Modélisation pharmacocinétique de la ciclosporine par approche en population chez les transplantes rénaux

Abstract

Aim Development of a population pharmacokinetic (PK) model for Algerian kidney transplant recipients treated with ciclosporin A (CsA), with the aim of applying it to pharmacological therapeutic drug monitoring. Patients and Methods A prospective study was conducted involving 55 renal transplant patients receiving oral CsA, with an average daily dose of 175 mg divided into two doses. PK parameter estimation was performed using Monolix® 2024R1 software with the SAEM (Stochastic Approximation Expectation-Maximization) algorithm. Results A one-compartment model with first-order absorption and linear elimination was used as the PK model. The absorption constant (Ka) was fixed at 1 h⁻¹. The estimated mean volume of distribution (Vd) was 82.61 L (RSE 8.49%), and the apparent clearance (CL) was 16.08 L/h (RSE 5.86%). Inter-individual variability for Ka, Vd, and CL was estimated at 0.37, 0.11, and 0.17, respectively. Covariate analysis identified triglycerides (TG) as an individual factor significantly influencing CsA clearance. The predictive performance of the population model was found to be satisfactory. A dose adjustment formula was proposed, taking into account the identified covariate. Conclusion A population pharmacokinetic model was successfully developed to reasonably estimate Vd and CL of CsA in renal transplant patients. This model can be used to individualize CsA dosing in order to rapidly and effectively achieve target blood concentrations, improving both the safety and efficacy of therapy.