that may arise during interdisciplinary communications about a given term. This glossary is intended to be educational for early stage researchers, as well as useful for investigators at various levels who participate on today’s highly multidisciplinary, collaborative small molecule drug discovery teams.

Prediction of in vivo clearance and associated variability of CYP2C19 substrates by genotypes in populations utilizing a pharmacogenetics-based mechanistic model

It is important to examine the cytochrome P450 2C19 (CYP2C19) genetic contribution to drug disposition and responses of CYP2C19 substrates during drug development. Design of such clinical trials requires projection of genotype-dependent in vivo clearance and associated variabilities of the investigational drug, which is not generally available during early stages of drug development, but is essential for CYP2C19 substrates with multiple clearance pathways. This study evaluated the utility of pharmacogenetics-based mechanistic modeling in predicting such parameters. Hepatic CYP2C19 activity and variability within genotypes were derived from in vitro S-mephenytoin metabolic activity in genotyped human liver microsomes (N = 128). These data were then used in mechanistic models to predict genotype-dependent disposition of CYP2C19 substrates (i.e., S-mephenytoin, citalopram, pantoprazole, and voriconazole) by incorporating in vivo clearance or pharmacokinetics of wild-type subjects and parameters of other clearance pathways. Relative to the wild-type, the CYP2C19 abundance (coefficient of variation percentage) in CYP2C19*17/*17, *1/*17, *1/*1, *17/null, *1/null, and null/null microsomes was estimated as 1.85 (117%), 1.79 (155%), 1.00 (138%), 0.83 (80%), 0.38 (130%), and 0 (0%), respectively. The subsequent modeling and simulations predicted, within 2-fold of the observed, the means and variabilities of urinary S/R-mephenytoin ratio (36 of 37 genetic groups), the oral clearance of citalopram (9 of 9 genetic groups) and pantoprazole (6 of 6 genetic groups), and voriconazole oral clearance (4 of 4 genetic groups). Thus, relative CYP2C19 genotype-dependent hepatic activity and variability were quantified in vitro and used in a mechanistic model to predict pharmacokinetic variability, thus allowing the design of pharmacogenetics and drug-drug interaction trials for CYP2C19 substrates.

Reduced physiologically-based pharmacokinetic model of repaglinide: impact of OATP1B1 and CYP2C8 genotype and source of in vitro data on the prediction of drug-drug interaction risk

PURPOSE

To investigate the effect of OATP1B1 genotype as a covariate on repaglinide pharmacokinetics and drug-drug interaction (DDIs) risk using a reduced physiologically-based pharmacokinetic (PBPK) model.

METHODS

Twenty nine mean plasma concentration-time profiles for SLCO1B1 c.521T>C were used to estimate hepatic uptake clearance (CLuptake) in different genotype groups applying a population approach in NONMEM v.7.2.

RESULTS

Estimated repaglinide CLuptake corresponded to 217 and 113 μL/min/10(6) cells for SLCO1B1 c.521TT/TC and CC, respectively. A significant effect of OATP1B1 genotype was seen on CLuptake (48% reduction for CC relative to wild type). Sensitivity analysis highlighted the impact of CLmet and CLdiff uncertainty on the CLuptake optimization using plasma data. Propagation of this uncertainty had a marginal effect on the prediction of repaglinide OATP1B1-mediated DDI with cyclosporine; however, sensitivity of the predicted magnitude of repaglinide metabolic DDI was high. In addition, the reduced PBPK model was used to assess the effect of both CYP2C8*3 and SLCO1B1 c.521T>C on repaglinide exposure by simulations; power calculations were performed to guide prospective DDI and pharmacogenetic studies.

CONCLUSIONS

The application of reduced PBPK model for parameter optimization and limitations of this process associated with the use of plasma rather than tissue profiles are illustrated.

