Identifying clinically relevant sources of variability: The clopidogrel challenge

Mind the Gap: Model-Based Switching from Selatogrel to Maintenance Therapy with Oral P2Y12 Receptor Antagonists

Background: The P2Y12 receptor antagonist selatogrel is being developed for subcutaneous self-administration with a ready-to-use autoinjector at the onset of acute myocardial infarction (AMI) symptoms. The unique pharmacological profile of selatogrel (fast, potent, and short-acting) can bridge the time gap between the onset of AMI and first medical care. A clinical Phase 1 study showed a time-dependent pharmacodynamic interaction between selatogrel and loading doses of clopidogrel and prasugrel. As treatment switching is a common clinical practice, the assessment of subsequent switching from a clopidogrel loading dose to the first maintenance dose of oral P2Y12 receptor antagonists is highly relevant. Objectives: Model-based predictions of inhibition of platelet aggregation (IPA) for the drugs triggering pharmacodynamic interactions were to be derived to support clinical guidance on the transition from selatogrel to oral P2Y12 receptor antagonists. Methods: Scenarios with selatogrel 16 mg administration or placebo followed by a clopidogrel loading dose and, in turn, prasugrel or ticagrelor maintenance doses at different times of administration were studied. Population pharmacokinetic/pharmacodynamic modeling and simulations of different treatment scenarios were used to derive quantitative estimates for IPA over time. Results: Following selatogrel/placebo and a clopidogrel loading dose, maintenance treatment with ticagrelor or a prasugrel loading dose followed by maintenance treatment quickly achieved sustained IPA levels above 80%. Prior to maintenance treatment, a short time span from 18 to 24 h was identified where IPA levels were predicted to be lower with selatogrel than with placebo if clopidogrel was administered 12 h after selatogrel or placebo. Predicted IPA levels reached with placebo alone and a clopidogrel loading dose at 4 h were consistently lower than with selatogrel administration, followed by a clopidogrel loading dose at 12 h. If a clopidogrel loading dose is administered at 12 h, selatogrel maintains higher IPA levels up to 16 h. IPA levels are subsequently lower than on the placebo until the administration of the first maintenance dose. Conclusions: Model-based predictions informed the transition from selatogrel subcutaneous administration to oral P2Y12 therapy. The application of modeling techniques illustrates the value of employing pharmacokinetic and pharmacodynamic modeling for the simulation of various clinical scenarios of switching therapies.

Prediction of Omeprazole Pharmacokinetics and its Inhibition on Gastric Acid Secretion in Humans Using Physiologically Based Pharmacokinetic-Pharmacodynamic Model Characterizing CYP2C19 Polymorphisms

PURPOSE

To develop a whole physiologically based pharmacokinetic-pharmacodynamic (PBPK-PD) model to describe the pharmacokinetics and anti-gastric acid secretion of omeprazole in CYP2C19 extensive metabolizers (EMs), intermediate metabolizers (IMs), poor metabolizers (PMs) and ultrarapid metabolizers (UMs) following oral or intravenous administration.

METHODS

A PBPK/PD model was built using Phoenix WinNolin software. Omeprazole was mainly metabolized by CYP2C19 and CYP3A4 and the CYP2C19 polymorphism was incorporated using in vitro data. We described the PD by using a turn-over model with parameter estimates from dogs and the effect of a meal on the acid secretion was also implemented. The model predictions were compared to 53 sets of clinical data.

RESULTS

Predictions of omeprazole plasma concentration (72.2%) and 24 h stomach pH after administration (85%) were within 0.5-2.0-fold of the observed values, indicating that the PBPK-PD model was successfully developed. Sensitivity analysis demonstrated that the contributions of the tested factors to the plasma concentration of omeprazole were Vmax,2C19 ≈ Papp > Vmax,3A4 > Kti, and contributions to its pharmacodynamic were Vmax,2C19 > kome > kms > Papp > Vmax,3A4. The simulations showed that while the initial omeprazole dose in UMs, EMs, and IMs increased 7.5-, 3- and 1.25-fold compared to those of PMs, the therapeutic effect was similar.

