Limited sampling strategy of partial area under the concentration-time curves to estimate midazolam systemic clearance for cytochrome P450 3A phenotyping

Validation of a 3-h Sampling Interval to Assess Variability in Cytochrome P450 3A Phenotype and the Impact of Induction and Mechanism-Based Inhibition Using Midazolam as a Probe Substrate

Background: Drug probe phenotyping is used extensively in academic and industry research to evaluate cytochrome P450 (CYP) phenotype in order to account for sources of between- and within- subject variability in metabolic clearance. In terms of application, CYP3A is the most important drug metabolizing enzyme the most frequently studied. Currently, phenotyping studies for CYP3A involve the administration of midazolam and collection of timed blood samples up to 24-48 hours in order to determine an area under the plasma concentration time curve (AUC). The key challenge that limits the use of midazolam-based phenotyping for CYP3A in academic research settings and preclude the use of this approach in a clinical setting is the logistical burden of collecting frequent blood samples for up to 48 h post dose following the administration of a probe drug ± an interacting drug. Aim: The current study sought to validate if a reduced sampling interval could be used to accurately define both between-subject variability in CYP3A phenotype and the magnitude of changes in CYP3A activity due to either induction or mechanism-based inhibition. Methods: The area under the curve (AUC) for midazolam was assessed under baseline, induction (7 days rifampin, 300 mg daily) and, following a washout period of 4 days, mechanism based inhibition (3 days clarithromycin, 250 mg daily) conditions in a cohort of 30 health males. The capacity of normalized reduced sampling interval AUCs measured over 0 to 1, 0 to 2, 0 to 3, and 0 to 4 h to accurately define the AUC_0-6 was evaluated with respect to precision (R2 for correlation), bias (slope of normalized correlation), agreement (Bland Altman analysis) and proportional bias (linear regression of Bland Altman parameters). Results: Robust concordance was observed between the AUC calculated from PK collection intervals of 0 to 3 and 0 to 6 h in terms of both the measurement of between-subject variability in midazolam AUC and changes in midazolam AUC due to induction and mechanism-based inhibition of CYP3A4. Conclusion: On this basis, it is proposed that a 3-h assessment of midazolam AUC (AUC_0-3) represents a viable strategy to reduce the logistical burden associated with the assessment of CYP3A phenotype.

Clinical Studies on Drug-Drug Interactions Involving Metabolism and Transport: Methodology, Pitfalls, and Interpretation

Many drug-drug interactions (DDIs) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life-threatening consequences. There has been tremendous progress in the predictability and modeling of DDIs. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDIs involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically-based pharmacokinetic modeling, complex DDIs, methodological pitfalls, and interpretation of DDI information.

Assessment of Pharmacokinetic Drug-Drug Interactions in Humans: In Vivo Probe Substrates for Drug Metabolism and Drug Transport Revisited

Pharmacokinetic parameters of selective probe substrates are used to quantify the activity of an individual pharmacokinetic process (PKP) and the effect of perpetrator drugs thereon in clinical drug-drug interaction (DDI) studies. For instance, oral caffeine is used to quantify hepatic CYP1A2 activity, and oral dagibatran etexilate for intestinal P-glycoprotein (P-gp) activity. However, no probe substrate depends exclusively on the PKP it is meant to quantify. Lack of selectivity for a given enzyme/transporter and expression of the respective enzyme/transporter at several sites in the human body are the main challenges. Thus, a detailed understanding of the role of individual PKPs for the pharmacokinetics of any probe substrate is essential to allocate the effect of a perpetrator drug to a specific PKP; this is a prerequisite for reliably informed pharmacokinetic models that will allow for the quantitative prediction of perpetrator effects on therapeutic drugs, also in respective patient populations not included in DDI studies.

Evaluation of Omeprazole Limited Sampling Strategies to Estimate Constitutive Cytochrome P450 2C19 Activity in Healthy Adults

BACKGROUND

Limited sampling strategy (LSS) is a validated method to estimate pharmacokinetic (PK) parameters from a reduced number of samples. Omeprazole is used to phenotype in vivo cytochrome P450 (CYP) 2C19 activity. This study examined an LSS using 2 estimation methods to determine apparent oral clearance (CL/F) and thus CYP2C19 activity.