Common clinical conditions - age, low BMI, ritonavir use, mild renal impairment - affect tenofovir pharmacokinetics in a large cohort of HIV-infected women

OBJECTIVE

Tenofovir is used commonly in HIV treatment and prevention settings, but factors that correlate with tenofovir exposure in real-world settings are unknown.

DESIGN

Intensive pharmacokinetic studies of tenofovir in a large, diverse cohort of HIV-infected women over 24 h at steady state were performed and factors that influenced exposure [assessed by areas under the concentration-time curves (AUCs)] identified.

METHODS

HIV-infected women (n = 101) on tenofovir-based therapy underwent intensive 24-h pharmacokinetic sampling. Data on race/ethnicity, age, exogenous steroid use, menstrual cycle phase, concomitant medications, recreational drugs and/or tobacco, hepatic and renal function, weight, and BMI were collected. Multivariable models using forward stepwise selection identified factors associated with effects on AUC. Glomerular filtration rates (GFRs) prior to starting tenofovir were estimated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation using both creatinine and cystatin-C measures.

RESULTS

The median (range) of tenofovir AUCs was 3350 (1031-13 911) ng × h/ml. Higher AUCs were associated with concomitant ritonavir use (1.33-fold increase, P = 0.002), increasing age (1.21-fold increase per decade, P = 0.0007), and decreasing BMI (1.04-fold increase per 10% decrease in BMI). When GFR was calculated using cystatin-C measures, mild renal insufficiency prior to tenofovir initiation was associated with higher subsequent exposure (1.35-fold increase when pre-tenofovir GFR <70 ml/min, P = 0.0075).

CONCLUSION

Concomitant ritonavir use, increasing age, decreasing BMI, and lower GFR prior to tenofovir initiation as estimated by cystatin C were all associated with elevated tenofovir exposure in a diverse cohort of HIV-infected women. Clinicians treating HIV-infected women should be aware of common clinical conditions that affect tenofovir exposure when prescribing this medication.

Incorporating In Vitro Information on Drug Metabolism Into Clinical Trial Simulations to Assess the Effect of CYP2D6 Polymorphism on Pharmacokinetics and Pharmacodynamics: Dextromethorphan as a Model Application

In vitro-in vivo extrapolation of clearance, embedded in a clinical trial simulation, was used to investigate differences in the pharmacokinetics and pharmacodynamics of dextromethorphan between CYP2D6 poor and extensive metabolizer phenotypes. Information on the genetic variation of CYP2D6, as well as the in vitro metabolism and pharmacodynamics of dextromethorphan and its active metabolite dextrorphan, was integrated to assess the power of studies to detect differences between phenotypes. Whereas 6 subjects of each phenotype were adequate to achieve 80% power in showing pharmacokinetic differences, the power required to detect a difference in antitussive response was less than 80% with 500 subjects in each study arm. Combining in vitro-in vivo extrapolation with a clinical trial simulation is useful in assessing different elements of study design and could be used a priori to avoid inconclusive pharmacogenetic studies.

Chapter 11: challenges in and principles for conducting systematic reviews of genetic tests used as predictive indicators

In this paper, we discuss common challenges in and principles for conducting systematic reviews of genetic tests. The types of genetic tests discussed are those used to 1). determine risk or susceptibility in asymptomatic individuals; 2). reveal prognostic information to guide clinical management in those with a condition; or 3). predict response to treatments or environmental factors. This paper is not intended to provide comprehensive guidance on evaluating all genetic tests. Rather, it focuses on issues that have been of particular concern to analysts and stakeholders and on areas that are of particular relevance for the evaluation of studies of genetic tests. The key points include: The general principles that apply in evaluating genetic tests are similar to those for other prognostic or predictive tests, but there are differences in how the principles need to be applied or the degree to which certain issues are relevant. A clear definition of the clinical scenario and an analytic framework is important when evaluating any test, including genetic tests. Organizing frameworks and analytic frameworks are useful constructs for approaching the evaluation of genetic tests. In constructing an analytic framework for evaluating a genetic test, analysts should consider preanalytic, analytic, and postanalytic factors; such factors are useful when assessing analytic validity. Predictive genetic tests are generally characterized by a delayed time between testing and clinically important events. Finding published information on the analytic validity of some genetic tests may be difficult. Web sites (FDA or diagnostic companies) and gray literature may be important sources. In situations where clinical factors associated with risk are well characterized, comparative effectiveness reviews should assess the added value of using genetic testing along with known factors compared with using the known factors alone. For genome-wide association studies, reviewers should determine whether the association has been validated in multiple studies to minimize both potential confounding and publication bias. In addition, reviewers should note whether appropriate adjustments for multiple comparisons were used.

