Pharmacokinetic tools for the dose adjustment of ciclosporin in haematopoietic stem cell transplant patients.: cyclosporine modeling in stem cell transplants

Autor: Woillard, Jean-Baptiste, Lebreton, Vincent, Neely, Michael, Turlure, Pascal, Girault, Stéphane, Debord, Jean, Marquet, Pierre, Saint-Marcoux, Franck
Přispěvatelé: Pharmacologie des Immunosuppresseurs et de la Transplantation (PIST), Université de Limoges (UNILIM)-CHU Limoges-Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST FR CNRS 3503)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratory of Applied Pharmacokinetics, University of California [Los Angeles] (UCLA), University of California-University of California, Service d'Hématologie clinique et thérapie cellulaire [CHU Limoges], CHU Limoges, Service de Pharmacologie, toxicologie et pharmacovigilance [CHU Limoges], Dynamic Reconfigurable Massively Parallel Architectures and Languages (DREAMPAL), Université de Lille, Sciences et Technologies-Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), University of California (UC)-University of California (UC)
Jazyk: angličtina
Rok vydání: 2014
Předmět:
Zdroj: British Journal of Clinical Pharmacology
British Journal of Clinical Pharmacology, Wiley, 2014, 78 (4), pp.836-46. ⟨10.1111/bcp.12394⟩
British Journal of Clinical Pharmacology, 2014, 78 (4), pp.836-46. ⟨10.1111/bcp.12394⟩
ISSN: 0306-5251
1365-2125
DOI: 10.1111/bcp.12394⟩
Popis: International audience; Ciclosporin A (CsA) is used in the prophylaxis and treatment of acute and chronic graft vs. host disease after haematopoietic stem cell (HSCT) transplantation. Our objective was to build and compare three independent Bayesian estimators of CsA area under the curve (AUC) using a limited sampling strategy (LSS), to assist in dose adjustment. The Bayesian estimators were developed using in parallel: two independent parametric modelling approaches (nonmem® and iterative two stage (ITS) Bayesian modelling) and the non-parametric adaptive grid method (Pmetrics®). Seventy-two full pharmacokinetic profiles (at pre-dose and 0.33, 0.66, 1, 2, 3, 4, 6, 8 and 12h after dosing) collected from 40 HSCT patients given CsA were used to build the pharmacokinetic models, while 15 other profiles (n = 7) were kept for validation. For each Bayesian estimator, AUCs estimated using the full profiles were compared with AUCs estimated using three samples. The pharmacokinetic profiles were well fitted using a two compartment model with first order elimination, combined with a gamma function for the absorption phase with ITS and Pmetrics or an Erlang distribution with nonmem. The derived Bayesian estimators based on a C0-C1 h-C4 h sampling schedule (best LSS) accurately estimated CsA AUC(0,12 h) in the validation group (n = 15; nonmem: bias (mean ± SD)/RMSE 2.05% ± 13.31%/13.02%; ITS: 4.61% ± 10.56%/11.20%; Pmetrics: 0.30% ± 10.12%/10.47%). The dose chosen confronting the three results led to a pertinent dose proposal. The developed Bayesian estimators were all able to predict ciclosporin AUC(0,12 h) in HSCT patients using only three blood with minimal bias and may be combined to increase the reliability of CsA dose adjustment in routine.
Databáze: OpenAIRE
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