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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.

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 EC 50 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.

Objectives: To assess the impact of the loss-of-function CYP3A5*3 allele (rs776746, 6986A>G SNP) on darunavir (DRV) plasma concentrations., Methods: 135 HIV-1 infected patients treated with DRV-based therapy were included in the study and plasma samples were obtained immediately before drug intake in order to determine DRV trough concentrations using an ultra performance liquid chromatography method (UPLC) with diode-array detection (DAD). Noteworthy is the fact that in 16 (11.9%) patients, etravirine (ETR) was combined with DRV. CYP3A5 genotypes were determined using real time PCR method (TaqMan® genotyping assay). The patients were then classified into CYP3A5 expressors (CYP3A5*1 allele carriers) and non-expressors (CYP3A5*3 homozygous). Subsequently, the association between DRV plasma trough concentration ([DRV]plasma) and CYP3A5 genotype-based expression status was analyzed., Results: 45% of the patients were classified as CYP3A5 expressors. In the whole cohort, mean [DRV]plasma was not different between CYP3A5 expressors and non-expressors (1894ng/ml [CI95%: 1566-2290] versus 1737ng/ml [CI95%: 1468-2057], p = 0.43). However, in the subgroup of the 16 patients receiving DRV combined with ETR, a significantly lower [DRV]plasma was observed for CYP3A5 expressors when compared to non-expressors (1385ng/ml [CI95%:886.3-2165] versus 3141ng/ml [CI95%:2042-4831], p = 0.007)., Conclusions: Interaction between DRV and ETR is partly mediated by CYP3A5 polymorphism with lower DRV plasma trough concentrations in CYP3A5 expressors suggesting a specific ETR-driven CYP3A5 activation only in CYP3A5 expressors. Consequently, these patients might be more at risk of infra-therapeutic [DRV]plasma. This potentially important observation is a good illustration of a genotype-based drug interaction, which could also have considerable consequences if translated to other CYP3A5-metabolized drugs. Further investigations are thus needed to confirm this association and to explore its clinical impact, mainly in the African population among whom CYP3A5 expressors are more frequent, before recommending systematic CYP3A5 pre-emptive genotyping for DRV-ETR co-administration., Competing Interests: The authors have declared that no competing interests exist.

Objectives: To describe the validation of a sensitive high performance liquid chromatography tandem mass spectrometry (LC-MS/MS) method allowing the simultaneous quantification of darunavir (DRV) and etravirine (ETR) in peripheral blood mononuclear cells (PBMCs) and its application in a cohort of HIV-1 infected patients., Methods: Blood samples were obtained from 110 patients. PMBCs were isolated using density gradient centrifugation. Drug extraction from PBMCs was performed with a 60:40 methanol-water (MeOH-H2O) solution containing deuterated IS (DRV-d9 and ETR-d8). The chromatographic separation was performed on a RP18 XBridge™ column., Results: The geometric mean (GM) of cell associated concentration ([DRV]CC) and plasmatic concentration ([DRV]plasma) were 360.5ng/mL (CI95%:294.5-441.2) and 1733ng/mL (CI95%:1486-2021), respectively. A geometric mean intracellular (IC)/plasma ratio (GMR) of 0.21 (CI95%:0.18-0.24) was calculated. Adjusted for dose/body surface area and post-intake time, a statistically significant correlation was observed between [DRV]Plasma and the eGFR (p=0.002) and between [DRV]Plasma and the concomitant use of ETR (p=0.038). For the 10 patients receiving ETR in addition to DRV, the GM of [ETR]Plasma (available for 8 out of 10 patients) and [ETR]CC were 492.3ng/mL and 2951ng/mL respectively. The GMR of ETR was 7.6 (CI95%: 3.61-13.83)., Conclusions: A handy and sensitive high performance LC-MS/MS method allowing the simultaneous quantification of DRV and ETR in PBMCs has been described and successfully applied in the largest cohort of DRV-treated patients reported to date. ETR accumulates more efficiently in PBMCs compared to DRV. We have also highlighted a possible impact of ETR on DRV plasma concentrations requiring further investigations., (Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.)