Application of a systems approach to the bottom-up assessment of pharmacokinetics in obese patients: expected variations in clearance

BACKGROUND AND OBJECTIVES

The maintenance dose of a drug is dependent on drug clearance, and thus any biochemical and physiological changes in obesity that affect parameters such as cardiac output, renal function, expression of drug-metabolizing enzymes and protein binding may result in altered clearance compared with that observed in normal-weight subjects (corrected or uncorrected for body weight). Because of the increasing worldwide incidence of obesity, there is a need for more information regarding the optimal dosing of drug therapy to be made available to prescribers. This is usually provided via clinical studies in obese people; however, such studies are not available for all drugs that might be used in obese subjects. Incorporation of the relevant physiological and biochemical changes into predictive bottom-up pharmacokinetic models in order to optimize dosage regimens may offer a logical way forward for the cases where no clinical data exist. The aims of the current report are to apply such a 'systems approach' to identify the likelihood of observing variations in the clearance of drugs in obesity and morbid obesity for a set of compounds for which clinical data, as well as the necessary in vitro information, are available, and to provide a framework for assessing other drugs in the future.

METHODS

The population-specific changes in demographic, physiological and biochemical parameters that are known to be relevant to obese and morbidly obese subjects were collated and incorporated into two separate population libraries. These libraries, together with mechanistic in vitro-in vivo extrapolations (IVIVE) within the Simcyp Population-based Simulator™, were used to predict the clearance of oral alprazolam, oral caffeine, oral chlorzoxazone, oral ciclosporin, intravenous and oral midazolam, intravenous phenytoin, oral theophylline and oral triazolam. The design of the simulated studies was matched as closely as possible with that of the clinical studies. Outcome was measured by the predicted ratio of the clearance of the drug in obese and lean subjects ± its 90% confidence interval, compared with observed values. The overall statistical measures of the performance of the model to detect differences in compound clearance between obese and lean populations were investigated by measuring sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). A power calculation was carried out to investigate the impact of the sample size on the overall outcome of clinical studies.

RESULTS

The model was successful in predicting clearance in obese subjects, with the degree to which simulations could mimic the outcome of in vivo studies being greater than 60% for six of the eight drugs. A clear difference in the clearance of chlorzoxazone was correctly picked up via simulation. The overall statistical measures of the performance of the Simcyp Simulator were 100% sensitivity, 66% specificity, 60% PPV and 100% NPV. Studies designed on the basis of the ratio of the absolute values required substantial numbers of participants in order to detect a significant difference, except for phenytoin and chlorzoxazone, where the ratios of the weight-normalized clearances generally showed statistically significant differences with a smaller number of subjects.

CONCLUSION

Extension of a mechanistic predictive pharmacokinetic model to accommodate physiological and biochemical changes associated with obesity and morbid obesity allowed prediction of changes in drug clearance on the basis of in vitro data, with reasonable accuracy across a range of compounds that are metabolized by different enzymes. Prediction of the effects of obesity on drug clearance, normalized by various body size scalars, is of potential value in the design of clinical studies during drug development and in the introduction of dosage adjustments that are likely to be needed in clinical practice.