CONCLUSIONS

The successful establishment of this PBPK-PD model highlights that pharmacokinetic and pharmacodynamic profiles of drugs can be predicted using preclinical data. The PBPK-PD model also provided a feasible alternative to empirical guidance for the recommended doses of omeprazole.

Physiologically Based Pharmacokinetic (PBPK) Modeling of Clopidogrel and Its Four Relevant Metabolites for CYP2B6, CYP2C8, CYP2C19, and CYP3A4 Drug–Drug–Gene Interaction Predictions

The antiplatelet agent clopidogrel is listed by the FDA as a strong clinical index inhibitor of cytochrome P450 (CYP) 2C8 and weak clinical inhibitor of CYP2B6. Moreover, clopidogrel is a substrate of—among others—CYP2C19 and CYP3A4. This work presents the development of a whole-body physiologically based pharmacokinetic (PBPK) model of clopidogrel including the relevant metabolites, clopidogrel carboxylic acid, clopidogrel acyl glucuronide, 2-oxo-clopidogrel, and the active thiol metabolite, with subsequent application for drug–gene interaction (DGI) and drug–drug interaction (DDI) predictions. Model building was performed in PK-Sim^® using 66 plasma concentration-time profiles of clopidogrel and its metabolites. The comprehensive parent-metabolite model covers biotransformation via carboxylesterase (CES) 1, CES2, CYP2C19, CYP3A4, and uridine 5′-diphospho-glucuronosyltransferase 2B7. Moreover, CYP2C19 was incorporated for normal, intermediate, and poor metabolizer phenotypes. Good predictive performance of the model was demonstrated for the DGI involving CYP2C19, with 17/19 predicted DGI AUC_last and 19/19 predicted DGI C_max ratios within 2-fold of their observed values. Furthermore, DDIs involving bupropion, omeprazole, montelukast, pioglitazone, repaglinide, and rifampicin showed 13/13 predicted DDI AUC_last and 13/13 predicted DDI C_max ratios within 2-fold of their observed ratios. After publication, the model will be made publicly accessible in the Open Systems Pharmacology repository.

Physiologically-Based Pharmacokinetic-Pharmacodynamics Model Characterizing CYP2C19 Polymorphisms to Predict Clopidogrel Pharmacokinetics and Its Anti-Platelet Aggregation Effect Following Oral Administration to Coronary Artery Disease Patients With or Without Diabetes

Background and Objective: Clopidogrel (CLOP) is commonly used in coronary artery disease (CAD) patients with or without diabetes (DM), but these patients often suffer CLOP resistance, especially those with diabetes. This study was aimed to develop a physiologically-based pharmacokinetic-pharmacodynamic (PBPK-PD) model to describe the pharmacokinetics and pharmacodynamics of clopidogrel active metabolite (CLOP-AM) in CAD patients with or without DM.

Methods: The PBPK-PD model was first established and validated in healthy subjects and then in CAD patients with or without DM. The influences of CYP2C19, CYP2C9, CYP3A4, carboxylesterase 1 (CES1), gastrointestinal transit rates (K_t,i) and platelets response to CLOP-AM (k_irre) on predicted pharmacokinetics and pharmacodynamics were investigated, followed with their individual and integrated effects on CLOP-AM pharmacokinetics due to changes in DM status.

Results: Most predictions fell within 0.5–2.0 folds of observations, indicating successful predictions. Sensitivity analysis showed that contributions of interested factors to pharmacodynamics were CES1> k_irre> K_t,i> CYP2C19 > CYP3A4> CYP2C9. Mimicked analysis showed that the decreased exposure of CLOP-AM by DM was mainly attributed to increased CES1 activity, followed by decreased CYP2C19 activity.

