Frédéric Gaspar1,2,3, Dr Jean Terrier5,6,7, Dr Pierre Fontana6,8, Dr Pauline Gosselin5,6, Prof Youssef Daali7, Prof Jean-Luc Reny5,6, Dr Monia Guidi1,2,3,4, Prof Chantal Csajka1,2,3
1Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, 2School of Pharmaceutical Sciences, University of Geneva, 3Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 4Service of Clinical Pharmacology, Lausanne University Hospital and University of Lausanne, 5Division of General Internal Medicine, Geneva University Hospitals, 6Geneva Platelet Group, Faculty of Medicine, University of Geneva, 7Clinical Pharmacology and Toxicology Service, Anaesthesiology, Pharmacology and Intensive Care Department, Geneva University Hospitals, 8Division of Angiology and Haemostasis, Geneva University Hospitals,
Objectives: Clopidogrel’s active metabolite (clopiH4) exhibits high pharmacokinetic variability, primarily driven by CYP2C19 polymorphisms. Current guidelines rely on genotyping for therapy guidance 1, but fail to account for environmental factors such as drug-drug interactions, hepatic impairment, and inflammation, which can alter enzymatic activity and cause phenoconversion2. This study aimed to develop a population pharmacokinetic (popPK) model of clopiH4 in hospitalized patients, evaluate the respective impact of CYP2C19 genotype and phenotype on metabolite exposure, and assess dose optimization strategies. Methods: Prospective data were collected from 100 hospitalized patients (NCT03477331) receiving clopidogrel 75 mg maintenance therapy, with 300 mg or 600 mg loading doses. ClopiH4 concentrations were measured using a validated LC-MS/MS method. Patients were classified as normal (NMs), poor (PMs), and ultra-rapid metabolizers (UMs) based on CYP2C19 genotyping3,4. In addition, phenotyping at first-dose intake using the Geneva micrococktail assessed CYP2C19 activity, enabling classification based on measured phenotype5. The genotype-phenotype concordance was then evaluated. Pharmacokinetic data were analyzed using a nonlinear mixed-effects model (NONMEM®) to assess the influence of age, body weight, renal function (Cockcroft-Gault clearance), liver function markers (AST, ALT, albumin, bilirubin, GGT, alkaline phosphatase), and CYP2C19 genotype/phenotype on ClopiH4 pharmacokinetics. The dataset was split into a model development set (70 patients) and a validation set (30 patients). Model performance was assessed using bootstrap resampling, corrected visual predictive checks (pcVPCs), and bias/accuracy metrics (MPE, RMSE). To evaluate dosing, three regimens for CYP2C19 PMs, standard (300 mg/75 mg), intermediate (600 mg/150 mg), and high-dose (900 mg/225 mg), were compared to the standard NM regimen based on ClopiH4 exposure (AUC0-6, AUC0-72, Cmax), with clinical relevance assessed against the AUC0-6 target (=20 ng·h/mL). Results: A significant genotype-phenotype discordance (68%) was observed, primarily due to co-medications (proton pump inhibitors, fluoxetine, amiodarone) inhibiting CYP2C19 activity, leading to phenoconversion into functional PMs despite a non-PM genotype. ClopiH4 pharmacokinetics was best described by a one-compartment model with linear elimination, incorporating both zero- and first-order processes for drug uptake and biotransformation, with significant between-subject variability (BSV) in clearance (76%) and distribution (90%). The model identified CYP2C19 phenotype as the only significant covariate, with PMs exhibiting a 54% reduction in ClopiH4 exposure compared to NMs, while CYP2C19 genotype had no significant impact. The final model estimated CL = 7860 L/h, reduced by 24% in PMs (?CYP2C19 = -0.24, CL = 5975 L/h), V = 2280 L, D1 = 0.57 h, and Ka = 2.94 h?¹. Model validation confirmed predictive accuracy and robustness. Model-based simulations showed that the high-dose regimen (900 mg/225 mg) significantly improved ClopiH4 exposure in PMs, achieving AUC0–6 and AUC0–72 levels comparable to NMs receiving the standard regimen (300 mg/75 mg). The intermediate-dose regimen (600 mg/150 mg) only partially compensated for reduced exposure. However, despite dose escalation, exposure remained suboptimal in 32% of PMs, indicating that dose adjustment alone is insufficient for some patients. Conclusions: This study confirms the important variability in clopiH4 pharmacokinetics and underscores the limitations of CYP2C19 genotyping alone in guiding clopidogrel therapy. Phenotyping-based approaches, accounting for drug-drug interactions and real-time enzyme activity, provide a more precise strategy for optimizing clopidogrel exposure, particularly in hospitalized patients where polypharmacy and comorbidities significantly influence metabolism. Although increasing clopidogrel to 900 mg/225 mg improves ClopiH4 exposure in PMs, inter-individual variability remains high, leading to unpredictable drug levels. Given these findings, we recommend switching to alternative P2Y12 inhibitors (e.g., prasugrel or ticagrelor) in CYP2C19 PM patients with high thromboembolic risk. Future research should focus on the prospective validation of the impact of phenotype-guided dosing on platelet inhibition and cardiovascular outcomes, further refining personalized antiplatelet therapy.
1. Pereira NL, Cresci S, Angiolillo DJ, et al. CYP2C19 Genetic Testing for Oral P2Y12 Inhibitor Therapy: A Scientific Statement From the American Heart Association. Circulation 2024;150(6):e129-e150. DOI: 10.1161/CIR.0000000000001257. 2. Rollason V, Mouterde M, Daali Y, et al. Safety of the Geneva Cocktail, a Cytochrome P450 and P-Glycoprotein Phenotyping Cocktail, in Healthy Volunteers from Three Different Geographic Origins. Drug Saf 2020;43(11):1181-1189. DOI: 10.1007/s40264-020-00983-8. 3. Whirl-Carrillo M, McDonagh EM, Hebert JM, et al. Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther 2012;92(4):414-7. DOI: 10.1038/clpt.2012.96. 4. Gaedigk A, Ingelman-Sundberg M, Miller NA, et al. The Pharmacogene Variation (PharmVar) Consortium: Incorporation of the Human Cytochrome P450 (CYP) Allele Nomenclature Database. Clin Pharmacol Ther 2018;103(3):399-401. DOI: 10.1002/cpt.910. 5. Bosilkovska M, Samer CF, Deglon J, et al. Geneva cocktail for cytochrome p450 and P-glycoprotein activity assessment using dried blood spots. Clin Pharmacol Ther 2014;96(3):349-59. DOI: 10.1038/clpt.2014.83.
Reference: PAGE 33 (2025) Abstr 11441 [www.page-meeting.org/?abstract=11441]
Poster: Drug/Disease Modelling - Other Topics