Meta-analysis of contribution of genetic polymorphisms in drug-metabolizing enzymes or transporters to axitinib pharmacokinetics

PURPOSE

Axitinib, an orally administered inhibitor of vascular endothelial growth factor 1, 2 and 3, is primarily metabolized by cytochrome P450 (CYP) 3A4/5 but is also a substrate for CYP1A2, CYP2C19, UDP-glucuronosyltransferase (UGT)1A1 and the drug transporters P-glycoprotein (encoded by the ABCB1 gene) and OATP1B1 (encoded by SLC01B1). The potential contribution of polymorphisms in genes encoding these enzymes and transporters to axitinib pharmacokinetic variability was assessed.

METHODS

A fixed effects meta-analysis was performed using data pooled from 11 healthy volunteer clinical pharmacology trials to investigate the potential association between axitinib exposure and major polymorphisms in these genes following a 5-mg dose of axitinib.

RESULTS

Up to 15 variant alleles were evaluated and up to 315 healthy volunteers per polymorphism were assayed. None of the polymorphisms analysed was a statistically significant predictor of axitinib pharmacokinetic variability. Amongst genotypes and inferred phenotypes, CYP2C19 genotype and the ABCB1 (G2677T/A) polymorphism were the closest to statistical significance in influencing axitinib pharmacokinetic variability after multiple-testing adjustment. However, no enzyme or transporter genotype/inferred phenotype contributed >5% to the overall pharmacokinetic variability of axitinib.

CONCLUSIONS

No statistically significant associations between the specific polymorphisms analysed and axitinib plasma exposure were observed, suggesting that genotype- or inferred phenotype-based adjustment of axitinib dose in individual subjects is not warranted.

A quantitative framework and strategies for management and evaluation of metabolic drug-drug interactions in oncology drug development: new molecular entities as object drugs

This article outlines general strategies for the management and evaluation of pharmacokinetic drug-drug interactions (DDIs) resulting from perturbation of clearance of investigational anticancer drug candidates by concomitantly administered agents in a drug development setting, with a focus on drug candidates that cannot be evaluated in first-in-human studies in healthy subjects. A risk level classification is proposed, based on quantitative integration of knowledge derived from preclinical drug-metabolism studies evaluating the projected percentage contribution [f(i)(%)] of individual molecular determinants (e.g. cytochrome P450 isoenzymes) to the overall human clearance of the investigational agent. The following classification is proposed with respect to susceptibility to DDIs with metabolic inhibitors: a projected maximum DDI expected to result in a ≤1.33-fold increase in exposure, representing a low level of risk; a projected maximum DDI expected to result in a >1.33-fold but <2-fold increase in exposure, representing a moderate level of risk; and a projected maximum DDI expected to result in a ≥2-fold increase in exposure, representing a potentially high level of risk. For DDIs with metabolic inducers, the following operational classification is proposed, based on the sum of the percentage contributions of enzymes that are inducible via a common mechanism to the overall clearance of the investigational drug: <<25%, representing a low level of risk; <50%, representing a moderate level of risk; and ≥50%, representing a potentially high level of risk. To ensure patient safety and to minimize bias in determination of the recommended phase II dose (RP2D), it is recommended that strong and moderate inhibitors and inducers of the major contributing enzyme are excluded in phase I dose-escalation studies of high-risk compounds, whereas exclusion of strong inhibitors and inducers of the contributing enzyme(s) is recommended as being sufficient for moderate-risk compounds. For drugs that will be investigated in diseases such as glioblastoma, where there may be relatively frequent use of enzyme-inducing antiepileptic agents (EIAEDs), a separate dose-escalation study in this subpopulation is recommended to define the RP2D. For compounds in the high-risk category, if genetic deficiencies in the activity of the major drug-metabolizing enzyme are known, it is recommended that poor metabolizers be studied separately to define the RP2D for this subpopulation. Whereas concomitant medication exclusion criteria that are utilized in the phase I dose-escalation studies will probably also need to be maintained for high-risk compounds in phase II studies unless the results of a clinical DDI study indicate the absence of a clinically relevant interaction, these exclusion criteria can potentially be relaxed beyond phase I for moderate-risk compounds, if supported by the nature of clinical toxicities and the understanding of the therapeutic index in phase I. Adequately designed clinical DDI studies will not only inform potential relaxation of concomitant medication exclusion criteria in later-phase studies but, importantly, will also inform the development of pharmacokinetically derived dose-modification guidelines for use in clinical practice when coupled with adequate safety monitoring, as illustrated in the prescribing guidance for many recently approved oncology therapeutics.

