Development of a physiology-directed population pharmacokinetic and pharmacodynamic model for characterizing the impact of genetic and demographic factors on clopidogrel response in healthy adults

Xi-Ling Jiang, Snehal Samant, Joshua P Lewis, Richard B Horenstein, Alan R Shuldiner, Laura M Yerges-Armstrong, Lambertus A Peletier, Lawrence J Lesko, Stephan Schmidt, Xi-Ling Jiang, Snehal Samant, Joshua P Lewis, Richard B Horenstein, Alan R Shuldiner, Laura M Yerges-Armstrong, Lambertus A Peletier, Lawrence J Lesko, Stephan Schmidt

Abstract

Clopidogrel (Plavix®), is a widely used antiplatelet agent, which shows high inter-individual variability in treatment response in patients following the standard dosing regimen. In this study, a physiology-directed population pharmacokinetic/pharmacodynamic (PK/PD) model was developed based on clopidogrel and clopidogrel active metabolite (clop-AM) data from the PAPI and the PGXB2B studies using a step-wise approach in NONMEM (version 7.2). The developed model characterized the in vivo disposition of clopidogrel, its bioactivation into clop-AM in the liver and subsequent platelet aggregation inhibition in the systemic circulation reasonably well. It further allowed the identification of covariates that significantly impact clopidogrel's dose-concentration-response relationship. In particular, CYP2C19 intermediate and poor metabolizers converted 26.2% and 39.5% less clopidogrel to clop-AM, respectively, compared to extensive metabolizers. In addition, CES1 G143E mutation carriers have a reduced CES1 activity (82.9%) compared to wild-type subjects, which results in a significant increase in clop-AM formation. An increase in BMI was found to significantly decrease clopidogrel's bioactivation, whereas increased age was associated with increased platelet reactivity. Our PK/PD model analysis suggests that, in order to optimize clopidogrel dosing on a patient-by-patient basis, all of these factors have to be considered simultaneously, e.g. by using quantitative clinical pharmacology tools.

Keywords: CES1; CYP2C19; Clopidogrel; PK/PD modeling; Pharmacogenetics; Physiology-directed population pharmacokinetic and pharmacodynamic model.

Conflict of interest statement

Conflict of interests

The authors have no conflict of interest.

Copyright © 2015 Elsevier B.V. All rights reserved.