Conclusion: The pharmacokinetics and pharmacodynamics of CLOP-AM were successfully predicted using the developed PBPK-PD model. Clopidogrel resistance by DM was the integrated effects of altered K_t,i, CYP2C19, CYP3A4, CES1 and k_irre.

Pharmacokinetics, Tissue Distribution and Excretion of a Novel Diuretic (PU-48) in Rats

Methyl 3-amino-6-methoxythieno [2,3-b] quinoline-2-carboxylate (PU-48) is a novel diuretic urea transporter inhibitor. The aim of this study is to investigate the profile of plasma pharmacokinetics, tissue distribution, and excretion by oral dosing of PU-48 in rats. Concentrations of PU-48 within biological samples are determined using a validated high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. After oral administration of PU-48 (3, 6, and 12 mg/kg, respectively) in self-nanomicroemulsifying drug delivery system (SNEDDS) formulation, the peak plasma concentrations (C_max), and the area under the curve (AUC_0⁻∞) were increased by the dose-dependent and linear manner, but the marked different of plasma half-life (t_1/2) were not observed. This suggests that the pharmacokinetic profile of PU-48 prototype was first-order elimination kinetic characteristics within the oral three doses range in rat plasma. Moreover, the prototype of PU-48 was rapidly and extensively distributed into thirteen tissues, especially higher concentrations were detected in stomach, intestine, liver, kidney, and bladder. The total accumulative excretion of PU-48 in the urine, feces, and bile was less than 2%. This research is the first report on disposition via oral administration of PU-48 in rats, and it provides important information for further development of PU-48 as a diuretic drug candidate.

Pharmacogenetic association study on clopidogrel response in Puerto Rican Hispanics with cardiovascular disease: a novel characterization of a Caribbean population

Introduction

High on-treatment platelet reactivity (HTPR) to clopidogrel imparts an increased risk for ischemic events in adults with coronary artery disease. Platelet reactivity varies with ethnicity and is influenced by both clinical and genetic variables; however, no clopidogrel pharmacogenetic studies with Puerto Rican patients have been reported. Therefore, we sought to identify clinical and genetic determinants of on-treatment platelet reactivity in a cohort of Puerto Rican patients with cardiovascular disease.

Methods

We performed a retrospective study of 111 patients on 75 mg/day maintenance dose of clopidogrel. Patients were allocated into 2 groups: Group I, without HTPR; and Group II, with HTPR. Platelet function was measured ex vivo using the VerifyNow® P2Y12 assay and HTPR was defined as P2Y12 reaction units (PRU) ≥230. Genotyping testing was performed using Taqman^® Genotyping Assays.

Results

The mean PRU across the cohort was 203±61 PRU (range 8–324), and 42 (38%) patients had HTPR. Multiple logistic regression showed that 27% of the total variation in PRU was explained by a history of diabetes mellitus, hematocrit, CYP2C19*2, and PON1 p.Q192R. Body mass index (odds ratio [OR]=1.15; 95% CI: 1.03–1.27), diabetes mellitus (OR=3.46; 95% CI: 1.05–11.43), hematocrit (OR=0.75; 95% CI: 0.65–0.87), and CYP2C19*2 (OR=4.44; 95% CI: 1.21–16.20) were the only independent predictors of HTPR.

Conclusion

Moreover, we propose a predictive model to determine PRU values as measured by VerifyNow P2Y12 assay for the Puerto Rican Hispanic population. This model has the potential to identify Hispanic patients at higher risk for adverse events on clopidogrel.