Pharmacogenetic influences on mycophenolate therapy

Mycophenolic acid (MPA) is a cornerstone immunosuppressant therapy in solid organ transplantation. MPA is metabolized by uridine diphosphate glucuronosyltransferase to inactive 7-O-MPA-glucuronide (MPAG). At least three minor metabolites are also formed, including a pharmacologically active acyl-glucuronide. MPA and MPAG are subject to enterohepatic recirculation. Biliary excretion of MPA/MPAG involves several transporters, including organic anion transporting polypeptides and multidrug resistant protein-2 (MRP-2). MPA metabolites are also excreted via the kidney, at least in part by MRP-2. MPA exerts its immunosuppressive effect through the inhibition of inosine-5-monophosphate dehydrogenase. Several SNPs have been identified in the genes encoding for uridine diphosphate glucuronosyltransferase, organic anion transporting polypeptides, MRP-2 and inosine-5-monophosphate dehydrogenase. This article provides an extensive overview of the known effects of these SNPs on the pharmacokinetics and pharmacodynamics of MPA.

Nonnucleoside reverse transcriptase inhibitor pharmacokinetics in a large unselected cohort of HIV-infected women

BACKGROUND

Small intensive pharmacokinetic (PK) studies of medications in early-phase trials cannot identify the range of factors that influence drug exposure in heterogenous populations. We performed PK studies in large numbers of HIV-infected women on nonnucleoside reverse transcriptase inhibitors (NNRTIs) under conditions of actual use to assess patient characteristics that influence exposure and evaluated the relationship between exposure and response.

METHODS

Two hundred twenty-five women on NNRTI-based antiretroviral regimens from the Women's Interagency HIV Study were enrolled into 12-hour or 24-hour PK studies. Extensive demographic, laboratory, and medication covariate data were collected before and during the visit to be used in multivariate models. Total NNRTI drug exposure was estimated by area under the concentration-time curves.

RESULTS

Hepatic inflammation and renal insufficiency were independently associated with increased nevirapine exposure in multivariate analysis: crack cocaine, high fat diets, and amenorrhea were associated with decreased levels (n = 106). Higher efavirenz exposure was seen with increased transaminase, albumin levels, and orange juice consumption; tenofovir use, increased weight, being African American, and amenorrhea were associated with decreased exposure (n = 119). With every 10-fold increase in nevirapine or efavirenz exposure, participants were 3.3 and 3.6 times likely to exhibit virologic suppression, respectively. Patients with higher drug exposure were also more likely to report side effects on therapy.

CONCLUSIONS

Our study identifies and quantitates previously unrecognized factors modifying NNRTI exposure in the "real-world" setting. Comprehensive PK studies in representative populations are feasible and may ultimately lead to dose optimization strategies in patients at risk for failure or adverse events.

Pharmacokinetics/genotype associations for major cytochrome P450 enzymes in native and first- and third-generation Japanese populations: comparison with Korean, Chinese, and Caucasian populations

