Ida Robertsen1, Jean Debord2,3, Anders Åsberg4,5, Pierre Marquet2,3, Jean-Baptiste Woillard2,3. 1. Department of Pharmaceutical Biosciences, School of Pharmacy, University of Oslo, P.O. Box 1068 Blindern, 0316, Oslo, Norway. ida.robertsen@farmasi.uio.no. 2. Department of Pharmacology, Toxicology and Pharmacovigilance, CHU Limoges, Limoges, France. 3. INSERM, UMR 1248, University of Limoges, Limoges, France. 4. Department of Pharmaceutical Biosciences, School of Pharmacy, University of Oslo, P.O. Box 1068 Blindern, 0316, Oslo, Norway. 5. Department of Transplantation Medicine, Clinic for Surgery, Inflammatory Medicine and Transplantation, Oslo University Hospital-Rikshospitalet, Oslo, Norway.
Abstract
BACKGROUND AND OBJECTIVE: Intracellular exposure of everolimus may be a better marker of therapeutic effect than trough whole blood concentrations. We aimed to develop pharmacokinetic population models and Bayesian estimators based on a limited sampling strategy for estimation of dose interval exposures of everolimus in whole blood and peripheral blood mononuclear cells (PBMCs) in renal transplant recipients. METHODS: Full whole blood and PBMC concentration-time profiles of everolimus were obtained from 12 stable renal transplant recipients on two different occasions, 4 weeks apart. The dataset was treated as 24 individual profiles and split into a development dataset (n = 20) and a validation dataset (n = 4). The pharmacokinetic model was developed using non-parametric modeling and its performances and those of the derived Bayesian estimator were evaluated in the validation set. RESULTS: A structural two-compartment model with first-order elimination and two absorption phases described by a sum of two gamma distributions were developed. None of the tested covariates (age, sex, albumin, hematocrit, fat-free mass and genetic variants such as CYP3A5*1, ABCB1 haplotype, PPARA*42, PPARA*48, and POR*28) were retained in the final model. A limited sampling schedule of two whole blood samples at 0 and 1.5 h and one PBMC sample at 1.5 h post dose provided accurate estimates of the area under the plasma concentration-time curve (AUC) in comparison with the trapezoidal reference AUC (relative bias ± standard deviation = - 3.9 ± 10.6 and 4.1 ± 12.3% for whole blood and PBMC concentrations, respectively). CONCLUSION: The developed model allows simultaneous and accurate prediction of everolimus exposure in whole blood and PBMCs, and supplies a base for a feasible exploration of the relationships between intracellular exposure and therapeutic effects in prospective trials.
BACKGROUND AND OBJECTIVE: Intracellular exposure of everolimus may be a better marker of therapeutic effect than trough whole blood concentrations. We aimed to develop pharmacokinetic population models and Bayesian estimators based on a limited sampling strategy for estimation of dose interval exposures of everolimus in whole blood and peripheral blood mononuclear cells (PBMCs) in renal transplant recipients. METHODS: Full whole blood and PBMC concentration-time profiles of everolimus were obtained from 12 stable renal transplant recipients on two different occasions, 4 weeks apart. The dataset was treated as 24 individual profiles and split into a development dataset (n = 20) and a validation dataset (n = 4). The pharmacokinetic model was developed using non-parametric modeling and its performances and those of the derived Bayesian estimator were evaluated in the validation set. RESULTS: A structural two-compartment model with first-order elimination and two absorption phases described by a sum of two gamma distributions were developed. None of the tested covariates (age, sex, albumin, hematocrit, fat-free mass and genetic variants such as CYP3A5*1, ABCB1 haplotype, PPARA*42, PPARA*48, and POR*28) were retained in the final model. A limited sampling schedule of two whole blood samples at 0 and 1.5 h and one PBMC sample at 1.5 h post dose provided accurate estimates of the area under the plasma concentration-time curve (AUC) in comparison with the trapezoidal reference AUC (relative bias ± standard deviation = - 3.9 ± 10.6 and 4.1 ± 12.3% for whole blood and PBMC concentrations, respectively). CONCLUSION: The developed model allows simultaneous and accurate prediction of everolimus exposure in whole blood and PBMCs, and supplies a base for a feasible exploration of the relationships between intracellular exposure and therapeutic effects in prospective trials.
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