Population pharmacokinetics of mycophenolic acid and Bayesian estimator in lung transplant adults recipients in the early post-transplant period

Mycophenolic acid (MPA), administered as its prodrug Mycophenolate mofetil (MMF), is widely used to prevent rejection after organ solid transplantation. Few population pharmacokinetic studies of MPA in lung transplantation are available, so the present study was designed to describe the population pharmacokinetics (PK) of MPA and develop a maximum a posteriori Bayesian estimator of MPA area under the curve (AUC0-12h) in lung transplant (LT) recipients in the early post-transplant period. We conducted a single-center retrospective study in the Plessis-Robinson hospital (France), including LT recipients receiving MMF in whom at least one concentration-time profile was available during the first 3 months post-transplantation. MPA was measured before intake and 0.5, 1, 2, 4 ± 6 hours post-administration. Patients were divided into an index group (N=72) and a validation group (N=46). A population PK model and a Bayesian estimator with three sampling times were built with the index dataset and externally evaluated with the validation dataset. Analyses were performed using nonlinear mixed-effects models with Monolix® software. The PK model was built using 97 MPA profiles in the index dataset. MPA PK was best described using a two-compartment model with a lag time and first-order absorption and elimination. The significant covariates on the MPA apparent clearance were creatinine, body weight and ciclosporin co-administration and the posttransplantation time on the apparent volume of the central compartment. The model was successfully evaluated in the 60 MPA profiles from the validation dataset. The best Bayesian estimator included samples just before intake, 1 and 4 hours post-administration. The prediction of AUC was unbiased in both datasets and had a precision around 20 %. This is the first Bayesian estimator allowing the prediction of AUC in LT patients without cystic fibrosis in the early post-transplant period, providing a tool to improve the therapeutic drug monitoring of MPA.

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Journal
European Journal of Pharmaceutical Sciences
Published
2025-09-25
DOI
https://doi.org/10.1016/j.ejps.2025.107290
Primary Topic
Renal Transplantation Outcomes and Treatments
Type
article
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article

Population pharmacokinetics of mycophenolic acid and Bayesian estimator in lung transplant adults recipients in the early post-transplant period

Lluch Jérome, Demchenko Alexandra, Verstuyft Céline, Emmanuelle Comets et al.
European Journal of Pharmaceutical Sciences
Renal Transplantation Outcomes and Treatments
article

Population pharmacokinetics of mycophenolic acid and Bayesian estimator in lung transplant adults recipients in the early post-transplant period

Lluch Jérome, Demchenko Alexandra, Verstuyft Céline, Emmanuelle Comets, Aurélie Barrail‐Tran, Kauv Juliette, Feuillet Séverine, Legrand Tiphaine, Furlan Valérie
article en

Abstract

Mycophenolic acid (MPA), administered as its prodrug Mycophenolate mofetil (MMF), is widely used to prevent rejection after organ solid transplantation. Few population pharmacokinetic studies of MPA in lung transplantation are available, so the present study was designed to describe the population pharmacokinetics (PK) of MPA and develop a maximum a posteriori Bayesian estimator of MPA area under the curve (AUC0-12h) in lung transplant (LT) recipients in the early post-transplant period. We conducted a single-center retrospective study in the Plessis-Robinson hospital (France), including LT recipients receiving MMF in whom at least one concentration-time profile was available during the first 3 months post-transplantation. MPA was measured before intake and 0.5, 1, 2, 4 ± 6 hours post-administration. Patients were divided into an index group (N=72) and a validation group (N=46). A population PK model and a Bayesian estimator with three sampling times were built with the index dataset and externally evaluated with the validation dataset. Analyses were performed using nonlinear mixed-effects models with Monolix® software. The PK model was built using 97 MPA profiles in the index dataset. MPA PK was best described using a two-compartment model with a lag time and first-order absorption and elimination. The significant covariates on the MPA apparent clearance were creatinine, body weight and ciclosporin co-administration and the posttransplantation time on the apparent volume of the central compartment. The model was successfully evaluated in the 60 MPA profiles from the validation dataset. The best Bayesian estimator included samples just before intake, 1 and 4 hours post-administration. The prediction of AUC was unbiased in both datasets and had a precision around 20 %. This is the first Bayesian estimator allowing the prediction of AUC in LT patients without cystic fibrosis in the early post-transplant period, providing a tool to improve the therapeutic drug monitoring of MPA.

European Journal of Pharmaceutical SciencesVol. 214
Inserm (FR), Université Paris Cité (FR), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris-Saclay (FR), Sorbonne Université (FR), Université Sorbonne Paris Nord (FR), Assistance Publique – Hôpitaux de Paris (FR), Centre Chirurgical Marie Lannelongue (FR), Hypertension pulmonaire : physiopathologie et innovation thérapeutique (FR), Institut de Recherche en Santé, Environnement et Travail (FR), Hôpital Marie Lannelongue (FR), CEA Paris-Saclay (FR), Bicêtre Hospital (FR), Université de Rennes (FR)
Openalex Percentile: Top 58%
Renal Transplantation Outcomes and Treatments
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