F. Riglet (1), C. Barau (2), AM. Taburet (3), J. Bertrand (1)
(1) : IAME, UMR 1137, INSERM, Université Paris Diderot, Sorbonne Paris Cité, Paris, France; (2) : AP-HP, Hôpital Henri Mondor, Plateforme de Ressources Biologiques, Créteil, France; (3) : AP-HP, Hôpital Bicêtre, Hôpitaux Universitaires Paris Sud, Service de Pharmacie Clinique, Paris, France
Objectives:
Mycophenolic acid (MPA) is an immunosuppressant drug used to prevent graft rejection, which acts as an inhibitor of inosine-monophosphate dehydrogenase (IMPDH). It shows a narrow therapeutic index, especially in renal transplant recipients because of its great between-patient variability [1,2]. So currently, in France, Therapeutic Drug Monitoring (TDM) of MPA is carried out by evaluating the Area Under the Curve (AUC0-12) of total MPA in plasma in order to improve long-term allograft survival with adequate dosing [3]. However, because MPA mechanism of action occurs into peripheral blood mononuclear cells (PBMCs), it is reasonable to think that carrying out TDM at cellular level could be more efficient to predict drug efficacy or adverse effect. The aim of the present study was to build a pharmacokinetics (PK) model using a population approach to describe MPA total and unbound concentrations in plasma and into PBMCs in adult kidney transplant recipients. We hoped to quantify average PK parameter values and their respective between and within subject variability (B and WSV), in this specific population, and to understand the origins of MPA PK high variability.
Methods:
PK data for MPA were available from 78 patients, included in the CIMTRe study, on 4 occasions; 15 days (D15), 1 month (M1), 2 months (M2) and 6 months (M6) after renal transplantation which amounted to 1993 PK samples. All patients originally received a dose of 1000 mg twice daily of mycophenolate mofetil (MMF), ester prodrug of MPA. Plasma total and unbound MPA as well as MPA in PBMCs concentration-time profiles were collected over 12h after the drug intake. Population analysis was performed using non-linear mixed-effects modelling with the Monolix® software.
Results:
A three-compartment PK model with a zero order absorption (Tk0u=1.85 h, BSV=83%) and a first order elimination (Clu/F= 965 L.h-1, 41%) was used to describe all unbound MPA concentration–time data at month 1 after renal transplantation. Unbound MPA distribution was described with one central compartment (Vcu/F=1430 L, 13%), one peripheral compartment (Vpu/F=37800 L, 127%) and an intercompartmental clearance (Qu/F=2330 L.h-1, 50%). The third compartment described the distribution of the drug in the PBMCs with three estimated parameters: the input rate into the cell (Clinu/F = 28.5 L.h-1, 80 %), the output rate from the cell (Cloutu/F = 0.76 L.h-1, 69%) and the volume of distribution in the cells (Vcellu/F = 223 L). A proportionality factor parameter described the linear link between plasma unbound and total MPA concentrations (Bmax = 52.8, 20%). With this model, the unbound MPA fraction obtained was then 1.86%, which is in agreement with the data of MPA literature. From this model, we derived MPA exposures in the plasma (total and unbound) and in the cells. We estimated a MPAunbound AUC0-12 median = 0.93 [0.79 – 1.22] mg.h.L-1 and a MPAtotal AUC0-12 median = 49.35 [41.98 – 65.02] mg.h.L-1. Such exposures correspond to a clearance of MPAtotal Clt/F = 20 L.h-1. All these parameters were close to values found in the literature [2]. Lastly, the MPAcellular AUC0-12 median was estimated at 29.16 [13.94 – 53.62] mg.h.L-1.
Conclusions:
The population PK model developed during this study successfully characterized MPA pharmacokinetics in adult patients with transplanted kidneys, including unbound and cellular pharmacokinetics. Although modelling of D15, M2, and M6 samples and covariates analyses are still under study, this first model can help predict how much MPA molecules can actually inhibit IMDPH in the cells.
References:
[1] Jeong H, Kaplan B. Therapeutic Monitoring of Mycophenolate Mofetil. Clin J Am Soc Nephrol. 2007;2:184–91.
[2] Hest RM van, Mathot RAA, Pescovitz MD, Gordon R, Mamelok RD, Gelder T van. Explaining Variability in Mycophenolic Acid Exposure to Optimize Mycophenolate Mofetil Dosing: A Population Pharmacokinetic Meta-Analysis of Mycophenolic Acid in Renal Transplant Recipients. J Am Soc Nephrol. 2006;17:871–80.
[3] Pawinski T, Durlik M, Szlaska I, Urbanowicz A, Majchrnak J, Gralak B. Comparison of mycophenolic acid pharmacokinetic parameters in kidney transplant patients within the first 3 months post-transplant. J Clin Pharm Ther. 2006;31:27–34.
Reference: PAGE 27 (2018) Abstr 8704 [www.page-meeting.org/?abstract=8704]
Poster: Drug/Disease Modelling - Other Topics