Figures

Fig. 1
Fig. 1
Schematic illustration of the proposed PK/PD model for clopidogrel, its active metabolite (clop-AM) and platelet reactivity (P). Fa: fraction absorbed, T1–T3: transit compartments 1–3, τ: first-order transit rate constant, Clint,CES1_CLOP: intrinsic clearance of clopidogrel mediated by carboxyl esterase 1 (CES1), EH,CES1_CLOP: hepatic extraction ratio of clopidogrel mediated by CES1, Vmax,CYPs: maximum metabolic rate of combined cytochrome P450 (CYP) enzymes involved in clopidogrel bioactivation, Km,CYPs: Michaelis–Menten constant for combined CYP activity, EH,CYPs_CLOP: hepatic extraction ratio of clopidogrel mediated by CYP enzymes, FH_CLOP: fraction of clopidogrel that escapes first-pass metabolism in the liver and enters the systemic circulation, VH: liver volume, Q H: liver plasma flow, V3: volume of distribution of clopidogrel in systemic compartment, Clint,CES1_AM: intrinsic clearance of clop-AM mediated by CES1, EH,CES1_AM: hepatic extraction ratio of clop-AM by CES1, FH_AM: fraction of clop-AM that escapes first-pass metabolism and enters the systemic circulation, V5: volume of distribution of clop-AM in systemic compartment, kin: zero-order rate constant characterizing platelet formation, kout: first-order rate constant characterizing the natural turnover of platelets, and kirre: second-order rate constant characterizing the clop-AM-mediated inactivation of platelets.
Fig. 2
Fig. 2
Standard goodness-of-fit plots (top left panel: observed versus population model predicted, top right panel: observed versus individual model predicted, bottom left panel: conditional weighted residuals versus time after dose and bottom right panel: conditional weighted residuals versus population predicted) for: (A) clopidogrel (CLOP), (B) its active metabolite (CLOP-AM) and (C) platelet reactivity (expressed as maximal platelet aggregation (MPA)).
Fig. 2
Fig. 2
Standard goodness-of-fit plots (top left panel: observed versus population model predicted, top right panel: observed versus individual model predicted, bottom left panel: conditional weighted residuals versus time after dose and bottom right panel: conditional weighted residuals versus population predicted) for: (A) clopidogrel (CLOP), (B) its active metabolite (CLOP-AM) and (C) platelet reactivity (expressed as maximal platelet aggregation (MPA)).
Fig. 3
Fig. 3
Prediction-corrected visual predictive check (pcVPC) for: (A) clopidogrel (CLOP), (B) its active metabolite (CLOP-AM) and (C) platelet reactivity (expressed as maximal platelet aggregation (MPA)) using data from the PGXB2B study. For each observation, data was split by dose (75, 150 and 300 mg, respectively) and the CYP2C19 phenotype (EMs, IMs and PMs, respectively). Each individual plot presents individual observed data (black circles), median (solid black line), 5th and 95th percentiles (dashed black lines) for the observed data, and 95% confidence intervals for the median (semitransparent dark gray field), 5% and 95% percentiles (semitransparent light gray fields) for model predictions.
Fig. 3
Fig. 3
Prediction-corrected visual predictive check (pcVPC) for: (A) clopidogrel (CLOP), (B) its active metabolite (CLOP-AM) and (C) platelet reactivity (expressed as maximal platelet aggregation (MPA)) using data from the PGXB2B study. For each observation, data was split by dose (75, 150 and 300 mg, respectively) and the CYP2C19 phenotype (EMs, IMs and PMs, respectively). Each individual plot presents individual observed data (black circles), median (solid black line), 5th and 95th percentiles (dashed black lines) for the observed data, and 95% confidence intervals for the median (semitransparent dark gray field), 5% and 95% percentiles (semitransparent light gray fields) for model predictions.
Fig. 4
Fig. 4
Predictive check for PAPI study data used in model development, which is presented as the impact of CYP2C19 polymorphism, BMI and age on clopidogrel active metabolite (CLOP-AM) PK on Day 7 (A, D, G) and platelet reactivity (expressed as maximal platelet aggregation (MPA)) on Day 0 at baseline (B, E and H) and on Day 7 after clopidogrel treatment (C, F and I). Each individual plot presents individual observed data (circles), loess smoothing line of the observed data (black solid line), the median (gray dashed line) and 90% confidence interval (semitransparent light gray field) for model predictions by age and BMI, and boxplot for model predictions by CYP2C19 polymorphism.
Fig. 5
Fig. 5
Predictive check for PAPI study data used in model qualification, which is presented as the impact of CYP2C19 polymorphism, BMI and age on platelet reactivity (expressed as maximal platelet aggregation (MPA)) on Day 0 at baseline (A, C and E) and on Day 7 after clopidogrel treatment (B, D and F). Each individual plot presents individual observed data (circles), loess smoothing line of the observed data (black solid line), the median (gray dashed line) and 90% confidence interval (semitransparent light gray field) for model predictions by age and BMI, and boxplot for model predictions by CYP2C19 polymorphism.
Fig. 6
Fig. 6
Predictive check for PAPI study data on the impact of CES1 polymorphism on clopidogrel active metabolite (CLOP-AM) PK (A) as well as platelet reactivity (expressed as maximal platelet aggregation (MPA)) on Day 0 at baseline (B) and on Day 7 after clopidogrel treatment (C). Each individual plot presents individual observed data (circles) and boxplots for model predictions. TC: CES1 G143E mutation carriers; CC: CES1 wild-type subjects.

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