Atorvastatin population pharmacokinetics in a real-life setting: Influence of genetic polymorphisms and association with clinical response.

The purpose of this study was to investigate the potential clinical relevance of estimating the apparent clearance (CL/F) of atorvastatin through population pharmacokinetic (PopPK) modeling with samples collected in a real-life setting in a cohort of ambulatory patients at risk of cardiovascular disease by using an opportunistic sampling strategy easily accessible in clinical routine. A total of 132 pharmacokinetic (PK) samples at a maximum of three visits were collected in the 70 included patients. The effects of demographic, genetic, and clinical covariates were also considered. With the collected data, we developed a two-compartment PopPK model that allowed estimating atorvastatin CL/F relatively precisely and considering the genotype of the patient for SLCO1B1 c.521T>C single-nucleotide polymorphism (SNP). Our results indicate that the estimation of the CL/F of atorvastatin through our PopPK model might help in identifying patients at risk of myalgia. Indeed, we showed that a patient presenting a CL/F lower than 414.67 L h-1 is at risk of suffering from muscle discomfort. We also observed that the CL/F was correlated with the efficacy outcomes, suggesting that a higher CL/F is associated with a better drug efficacy (i.e., a greater decrease in total and LDL-cholesterol levels). In conclusion, our study demonstrates that PopPK modeling can be useful in daily clinics to estimate a patient' atorvastatin clearance. Notifying the clinician with this information can help in identifying patients at risk of myalgia and gives indication about the potential responsiveness to atorvastatin therapy.

Effect of four ABCB1 genetic polymorphisms on the accumulation of darunavir in HEK293 recombinant cell lines.

The intracellular penetration of darunavir, a second-generation HIV protease inhibitor, is limited by the activity of the efflux P-glycoprotein (ABCB1). ABCB1 expression and/or activity levels can vary between individuals due to genetic polymorphisms including the c.1199G>A, c.1236C>T, c.2677G>T and c.3435C>T variants, which could in part explain why the pharmacokinetics of darunavir are so variable from one individual to another. While a few clinical studies have failed to demonstrate an influence of these polymorphisms on darunavir pharmacokinetics, drug-drug interactions and methodological limitations may have prevented them from revealing the true influence of ABCB1 variants. In this work, we report on the intracellular accumulation of darunavir in recombinant HEK293 cell lines expressing wild-type ABCB1 or one of several variants: ABCB1 1199A, ABCB1 3435T, and ABCB1 1236T/2677T/3435T. We demonstrate that while ABCB1 expression limits intracellular accumulation of darunavir, there is no significant difference in efflux activity between cells expressing wild-type ABCB1 and those that express any of the studied variants.

Exploration of Reduced Doses and Short-Cycle Therapy for Darunavir/Cobicistat in Patients with HIV Using Population Pharmacokinetic Modeling and Simulations.

BACKGROUND AND OBJECTIVES: Protease inhibitors such as darunavir are an important therapeutic option in the anti-human immunodeficiency virus arsenal. Current dosage guidelines recommend using cobicistat- or ritonavir-boosted darunavir 800 mg every 24 h (q24h) in protease inhibitor-naïve patients, or ritonavir-boosted darunavir 600 mg q12h in experienced patients. However, darunavir displays a large, poorly characterized, inter-individual pharmacokinetic variability. The objectives of this study were to investigate the pharmacokinetics of darunavir and to elucidate the sources of its inter-individual variability using population pharmacokinetic modeling. Then, to determine the appropriateness of current treatment guidelines and the feasibility of alternative dosing regimens in a representative cohort of adult patients using simulations. METHODS: Sparse pharmacokinetic samples were collected in 127 patients with human immunodeficiency virus type 1 infection, then supplemented with rich sampling data from a subset of 12 individuals. Data were analyzed using the nonlinear mixed-effects modeling software NONMEM. The effect of reduced doses (600 mg q24h and 400 mg q24h) or reduced frequency of administration (800 mg q24h for 5 days followed by 2 days of treatment interruption) was simulated. RESULTS: Our model adequately described the pharmacokinetics of darunavir. Predictors of individual exposure were CYP3A5*3 and SLCO3A1 rs8027174 genotypes, sex, and alpha-1 acid glycoprotein level. No relationship was apparent between darunavir area under the curve and treatment efficacy or safety. For reduced dose regimens, darunavir concentrations remained above the protein binding-corrected EC50 in the majority of subjects. More stringent pharmacokinetic targets were not reached in a significant proportion of patients. CONCLUSIONS: These results add to the growing body of evidence that darunavir-based therapy could be simplified to reduce costs and toxicity, as well as to improve patient compliance. However, the heterogeneity in pharmacokinetic response should be considered when assessing whether individual patients could benefit from a particular regimen, for instance through the use of population pharmacokinetic models. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03101644, date of registration: 5 April, 2017.