METHODS

Data from 7 previously published studies included healthy subjects receiving a single, oral dose of omeprazole with intensive PK sampling. CL/F was estimated using noncompartmental analysis (NCA) and population PK modeling. LSS was simulated by selecting the 1, 2, 4, and/or 6-hour postdose time points. Linear regression was performed to assess whether CL/F estimated from limited sampling could accurately predict CL/F from the full PK profile.

RESULTS

Median CL/F was 23.7 L/h by NCA and 19.3 L/h by population PK modeling. In comparing the LSS NCA estimated versus observed CL/F, all evaluated linear regression models had unacceptable coefficients of determination (r, range: 0.14-0.81). With the population PK approach, 737 plasma concentrations (n = 71) and CYP2C19 genotype data were described with a 1-compartment structural model with mixed zero and first-order absorption and lag time. In comparing the population PK LSS estimated versus observed CL/F, all evaluated linear regression models had unacceptable r (range: 0.02-0.74). Post hoc comparison of CYP2C19 poor metabolizers versus CYP2C19 extensive metabolizers resulted in significantly lower CL/F in poor metabolizers versus extensive metabolizers.

CONCLUSIONS

Omeprazole LSS performed poorly in estimating CL/F using 2 separate estimation approaches and does not seem to be a suitable method for determining CYP2C19 activity.

CYP3A activity: towards dose adaptation to the individual

INTRODUCTION

Co-medication, gene polymorphisms and co-morbidity are main causes for high variability in expression and function of the CYP3A isoenzymes. Pharmacokinetic variability is a major source of interindividual variability of drug effect and response of CYP3A substrates. While CYP3A genotyping is of limited use, direct testing of enzyme function ('phenotyping') may be more promising to achieve individualized dosing of CYP3A substrates.

AREAS COVERED

We will discuss available phenotyping strategies for CYP3A isoenzymes and causes of intra- and interindividual variability of CYP3A. The impact of phenotyping on the dose selection and pharmacokinetics of CYP3A substrates (docetaxel, irinotecan, tyrosine kinase inhibitors, ciclosporin, tacrolimus) are reviewed. Pubmed searches were conducted during March-November 2015 to retrieve articles related to CYP3A enzyme, phenotyping, drug interactions with CYP3A probe substrates, and phenotyping-guided dosing algorithms.

EXPERT OPINION

While ample data is available on the choice appropriate phenotyping drugs (midazolam, alfentanil, aplrazolam, buspirone, triazolam), less clinical trial data is available concerning strategies to usefully guide dosing in the clinical practice. Implementation into the clinical routine necessitates further research to identify (1) an easy-to-use and cheap test for CYP3A activity that (2) adequately predicts drug exposure to (3) allow a sound decision on dose adaptation and hence (4) improve clinical outcome and/or reduce the intensity or frequency of adverse drug effects.

Multiplex Phenotyping for Systems Medicine: A One-Point Optimized Practical Sampling Strategy for Simultaneous Estimation of CYP1A2, CYP2C9, CYP2C19, and CYP2D6 Activities Using a Cocktail Approach

Phenotyping of the CYP450 enzyme activities contributes to personalized medicine, but the past phenotyping approaches have followed a piecemeal strategy measuring single enzyme activities in vivo. A barrier to phenotyping of populations in rural and remote areas is the limited time and resources for sample collection. The CEIBA cocktail approach allows metabolic capacity estimation of multiple CYP450 enzymes in a single sample analysis, but the attendant sample collection schemes for applications in diverse global settings are yet to be optimized. The present study aimed to select an optimal matrix to simultaneously analyze CYP450 enzyme activities so as to simplify the sampling schemes in the phenotyping protocol to enhance its throughput and feasibility in native populations or in remote and underserviced geographies and social contexts. We evaluated 13 Ecuadorian healthy volunteers for CYP1A2, CYP2C9, CYP2C19, and CYP2D6 genotypes and their metabolic phenotypes, including CYP3A4, in plasma and urine after administering one reduced dose of caffeine, losartan, omeprazole, and dextromethorphan. Pharmacokinetic analyses were performed, and the correlation between AUC parent/AUC metabolite and the ratio between concentrations of probe drugs and their corresponding metabolites at timepoints ranging from 0 to 12 hours post-dose were analyzed. A single sampling timepoint, 4 hours post-dose in plasma, was identified as optimal to reflect the metabolic activity of the attendant CYP450 enzymes. This study optimizes the CEIBA multiplexed phenotyping approach and offers new ways forward for integrated drug metabolism analyses, in the pursuit of global personalized medicine applications in resource-limited regions, be they in developed or developing countries.