Joint population pharmacokinetic model for clopidogrel and its inactive carboxylic acid metabolite
Zorica Pejčić (1,2), Valentina Topić Vučenović (3), Branislava Miljković (2), Katarina Vučićević (2)
(1) Medicines and Medical Devices Agency of Serbia, Belgrade, Republic of Serbia, (2) University of Belgrade – Faculty of Pharmacy, Department of Pharmacokinetics and Clinical Pharmacy, Belgrade, Republic of Serbia, (3) University of Banja Luka Faculty of Medicine, Department of Pharmacy, Banja Luka, Bosnia and Herzegovina.
Introduction: Clopidogrel, an antiplatelet agent, exhibits complex pharmacokinetics. It is rapidly absorbed after oral administration and extensively metabolized in the liver. Since it is a prodrug, approximately 85% of the oral dose is hydrolyzed to the inactive metabolite clopidogrel carboxylic acid, while 15% of the dose is oxidized by cytochrome P (CYP) 450 isoenzymes to its active metabolite clopidogrel thiol. Clopidogrel carboxylic acid is the major circulating metabolite with much higher plasma levels than clopidogrel and clopidogrel thiol [1]. To date, there are only a few published population pharmacokinetic (PK) models for clopidogrel and its metabolites [2-9], most of which focus on the active metabolite. A joint model for clopidogrel and its inactive metabolite that takes into account first-pass effect (FPE) in the liver has not yet been comprehensively investigated.
Objectives: The aim of this study was to characterize the process of clopidogrel absorption and its conversion to clopidogrel carboxylic acid through the joint population pharmacokinetic model.
Methods: Data from two bioequivalence studies were used, in which 24 and 26 volunteers participated and in which extensive blood samples were taken up to 48 and 36 hours, respectively. In each study, a single generic medicine of clopidogrel film coated tablets, 75 mg, was assessed in comparison to Plavix film coated tablets, 75 mg (Sanofi) as the reference medicine. Both studies were conducted according to the same 2-way cross-over design, after a single dose of clopidogrel 150 mg (2 tablets) was administered under fasting conditions. A total of 1556 plasma samples were available. Plasma concentrations of clopidogrel and clopidogrel carboxylic acid were determined in both studies using a validated HPLC-MS method, with a lower limit of quantification of 0.5 ng/ml for clopidogrel and 0.1 µg/ml for clopidogrel carboxylic acid. Our dataset included all demographic and clinical assessment data including biochemical parameters, randomization scheme, time of dose administration and blood sampling, concentration of clopidogrel and clopidogrel carboxylic acid. The data were analyzed using NONMEM® 7.5. Model building procedure was based on a previous publication using the hepatic compartment to characterize the FPE [7]. Drug’s absorption was tested as a first-order, standard lag time and transit compartment model. In addition, both one- and two-compartment models with linear elimination were tested for both the parent drug and the inactive metabolite. Several models for the variability of different parameters were also tested. The adequacy of the model was based on several numerical and graphical criteria. The final model was validated using nonparametric bootstrap technique and visual predictive check including 1000 replicates.
Results: Our joint model for clopidogrel and its inactive metabolite includes transit compartment model for drug absorption, hepatic compartment for FPE, one-compartment distribution model for parent and two-compartment for clopidogrel carboxylic acid. A total of 24 (including 11 structural) model parameters were estimated. The mean transit time (MTT) for two studies were 0.495 h and 0.412 h. Estimated fraction metabolized to an inactive metabolite was estimated at 87.4% and 87.0% for two studies. Relative bioequivalence for both generic medicines compared to reference medicine was 1.09 and 0.959, and their 95% confidence intervals included 1. Relative standard errors of structural parameters were up to 13.5%. Interoccasional and interindividual variability was incorporated on absorption parameters, while interindividual was estimated on volumes of distribution, and study-specific proportional error models described residual variability. VPC for both parent and inactive metabolite shows good agreement between measured and simulated concentration data.
Conclusion: We have successfully characterized clopidogrel pharmacokinetics focusing on absorption and its conversion to inactive carboxylic acid metabolite.
Acknowledgement: This research was funded by the Ministry of Science, Technological Development and Innovation, Republic of Serbia through two Grant Agreements with University of Belgrade-Faculty of Pharmacy No 451-03-65/2024-03/ 200161 and No 451-03-66/2024-03/ 200161.
References:
[1] Plavix film-coated tablets 75 mg EPAR – Product information EMEA/H/C/000174 (http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/000174/WC500042189.pdf).
[2] Ernest CS et al. Population pharmacokinetics and pharmacodynamics of prasugrel and clopidogrel in aspirin-treated patients with stable coronary artery disease. J Pharmacokinet Pharmacodyn. 2008;35(6):593-618.
[3] Zhang L et al. Semi-mechanistic population pharmacokinetics analysis reveals distinct CYP2C19 dependency in the bioactivation of vicagrel and clopidogrel to active metabolite M15-2. Eur J Pharm Sci. 2022;177:106264.
[4] Jiang XL et al. 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. Eur J Pharm Sci. 2016 January 20; 82: 64–78.
[5] Danielak D et al. Influence of genetic co-factors on the population pharmacokinetic model for clopidogrel and its active thiol metabolite. Eur J Clin Pharmacol. 2017;73(12):1623-1632.
[6] Zakaria ZH et al. Clopidogrel Pharmacokinetics in Malaysian Population Groups: The Impact of Inter-Ethnic Variability. Pharmaceuticals 2018, 11, 74.
[7] Jung YS et al. Population pharmacokinetic pharmacodynamic modeling of clopidogrel for dose regimen optimization based on CYP2C19 phenotypes: A proof of concept study. CPT Pharmacometrics Syst Pharmacol. 2023;00:1-12.
[8] Yousef AM et al. Population pharmacokinetic analysis of clopidogrel in healthy Jordanian subjects with emphasis optimal sampling strategy. Biopharm Drug Dispos. 2013;34(4):215-226.
[9] Lee J et al. Population pharmacokinetic/pharmacodynamic modeling of clopidogrel in Korean healthy volunteers and stroke patients. J Clin Pharmacol. 2012;52(7):985-995.
