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Aims: The pharmacokinetics of doravirine has been studied in clinical trials but not in real‐world settings. Our study aims to characterize and identify factors influencing doravirine (a CYP3A4 substrate) pharmacokinetics in real‐world people with HIV (PWH). Methods: A total of 174 doravirine concentrations measured in 146 PWH followed up in the therapeutic drug monitoring (TDM) program at the University Hospital of Lausanne (Switzerland) between 2019 and 2023 were included in the analysis. Demographic data, clinical information and comedications were recorded during the routine SHCS visits (every 3–6 months). Population pharmacokinetic analysis and Monte Carlo simulations to investigate the clinical significance of the covariates retained in the final model were performed using NONMEM. Results: A one‐compartment model with first‐order absorption and linear elimination best described doravirine pharmacokinetics. Potent CYP3A4 inhibitors and, to a lesser extent age, were the only tested covariates to significantly impact doravirine clearance (CL). Potent CYP3A4 inhibitors reduced CL by 50%, and a 30% decrease in CL was observed in an 80‐year‐old compared with a 55‐year‐old PWH. The effect of potent CYP3A4 inhibitors was prominent, explaining 59% of between‐subject variability in CL. Model‐based simulations predicted 2.8‐fold and 1.6‐fold increases in median steady‐state trough and maximum doravirine concentrations, respectively, when a potent CYP3A4 inhibitor was co‐administered. Conclusions: Our findings show that potent CYP3A4 inhibitors and age influence doravirine pharmacokinetics. However, given the good tolerability of doravirine, dosing adjustment of doravirine is probably not mandatory in those situations. TDM remains useful essentially in specific clinical situations, such as hepatic impairment, suspected nonadherence or pregnancy. [ABSTRACT FROM AUTHOR]

Background Tenofovir alafenamide is gradually replacing tenofovir disoproxil fumarate, both prodrugs of tenofovir, in HIV prevention and treatment. There is thus an interest in describing tenofovir pharmacokinetics (PK) and its variability in people living with HIV (PLWH) under tenofovir alafenamide in a real-life setting. Objectives To characterize the usual range of tenofovir exposure in PLWH receiving tenofovir alafenamide, while assessing the impact of chronic kidney disease (CKD). Methods We conducted a population PK analysis (NONMEM®) on 877 tenofovir and 100 tenofovir alafenamide concentrations measured in 569 PLWH. Model-based simulations allowed prediction of tenofovir trough concentrations (C min) in patients having various levels of renal function. Results Tenofovir PK was best described using a one-compartment model with linear absorption and elimination. Creatinine clearance (CLCR, estimated according to Cockcroft and Gault), age, ethnicity and potent P-glycoprotein inhibitors were statistically significantly associated with tenofovir clearance. However, only CLCR appeared clinically relevant. Model-based simulations revealed 294% and 515% increases of median tenofovir C min in patients with CLCR of 15–29 mL/min (CKD stage 3), and less than 15 mL/min (stage 4), respectively, compared with normal renal function (CLCR = 90–149 mL/min). Conversely, patients with augmented renal function (CLCR > 149 mL/min) had a 36% decrease of median tenofovir C min. Conclusions Kidney function markedly affects circulating tenofovir exposure after tenofovir alafenamide administration in PLWH. However, considering its rapid uptake into target cells, we suggest only a cautious increase of tenofovir alafenamide dosage intervals to 2 or 3 days only in case of moderate or severe CKD, respectively. [ABSTRACT FROM AUTHOR]

SHCS#879 is an ongoing Switzerland-wide multicenter observational study conducted within the Swiss HIV Cohort Study (SHCS) for the prospective follow-up of people living with HIV (PLWH) receiving long-acting injectable cabotegravir-rilpivirine (LAI-CAB/RPV). All adults under LAI-CAB/RPV and part of SHCS are enrolled in the project. The study addresses an integrated strategy of treatment monitoring outside the stringent frame of controlled clinical trials, based on relevant patient characteristics, clinical factors, potential drug-drug interactions, and measurement of circulating blood concentrations. So far, 91 blood samples from 46 PLWH have been collected. Most individuals are less than 50 years old, with relatively few comorbidities and comedications. The observed concentrations are globally in accordance with the available values reported in the randomized clinical trials. Yet, low RPV concentrations not exceeding twice the reported protein-adjusted 90% inhibitory concentration have been observed. Data available at present confirm a considerable between-patient variability overall. Based on the growing amount of PK data accumulated during this ongoing study, population pharmacokinetic analysis will characterize individual concentration-time profiles of LAI-CAB/RPV along with their variability in a real-life setting and their association with treatment response and tolerability, thus bringing key data for therapeutic monitoring and precision dosage adjustment of this novel long-acting therapy. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the association between dolutegravir (DTG) pharmacokinetic parameters and weight changes in treatment‐experienced people with HIV (PWHIV) from the Simpl'HIV study newly switched to a dual DTG‐based regimen. We used multivariable linear regressions to evaluate the association between DTG pharmacokinetic parameters at week 48 (derived using an established model) and weight change between week 0 and week 48. We adjusted our model for potential confounders including CD4 nadir, female sex, African origin, age, weight at week 0 and presence of a non‐nucleoside reverse transcriptase inhibitor‐based regimen before switch to DTG. The analysis included data from 39 PWHIV. An average significant weight gain of 2.4 kg was observed between baseline and week 48. DTG plasma exposure was not significantly associated with weight gain, even after adjusting for potential confounders (P =.9). We found no significant association between DTG pharmacokinetic parameters and weight gain amongst PWHIV newly switched to a DTG‐based dual regimen. [ABSTRACT FROM AUTHOR]

