Evaluation of limited sampling models for prediction of oral midazolam AUC for CYP3A phenotyping and drug interaction studies

Intrasubject Variability in Intravenous and Oral Probes for Hepatic and First-Pass CYP3A Activity

BACKGROUND AND OBJECTIVES

Clearances and the area under the plasma concentration-time curve extrapolated to infinity (AUC0-∞) of intravenous (IV) and oral midazolam and alfentanil are probes for hepatic and first-pass cytochrome P450 3A (CYP3A) activity, drug interactions, and phenotyping. Single-time plasma concentrations are also used as a proxy for clearance and AUC0-∞. Pupil diameter change is a noninvasive surrogate for plasma alfentanil. An ideal probe should have minimal intrasubject (interday) variability. Despite their widespread use, the intrasubject variability of CYP3A probes is not well characterized. This investigation determined the intrasubject (interday) variability of midazolam and alfentanil metrics of hepatic and first-pass CYP3A.

METHODS

Twelve volunteers were studied in a four-period protocol, with each period identical and separated by approximately 2 weeks. In each period, participants received 1 mg IV midazolam then 15 μg/kg IV alfentanil 1 h later. The next day, they received 3 mg oral midazolam then 60 μg/kg oral alfentanil. Plasma drug concentrations were determined by liquid chromatography-mass spectrometry (LCMS). Dark-adapted pupil diameters were measured coincident with blood sampling. Plasma concentrations and pupil effects (miosis) were analyzed using noncompartmental methods. The results were the coefficient of variation (%CV, mean ± SD) across four sessions in 12 participants.

RESULTS

For IV midazolam: AUC0-∞, clearance, and 5 h concentration, the %CVs were 12 ± 3, 12 ± 3, and 18 ± 8. For IV alfentanil AUC0-∞, clearance, 2 h concentration, and area under the effect curve from time zero to infinity (AUEC0-∞), the %CVs were 16 ± 5, 15 ± 4, 22 ± 7, and 50 ± 28. For oral midazolam AUC0-∞, clearance, and 5 h concentration, %CVs were 19 ± 5, 18 ± 4, and 28 ± 11. For oral alfentanil: AUC0-∞, clearance, 4 h concentration, and AUEC0-∞, %CVs were 20 ± 4, 21 ± 4, 42 ± 26, and 37 ± 14.

CONCLUSIONS

Midazolam and alfentanil had comparable intrasubject variabilities of clearance and AUC0-∞. Single-time point metrics had greater intrasubject variability than AUC0-∞ and clearance. Miosis was a surrogate for alfentanil concentrations and provided real-time results, but intrasubject variability was greater than that of clearances and AUC0-∞.

Fexofenadine Plasma Concentrations to Estimate Systemic Exposure in Healthy Adults Using a Limited Sampling Strategy with a Population Pharmacokinetic Approach

BACKGROUND

Fexofenadine is a recommended in vivo probe drug for phenotyping P-glycoprotein (P-gp) and organic anion transporting polypeptide (OATP) 1B1/3 transporter activities. This study evaluated a limited sampling strategy using a population pharmacokinetic approach to estimate plasma fexofenadine exposure as an index of P-gp and OATP activities.

METHODS

In a previous study, a single oral dose of fexofenadine (120 mg) was administered alone or in combination with grapefruit juice, Panax ginseng , or Echinacea purpurea to healthy adult participants. Serial plasma samples were collected up to 72 hours after administration and fexofenadine concentrations were measured. A population pharmacokinetic model was developed using nonlinear mixed-effects modeling. Limited sampling models (LSMs) using single and 2-timepoint fexofenadine concentrations were compared with full profiles from intense sampling using empirical Bayesian post hoc estimations of systemic exposure derived from the population pharmacokinetic model. Predefined criteria for LSM selection and validation included a coefficient of determination (R 2 ) ≥ 0.90, relative percent mean prediction error ≥ -5 to ≤5%, relative percent mean absolute error ≤ 10%, and relative percent root mean square error ≤ 15%.

RESULTS

Fexofenadine concentrations (n = 1520) were well described using a 2-compartment model. Grapefruit juice decreased the relative oral bioavailability of fexofenadine by 25%, whereas P. ginseng and E. purpurea had no effect. All the evaluated single timepoint fexofenadine LSMs showed unacceptable percent mean prediction error, percent mean absolute error, and/or percent root mean square error. Although adding a second time point improved precision, the predefined criteria were not met.

CONCLUSIONS

Identifying novel fexofenadine LSMs to estimate P-gp and OATP1B1/3 activities in healthy adults for future transporter-mediated drug-drug interaction studies remains elusive.