Optimal sampling strategies for darunavir and external validation of the underlying population pharmacokinetic model.

PURPOSE: A variety of diagnostic methods are available to validate the performance of population pharmacokinetic models. Internal validation, which applies these methods to the model building dataset and to additional data generated through Monte Carlo simulations, is often sufficient, but external validation, which requires a new dataset, is considered a more rigorous approach, especially if the model is to be used for predictive purposes. Our first objective was to validate a previously published population pharmacokinetic model of darunavir, an HIV protease inhibitor boosted with ritonavir or cobicistat. Our second objective was to use this model to derive optimal sampling strategies that maximize the amount of information collected with as few pharmacokinetic samples as possible. METHODS: A validation dataset comprising 164 sparsely sampled individuals using ritonavir-boosted darunavir was used for validation. Standard plots of predictions and residuals, NPDE, visual predictive check, and bootstrapping were applied to both the validation set and the combined learning/validation set in NONMEM to assess model performance. D-optimal designs for darunavir were then calculated in PopED and further evaluated in NONMEM through simulations. RESULTS: External validation confirmed model robustness and accuracy in most scenarios but also highlighted several limitations. The best one-, two-, and three-point sampling strategies were determined to be pre-dose (0 h); 0 and 4 h; and 1, 4, and 19 h, respectively. A combination of samples at 0, 1, and 4 h was comparable to the optimal three-point strategy. These could be used to reliably estimate individual pharmacokinetic parameters, although with fewer samples, precision decreased and the number of outliers increased significantly. CONCLUSIONS: Optimal sampling strategies derived from this model could be used in clinical practice to enhance therapeutic drug monitoring or to conduct additional pharmacokinetic studies.

Rivaroxaban plasma levels in patients admitted for bleeding events: insights from a prospective study.

BACKGROUND: Serious bleeding events have been frequently described in patients taking direct oral anticoagulants (DOAC). In secondary analyses of phase 3 trials, DOAC plasma concentrations were shown to correlate with bleeding outcomes. This study aimed to describe rivaroxaban plasma levels in patients admitted to the emergency department (ED) for bleeding events. For each patient, risk factors for experiencing bleeding events were also investigated. METHODS: This analysis was part of an observational study conducted in the ED of two teaching hospitals. Plasma samples from 10 rivaroxaban-treated patients admitted for bleeding events were collected. Rivaroxaban plasma concentrations were determined by calibrated chromogenic anti-Xa assay. The measured rivaroxaban levels were then extrapolated at trough using a published population pharmacokinetic (PopPK) model, and compared to on-therapy ranges observed in large clinical trials. For each patient, clinical, medication and ABCB1 genotype data were collected. RESULTS: Rivaroxaban measurements varied from 5 to 358 ng/ml, with a post-intake delay ranging from 9 to 38 h. At trough, estimated plasma concentrations were between 12 and 251 ng/ml (median value 94 ng/ml). Four patients had higher-than-expected rivaroxaban levels. Inadequate dose regimen, excessive alcohol consumption and lack of treatment reassessment were observed in several patients. Half of patients were taking ≥1 drug with potential pharmacokinetics interactions (e.g. amiodarone, diltiazem), while half of patients were taking ≥1 drug increasing the risk of bleeding. All 3 patients with available genotyping data and higher-than-expected rivaroxaban levels were heterozygous or homozygous mutated for the ABCB1 1236C > T, 2677G > T, 3435 C > T and rs4148738 single nucleotide polymorphisms (SNP). CONCLUSIONS: Rivaroxaban patients admitted to the ED for bleeding events showed highly variable plasma concentrations. This analysis underlines the usefulness of rapid DOAC measurement and the value of PopPK models to estimate concentrations at trough in a context where the post-intake delay is unmanageable. Close patient follow-up, including renal function assessment and drug interactions review, is essential for bleeding risk minimization.

Pharmacogenetic associations with cytochrome P450 in antiretroviral therapy: what does the future hold?

INTRODUCTION: Several antiretroviral drugs used to treat infection with the human immunodeficiency virus (HIV) are substrates of enzymes belonging to the cytochrome P450 (CYP) superfamily, which are polymorphically expressed. It may therefore be useful to take into account the genetic variation in these enzymes to predict the likelihood of anti-HIV treatment success, toxicity and the potential for drug-drug interactions. Areas covered: In this manuscript, the authors discuss the current state of knowledge regarding pharmacogenetic associations between CYP and all major antiretrovirals, as well as the importance of these associations. Expert opinion: While many pharmacogenetic associations for CYP have been described in the literature, replication studies are sometimes lacking. The implementation of this knowledge in clinical practice also remains difficult. Further efforts are required both to expand this field of knowledge and to enable its use in everyday clinical practice.