Purpose: Drug-drug interactions (DDIs) with antiretroviral drugs (ARVs) represent an important issue in elderly people living with HIV (PLWH). Amlodipine is a commonly prescribed antihypertensive drug metabolized by CYP3A4, thus predisposed to a risk of DDIs. Guidance on the management of DDIs is mostly based on theoretical considerations derived from coadministration with other CYP3A4 inhibitors. This study aimed at characterizing the magnitude of DDIs between amlodipine and ARV drugs in order to establish dosing recommendations. Methods: A population pharmacokinetic analysis was developed using non-linear mixed effect modelling (NONMEM) and included 163 amlodipine concentrations from 55 PLWH. Various structural and error models were compared to characterize optimally the concentration-time profile of amlodipine. Demographic and clinical characteristics as well as comedications were tested as potential influential covariates. Model-based simulations were performed to compare amlodipine exposure (i.e. area under the curve, AUC) between coadministered ARV drugs. Results: Amlodipine concentration-time profile was best described using a one-compartment model with first-order absorption and a lag-time. Amlodipine apparent clearance was influenced by both CYP3A4 inhibitors and efavirenz (CYP3A4 inducer). Model-based simulations revealed that amlodipine AUC increased by 96% when coadministered with CYP3A4 inhibitors, while efavirenz decreased drug exposure by 59%. Conclusion: Coadministered ARV drugs significantly impact amlodipine disposition in PLWH. Clinicians should adjust amlodipine dosage accordingly, by halving the dosage in PLWH receiving ARV with inhibitory properties (mainly ritonavir-boosted darunavir), whereas they should double amlodipine doses when coadministering it with efavirenz, under appropriate monitoring of clinical response and tolerance. [ABSTRACT FROM AUTHOR]

Background: Rosuvastatin is a lipid-lowering agent widely prescribed in people living with HIV, which is actively transported into the liver, making it a potential victim of drug–drug interactions with antiretroviral agents. Objectives: The aims of this study were to characterise the pharmacokinetic profile of rosuvastatin and to describe the relationship between rosuvastatin concentrations and non-high-density lipoprotein (HDL)-cholesterol levels in people living with HIV. Methods: A population pharmacokinetic model (NONMEM) was developed to quantify the influence of demographics, clinical characteristics and comedications on rosuvastatin pharmacokinetics. This model was combined with an indirect effect model to describe non-HDL-cholesterol measurements. Results: A two-compartment model with sequential zero- and first-order absorption best fitted the 154 rosuvastatin concentrations provided by 65 people living with HIV. None of the tested covariates significantly influenced rosuvastatin pharmacokinetics. A total of 403 non-HDL cholesterol values were available for pharmacokinetic-pharmacodynamic modelling. Baseline non-HDL cholesterol decreased by 14% and increased by 12% with etravirine and antiretroviral drugs with a known impact on the lipid profile (i.e. protease inhibitors, efavirenz, cobicistat), respectively. The baseline value was surprisingly 43% lower in people living with HIV aged 80 years compared with those aged 40 years. Simulations based on the covariate-free model predicted that, under standard rosuvastatin dosages of 5 mg and 20 mg once daily, 31% and 64% of people living with HIV would achieve non-HDL-cholesterol targets, respectively. Conclusions: The high between-subject variability that characterises both rosuvastatin pharmacokinetic and pharmacodynamic profiles remained unexplained after the inclusion of usual covariates. Considering its limited potential for drug–drug interactions with antiretroviral agents and its potent lipid-lowering effect, rosuvastatin prescription appears safe and effective in people living with HIV with hypercholesterolaemia. Clinical Trial Registration No.: NCT03515772. [ABSTRACT FROM AUTHOR]

Objectives: Co-formulated elvitegravir, cobicistat, tenofovir disoproxil fumarate and emtricitabine is among the preferred regimens for first-line ART. A population approach was used to characterize the pharmacokinetics of elvitegravir and cobicistat and identify individual factors and co-medications influencing their disposition, taking into consideration the interaction between the two compounds.Methods: The study population included 144 HIV-infected individuals who provided 186 and 167 elvitegravir and cobicistat plasma concentrations, respectively. First, distinct NONMEM(®) analyses were conducted for elvitegravir and cobicistat, including individual demographic, clinical and genetic factors as potential covariates. Elvitegravir and cobicistat interaction was then assessed through different inhibitory models. Simulations based on the final model served to compare expected drug concentrations under standard and alternative dosage regimens.Results: Clearance with between-subject variability was 7.6 L/h [coefficient of variation (CV) 16.6%] and volume of distribution 61 L for elvitegravir and 16.0 L/h (CV 41.9%) and 88.3 L, respectively, for cobicistat. Concomitant administration of non-ritonavir-boosted atazanavir decreased elvitegravir clearance by 35%, likely due to UDP-glucuronosyl transferase (UGT) 1A1 inhibition. Concomitant administration of non-ritonavir-boosted atazanavir and ritonavir-boosted darunavir decreased cobicistat clearance by 47% and 27%, respectively. The final interaction model included cobicistat exposure (AUC0-24) on elvitegravir clearance. Simulations confirmed that a reduced elvitegravir dose of 85 mg co-administered with cobicistat and atazanavir produces a concentration-time course comparable to the standard regimen without atazanavir.Conclusions: Elvitegravir and cobicistat pharmacokinetic variability appears to be mainly explained by drug-drug interactions that may be encountered in routine clinical practice. In these cases, therapeutic drug monitoring and surveillance for potential toxicities would be justified. [ABSTRACT FROM AUTHOR]