Application of foreign clinical data across geographic regions can accelerate drug development. Drug disposition can be variable, and identification of factors influencing responsible pharmacokinetic/pharmacogenomic approaches could facilitate the universal application of foreign data and reduce the total amount of phase III clinical trials evaluating risks in different populations. Our objective was to establish and compare genotype (major cytochrome P450 (CYP) enzymes)/phenotype associations for Japanese (native and first- and third-generation Japanese living abroad), Caucasian, Chinese, and Korean populations using a standard drug panel. The mean metabolic ratios (MRs) for the four ethnic groups were similar except for a lower activity of CYP2D6 in Caucasians and CYP2C19 in Asians. Genotype, not ethnicity, impacted the MR for CYP2C9, CYP2C19, and CYP2D6; neither affected CYP1A2, CYP2E1, and CYP3A4/5 activities. We conclude that equivalent plasma drug concentrations and metabolic profiles can be expected for native Japanese, first- and third-generation Japanese, Koreans, and Chinese for compounds handled through these six CYP enzymes.

The role of pharmacogenetics in the metabolism of antiepileptic drugs: pharmacokinetic and therapeutic implications

Several different factors, including pharmacogenetics, contribute to interindividual variability in drug response. Like most other agents, many antiepileptic drugs (AEDs) are metabolised by a variety of enzymatic reactions, and the cytochrome P450 (CYP) superfamily has attracted considerable attention. Some of those CYPs exist in the form of genetic (allelic) variants, which may also affect the plasma concentrations or drug exposure (area under the plasma concentration-time curve [AUC]) of AEDs. With regard to the metabolism of AEDs, the polymorphic CYP2C9 and CYP2C19 are of interest. This review summarises the evidence as to whether such polymorphisms affect the clinical action of AEDs. In the case of mephenytoin, defects in its metabolism may be attributable to >10 mutated alleles (designated as *2, *3 and others) of the gene expressing CYP2C19. Consequently, poor metabolisers (PMs) and extensive metabolisers (EMs) could be differentiated, whose frequencies vary among ethnic populations. CYP2C19 contributes to the metabolism of diazepam and phenytoin, the latter drug also representing a substrate of CYP2C9, with its predominant variants being defined as *2 and *3. For both AEDs, there is maximally a 2-fold difference in the hepatic elimination rate (e.g. clearance) or the AUC between the extremes of EMs and PMs which, in the case of phenytoin (an AED with a narrow 'therapeutic window'), would suggest a dosage reduction only for patients who are carriers of mutated alleles of both CYP2C19 and CYP2C9, a subgroup that is very rare among Caucasians (about 1% of the population) but more frequent in Asians (about 10%). The minor contribution of CYP2C19 to the metabolism of phenobarbital (phenobarbitone) can be overlooked. In rare cases, valproic acid can be metabolised to the reactive (hepatotoxic) metabolite, 4-ene-valproic acid. It is not yet clear whether genetic variants of the involved enzyme (CYP2C9) are responsible for this problem. Likewise, the active metabolite of carbamazepine, carbamazepine-10,11-epoxide, is transformed by the microsomal epoxide hydrolase, an enzyme that is also highly polymorphic, but the pharmacokinetic and clinical consequences still need to be evaluated. Pharmacogenetic investigations have increased our general knowledge of drug disposition and action. As for old and especially new AEDs the pharmacogenetic influence on their metabolism is not very striking, it is not surprising that there are no treatment guidelines taking pharmacogenetic data into account. Therefore, the traditional and validated therapeutic drug monitoring approach, representing a direct 'phenotype' assessment, still remains the method of choice when an individualised dosing regimen is anticipated. Nevertheless, pharmacogenetics and pharmacogenomics can offer some novel contributions when attempts are made to maximise drug efficacy and enhance drug safety.

Limited influence of UGT1A1*28 and no effect of UGT2B7*2 polymorphisms on UGT1A1 or UGT2B7 activities and protein expression in human liver microsomes

AIMS

UGT1A1 and UGT2B7 are enzymes that commonly contribute to drug glucuronidation. Since genetic factors have been suggested to contribute to variability in activities and expression levels of these enzymes, a quantitative assessment of the influence of the major genotypes (UGT1A1*28 or UGT2B7*2) on enzyme activities was conducted.