Limited sampling strategies for estimation of tacrolimus exposure in kidney transplant recipients receiving extended-release tacrolimus preparation

Tacrolimus is the key component of most contemporary immunosuppressive drug regimens for the prevention of transplant rejection. Area under the concentration time curve over 24 h (AUC_0–24) predicts efficacy, but predose (trough) tacrolimus blood concentration (C₀) is currently used to guide dosing. In clinical or research situations where an estimate of AUC is required, collection of a full 24 h pharmacokinetic (PK) profile is cumbersome. Limited sampling strategies (LSSs) have been developed for some tacrolimus preparations but not for the new, extended‐release, once‐daily formulation of tacrolimus, ENVARSUS XR. Twenty‐four kidney transplant recipients were enrolled in this study. Twenty‐four tacrolimus PK profiles were obtained over 24 h. Multiple linear regression was used to generate LSSs with the best subset selection for accurate estimation of tacrolimus AUC_0–24. The predictive performance of each model was assessed in the evaluation group. The correlation between actual and predicted AUC_0–24 was evaluated and mean percentage prediction error (MPE%), mean absolute percentage prediction error (MAE%), and root mean squared error (RMSE) were calculated for each prediction model to assess bias and precision. The selected LSSs were highly correlated to AUC_0–24 compared with the correlation between C₀ and AUC_0‐24. Two and three sampling points limited sampling strategies: C₀, C₂, and C₁₀ provide the most reliable and effective LSS for estimation of tacrolimus AUC_0–24 in routine clinic use. These limited sampling models can be applied in therapeutic drug monitoring schemes to personalize tacrolimus dosing for kidney transplant recipients on treatment with extended‐release tacrolimus.

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.

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.

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

OBJECTIVE

Intravenous (IV) midazolam is the preferred cytochrome P450 (CYP) 3A probe for phenotyping, with systemic clearance (CL) estimating hepatic CYP3A activity. A limited sampling strategy was conducted to determine whether partial area under the concentration-time curves (AUCs) could reliably estimate midazolam systemic CL during conditions of CYP3A baseline activity, inhibition, and induction/activation.

METHODS

Midazolam plasma concentrations during CYP3A baseline (n = 93), inhibition (n = 40), and induction/activation (n = 33) were obtained from 7 studies in healthy adults. Noncompartmental analysis determined observed CL (CL(obs)) and partial AUCs. Linear regression equations were derived from partial AUCs to estimate CL (CL(pred)) during CYP3A baseline, inhibition, and induction/activation. Preestablished criterion for linear regression analysis was r(2) ≥ 0.9. CL(pred) was compared with CL(obs), and relative bias and precision were assessed using percent mean prediction error and percent mean absolute error.

RESULTS

During CYP3A baseline and inhibition, all evaluated partial AUCs failed to meet criterion of r(2) ≥ 0.9 and/or percent mean absolute error <15%. During CYP3A induction/activation, equations derived from partial AUCs from 0 to 1 hour (AUC0-1), 0 to 2 hours (AUC0-2), and 0 to 4 hours (AUC0-4) were acceptable, with good precision and minimal bias. These equations provided the same conclusions regarding equivalency testing compared with intense sampling.

CONCLUSIONS

During CYP3A induction/activation, but not baseline or inhibition, midazolam partial AUC0-1, AUC0-2, and AUC0-4 reliably estimated systemic CL and consequently hepatic CYP3A activity in healthy adults.

Effect of brivaracetam on CYP3A activity, measured by oral midazolam

Brivaracetam is a synaptic vesicle protein 2A ligand in phase III development for epilepsy. A phase I, open-label, randomized study was conducted in 42 healthy male participants to assess the effect of brivaracetam on CYP3A activity using midazolam as a probe. Participants were randomized to oral brivaracetam 5, 50, or 150 mg/day from Day 8 to Day 14. A single oral dose (7.5 mg) of midazolam was administered on Days 1, 13, and 20, and full pharmacokinetic profiles were obtained. For all brivaracetam doses, the areas under the plasma concentration-time curves from 0 to infinity (AUCinf ) for midazolam and 1'-hydroxymidazolam were similar on Days 13 and 20 compared with Day 1. Following brivaracetam 150 mg/day, the Day 13/Day 1 AUCinf ratio (90% confidence interval) was 1.09 (0.97, 1.21) and 1.04 (0.93, 1.17) for midazolam and 1'-hydroxymidazolam, respectively. For the Day 20/Day 1 comparison, the corresponding AUCinf ratios were 1.10 (0.98, 1.23) and 1.07 (0.97, 1.18). Maximum midazolam plasma concentration was increased on both Day 13 and Day 20 vs. Day 1 but the relevance of this finding was unclear. This study indicates that brivaracetam up to 150 mg/day has no significant inducing or inhibiting effect on CYP3A activity.

Searching for an optimal AUC estimation method: a never-ending task?

An effective method of construction of a linear estimator of AUC in the finite interval, optimal in the minimax sense, is developed and demonstrated for five PK models. The models may be given as an explicit C(t) relationship or defined by differential equations. For high variability and rich sampling the optimal method is only moderately advantageous over optimal trapezoid or standard numerical approaches (Gauss-Legendre or Clenshaw-Curtis quadratures). The difference between the optimal estimator and other methods becomes more pronounced with a decrease in sample size or decrease in the variability. The described estimation method may appear useful in development of limited-sampling strategies for AUC determination, as an alternative to the widely used regression-based approach. It is indicated that many alternative approaches are also possible.