Investigating Real-World Clopidogrel Pharmacogenetics in Stroke Using a Bioresource Linked to Electronic Medical Records

Clopidogrel efficacy is influenced by genetic variation of cytochrome P450 (CYP)2C19, however, few studies have considered patients who have a stroke. We used electronic medical records (EMRs) linked to a bioresource to examine real-world implications of clopidogrel pharmacogenetics in stroke. Patients hospitalized for any arterial thrombo-occlusive (ATO) event who subsequently redeemed clopidogrel prescriptions in the community were entered into the study (n = 651). During 24-month follow-up, the primary endpoint of recurrent ATO or death occurred in 299 patients (46%). CYP2C19*2 loss-of-function allele carriers had an increased risk (hazard ratio (HR) = 1.29; 95% confidence interval (CI) = 1.04-1.59; P = 0.019). In the ischemic stroke subgroup (n = 94), the estimate of risk was greater (HR = 2.23; 95% CI = 1.17-4.24; P = 0.015), which was further supported by a meta-analysis of available studies. In conclusion, we have demonstrated the clinical impact of CYP2C19*2 on clopidogrel efficacy using a purely EMR approach. This suggests that the risk in the ischemic stroke population may be particularly high.

Influence of genetic co-factors on the population pharmacokinetic model for clopidogrel and its active thiol metabolite

PURPOSE

A high interindividual variability is observed in the pharmacokinetics of clopidogrel, a widely used antiplatelet drug. In the present study, a joint parent-metabolite population pharmacokinetic model was developed to adequately describe observed concentrations of clopidogrel and its active thiol metabolite (H4).

METHODS

The study included 63 patients undergoing elective coronarography or percutaneous coronary intervention. The population pharmacokinetic model was developed in the NONMEM 7.3 software, and first-order conditional estimation method with interaction was applied. Also, the influence of covariates was evaluated (age, weight, body mass index (BMI), obesity defined as BMI ≥ 30 kg/m2, sex, diabetes mellitus, co-administration of PPI or statins, presence of CYP2C19*2, CYP2C19*17, CYP3A4*1G alleles, and ABCB1 3435 TT genotype).

RESULTS

It was found that the only significant covariate was the presence of CYP2C19*2 allele, which had an impact on lower conversion of clopidogrel to H4. As a result, predicted area under the time-concentration curve values was lower in carriers of this allele, with median 5.94 ng h/ml (interquartile range 3.92-12.51 [ng∙h/ml]) vs. 12.70 ng h/ml in non-carriers (interquartile range, 7.00-19.39 [ng∙h/ml]), respectively (p = 0.004).

CONCLUSIONS

Developed model predicts that the only significant covariate influencing the observed concentrations and therefore the exposure to the active H4 metabolite is the presence of CYP2C19*2 allele.

Impact of Drug Treatment at Neonatal Ages on Variability of Drug Metabolism and Drug-drug Interactions in Adult Life

PURPOSE OF REVIEW

As the number of patients taking more than one medication concurrently continues to increase, predicting and preventing drug-drug interactions (DDIs) is now more important than ever. Administration of one drug can cause changes in the expression and activity of drug metabolizing enzymes (DMEs) and alter the efficacy or toxicity of other medications that are substrates for these enzymes, resulting in a DDI. In today's medical practice, potential DDIs are evaluated based on the current medications a patient is taking with little regard to drugs the patient has been exposed to in the past. The purpose of this review is to discuss potential impacts of drug treatment at neonatal ages on the variability of drug metabolism and DDIs in adult life.

RECENT FINDINGS

Existing evidence from the last thirty years has shown that exposure to certain xenobiotics during neonatal life has the potential to persistently alter DME expression through adult life. With recent advancements in the understanding of epigenetic regulation on gene expression, this phenomenon is resurfacing in the scientific community in hopes of defining possible mechanisms. Exposure to compounds that have the ability to bind nuclear receptors and trigger epigenetic modifications at neonatal and pediatric ages may have long-term, if not permanent, consequences on gene expression and DME activity.

SUMMARY

The information summarized in this review should challenge the way current healthcare providers assess DDI potential and may offer an explanation to the significant interindividual variability in drug metabolism that is observed among patients.