A Limited Sampling Strategy to Estimate Exposure of Everolimus in Whole Blood and Peripheral Blood Mononuclear Cells in Renal Transplant Recipients Using Population Pharmacokinetic Modeling and Bayesian Estimators
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.
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.
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).
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.
The authors thank Mrs Karen Poole of the Department of Pharmacology, Toxicology and Pharmacovigilance, CHU Limoges for manuscript editing.
Compliance with Ethical Standards
The authors did not receive any funding for this project.
Conflict of interest
I. Robertsen, J. Debord, A. Åsberg, K. Midtvedt, P. Marquet, and J.-B. Woillard declare that they have no conflicts of interest.
Research involving human participants
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
- 8.Capron A, Lerut J, Latinne D, Rahier J, Haufroid V, Wallemacq P. Correlation of tacrolimus levels in peripheral blood mononuclear cells with histological staging of rejection after liver transplantation: preliminary results of a prospective study. Transpl Int. 2012;25:41–7.CrossRefPubMedGoogle Scholar
- 14.Vethe NT, Gjerdalen LC, Bergan S. Determination of cyclosporine, tacrolimus, sirolimus and everolimus by liquid chromatography coupled to electrospray ionization and tandem mass spectrometry: assessment of matrix effects and assay performance. Scand J Clin Lab Invest. 2010;70(8):583–91.CrossRefPubMedGoogle Scholar
- 17.Nagy G. Ordinary differential equations. 2017. http://users.math.msu.edu/users/gnagy/teaching/ode.pdf. Accessed 26 Oct 2017
- 27.Tanaka C, O’Reilly T, Kovarik JM, Shand N, Hazell K, Judson I, et al. Identifying optimal biologic doses of everolimus (RAD001) in patients with cancer based on the modeling of preclinical and clinical pharmacokinetic and pharmacodynamic data. J Clin Oncol. 2008;26(10):1596–602.CrossRefGoogle Scholar
- 29.Saint-Marcoux F, Knoop C, Debord J, Thiry P, Rousseau A, Estenne M, et al. Pharmacokinetic study of tacrolimus in cystic fibrosis and non-cystic fibrosis lung transplant patients and design of Bayesian estimators using limited sampling strategies. Clin Pharmacokinet. 2005;44(12):1317–28.CrossRefPubMedGoogle Scholar