Tacrolimus Pharmacokinetics is Associated with Gut Microbiota Diversity in Kidney Transplant Patients: Results from a Pilot Cross-Sectional Study.

Clinical use of tacrolimus (TAC), an essential immunosuppressant following transplantation, is complexified by its high pharmacokinetic (PK) variability. The gut microbiota gains growing interest but limited investigations have evaluated its contribution to TAC PKs. Here, we explore the associations between the gut microbiota composition and TAC PKs. In this pilot cross-sectional study (Clinicaltrial.gov NCT04360031), we recruited 93 CYP3A5 non-expressers stabilized kidney transplant recipients. Gut microbiota composition was characterized by 16S rRNA gene sequencing, TAC PK parameters were computed, and additional demographic and medical covariates were collected. Associations between PK parameters or diabetic status and the gut microbiota composition, as reflected by α- and ß-diversity metrics, were evaluated. Patients with higher TAC area under the curve AUC/(dose/kg) had higher bacterial richness, and TAC PK parameters were associated with specific bacterial taxa (e.g., Bilophila) and amplicon sequence variant (ASV; e.g., ASV 1508 and ASV 1982 (Veillonella/unclassified Sporomusaceae); ASV 664 (unclassified Oscillospiraceae)). Building a multiple linear regression model showed that ASV 1508 (co-abundant with ASV 1982) and ASV 664 explained, respectively, 16.0% and 4.6% of the interindividual variability in TAC AUC/(dose/kg) in CYP3A5 non-expresser patients, when adjusting for hematocrit and age. Anaerostipes relative abundance was decreased in patients with diabetes. Altogether, this pilot study revealed unprecedented links between the gut microbiota composition and diversity and TAC PKs in stable kidney transplant recipients. It supports the relevance of studying the gut microbiota as an important contributor to TAC PK variability. Elucidating the causal relationship will offer new perspectives to predict TAC inter- and intra-PK variability.

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.

Population Pharmacokinetics of Hydroxychloroquine in COVID-19 Patients: Implications for Dose Optimization.

BACKGROUND AND OBJECTIVE: In the absence of characterization on pharmacokinetics and reference concentrations for hydroxychloroquine in COVID-19 patients, the dose and treatment duration for hydrochloroquine are currently empirical, mainly based on in vitro data, and may vary across national guidelines and clinical study protocols. The aim of this paper is to describe the pharmacokinetics of hydroxychloroquine in COVID-19 patients, considered to be a key step toward its dosing optimization. METHODS: We have developed a population pharmacokinetic model for hydroxychloroquine in COVID-19 patients using prospectively collected pharmacokinetic data from patients either enrolled in a clinical trial or treated with hydroxychloroquine as part of standard of care in two tertiary Belgian hospitals. RESULTS: The final population pharmacokinetic model was a one-compartment model with first-order absorption and elimination. The estimated parameter values were 9.3/h, 860.8 L, and 15.7 L/h for the absorption rate constant, the central compartment volume, and the clearance, respectively. The bioavailability factor was fixed to 0.74 based on previously published models. Model validations by bootstraps, prediction corrected visual predictive checks, and normalized prediction distribution errors gave satisfactory results. Simulations were performed to compare the exposure obtained with alternative dosing regimens. CONCLUSION: The developed models provide useful insight for the dosing optimization of hydroxychloroquine in COVID-19 patients. The present results should be used in conjunction with exposure-efficacy and exposure-safety data to inform optimal dosing of hydroxychloroquine in COVID-19.

Quantification of darunavir and etravirine in human peripheral blood mononuclear cells using high performance liquid chromatography tandem mass spectrometry (LC-MS/MS), clinical application in a cohort of 110 HIV-1 infected patients and evidence of a potential drug-drug interaction.

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.