Vanessa Guy-Viterbo (1), Anaïs Scohy (1), Raymond Reding (2), Roger Verbeeck (3), Pierre Wallamacq (1), Flora Tshinanu Musuamba (1, 3)
(1) Louvain Center for Toxicology and Applied Pharmacology, Université catholique de Louvain, Brussels, Belgium (2) Pediatric Surgery and Liver transplant Unit, Cliniques Universitaires St-Luc, Université catholique de Louvain, Brussels, Belgium (3) Louvain Drug Research Institute, Université catholique de Louvain, Brussels, Belgium.
Objectives: Different tacrolimus pharmacokinetics (PK) models have been proposed to characterize the tacrolimus PK variability observed in pediatric liver transplantation. They mainly focused on the early post transplantation period. However, as acute rejection may occur up to the end of the first year, the objective of this study was to describe tacrolimus PK during the first year post liver transplantation in a pediatric cohort.
Methods: TAC doses and routine TDM trough levels from 82 pediatric liver allograft recipients during the first year post transplantation were used to develop a population PK model using mixed effects modelling. Patient's demographics, biochemical test results and physiological characteristics were tested as covariates to explain interindividual variability. Data from 42and 40 patients were used for model building and model validation, respectively.
Results: A two-compartment model with first-order elimination best described the TAC PK. Apparent volumes of central and peripheral compartments, intercompartmental clearance and blood clearance estimates were 85L, 100L, 11.3L/h and 4.96L/h, respectively. The absorption first order rate fixed to 4.5h-1. Bodyweight was the only covariate found to have a significant effect on volumes of distribution whilst hematocrit levels, time after transplantation and bodyweight all influenced the TAC clearance. Bias and precision of estimates were within acceptable limits after model validation.
Conclusions: We developed and validated a tacrolimus PK model covering the first year after pediatric liver transplantation. After implementation in PK software with Bayesian prediction, this model could therefore constitute a unique tool to help clinicians for tacrolimus posology adaptation.
Reference: PAGE 22 () Abstr 2701 [www.page-meeting.org/?abstract=2701]
Poster: Paediatrics