METHODS

Using a bank of microsomal samples from 59 human livers, the effect of UGT1A1*28 or UGT2B7*2 polymorphisms were investigated on rates of estradiol 3-glucuronidation (a marker of UGT1A1 enzyme activity) or zidovudine glucuronidation (a marker of UGT2B7 enzyme activity) and levels of immunoreactive protein for each enzyme. Glucuronidation rates for both enzymes were measured at K(m)/S(50) and 10 times K(m)/S(50) concentrations.

RESULTS

UGT1A1 and UGT2B7 enzyme activities varied up to 16-fold and sixfold, respectively. Rates at K(m)/S(50) concentration closely correlated with rates at 10 times K(m)/S(50) concentration for both enzymes (but not at 1/10th K(m) for UGT2B7). Enzyme activities correlated with relative levels of immunoreactive protein for UGT1A1 and UGT2B7. Furthermore, rates of zidovudine glucuronidation correlated well with rates of glucuronidation of the UGT2B7 substrate gemcabene, but did not correlate with UGT1A1 enzyme activities. For the UGT1A1*28 polymorphism, consistent with levels of UGT1A1 immunoreactive protein, mean UGT1A1 activity was 2.5- and 3.2-fold lower for TA(6)/TA(7) (P < 0.05) and TA(7)/TA(7) (P < 0.001) genotypes in comparison with the TA(6)/TA(6) genotype.

CONCLUSIONS

Relative to the observed 16-fold variability in UGT1A1 activity, these data indicate only a partial (approximately 40%) contribution of the UGT1A1*28 polymorphism to variability of interindividual differences in UGT1A1 enzyme activity. For the UGT2B7*2 polymorphism, genotype had no influence on immunoreactive UGT2B7 protein or the rate of 3'-azido-3'-deoxythymidine glucuronidation.

Influence of CYP3A5 genotype on the pharmacokinetics and pharmacodynamics of the cytochrome P4503A probes alfentanil and midazolam

The hepatic and first-pass cytochrome P4503A (CYP3A) probe alfentanil (ALF) is also metabolized in vitro by CYP3A5. Human hepatic microsomal ALF metabolism is higher in livers with at least one CYP3A5*1 allele and higher CYP3A5 protein content, compared with CYP3A5*3 homozygotes with little CYP3A5. The influence of CYP3A5 genotype on ALF pharmacokinetics and pharmacodynamics was studied, and compared to midazolam (MDZ), another CYP3A probe. Healthy volunteers (58 men, 41 women) were genotyped for CYP3A5 *1, *3, *6, and *7 alleles. They received intravenous MDZ then ALF, and oral MDZ and ALF the next day. Plasma MDZ and ALF concentrations were determined by mass spectrometry. Dark-adapted pupil diameters were determined coincident with blood sampling. In CYP3A5(*)3/(*)3 (n=62), (*)1/(*)3 (n=28), and (*)1/(*)1 (n=8) genotypes, systemic clearances of ALF were 4.6+/-1.8, 4.8+/-1.7, and 3.9+/-1.7 ml/kg/min and those of MDZ were 7.8+/-2.3, 7.7+/-2.3, and 6.0+/-1.4 ml/kg/min, respectively (not significant), and apparent oral clearances were 11.8+/-7.2, 13.3+/-6.1, and 12.6+/-8.2 ml/kg/min for ALF and 35.2+/-19.0, 36.4+/-15.7, and 29.4+/-9.3 ml/kg/min for MDZ (not significant). Clearances were not different between African Americans (n=25) and Whites (n=68), or between CYP3A5 genotypes within African Americans. ALF pharmacodynamics was not different between CYP3A5 genotypes. There was consistent concordance between ALF and MDZ, in clearances and extraction ratios. Thus, in a relatively large cohort of healthy subjects with constitutive CYP3A activity, CYP3A5 genotype had no effect on the systemic or apparent oral clearances, or pharmacodynamics, of the CYP3A probes ALF and MDZ, despite affecting their hepatic microsomal metabolism.