Population Pharmacokinetic Model of Plasma and Cellular Mycophenolic Acid in Kidney Transplant Patients from the CIMTRE Study.

BACKGROUND AND OBJECTIVE: Mycophenolate mofetil is widely used in kidney transplant recipients. Mycophenolate mofetil is hydrolysed by blood esterases to mycophenolic acid (MPA), the active drug. Although MPA therapeutic drug monitoring has been recommended to optimise the treatment efficacy by the area under the plasma concentration vs time curve, little is known regarding MPA concentrations in peripheral blood mononuclear cells, where MPA inhibits inosine monophosphate dehydrogenase. This study aimed to build a pharmacokinetic model using a population approach to describe MPA total and unbound concentrations in plasma and into peripheral blood mononuclear cells in 78 adult kidney transplant recipients receiving mycophenolate mofetil therapy combined with tacrolimus and prednisone. METHODS: Total and unbound plasma concentrations and peripheral blood mononuclear cell concentrations were assayed. A three-compartment model, two for plasma MPA and one for peripheral blood mononuclear cell MPA, with a zero-order absorption and a first-order elimination was used to describe the data. RESULTS: Mycophenolic acid average concentrations in peripheral blood mononuclear cells were well above half-maximal effective concentration for inosine monophosphate dehydrogenase and no relationship was found with the occurrence of graft rejection. Three covariates affected unbound and intracellular MPA pharmacokinetics: creatinine clearance, which has an effect on unbound MPA clearance, human serum albumin, which influences fraction unbound MPA and the ABCB1 3435 C>T (rs1045642) genetic polymorphism, which has an effect on MPA efflux transport from peripheral blood mononuclear cells. CONCLUSION: This population pharmacokinetic model demonstrated the intracellular accumulation of MPA, the efflux of MPA out of the cells being dependent on P-glycoprotein transporters. Nevertheless, further studies are warranted to investigate the relevance of MPA concentrations in peripheral blood mononuclear cells to dosing regimen optimisation.

Bayesian Individual Dynamic Predictions with Uncertainty of Longitudinal Biomarkers and Risks of Survival Events in a Joint Modelling Framework: a Comparison Between Stan, Monolix, and NONMEM.

Given a joint model and its parameters, Bayesian individual dynamic prediction (IDP) of biomarkers and risk of event can be performed for new patients at different landmark times using observed biomarker values. The aim of the present study was to compare IDP, with uncertainty, using Stan 2.18, Monolix 2018R2 and NONMEM 7.4. Simulations of biomarker and survival were performed using a nonlinear joint model of prostate-specific antigen (PSA) kinetics and survival in metastatic prostate cancer. Several scenarios were evaluated, according to the strength of the association between PSA and survival. For various landmark times, a posteriori distribution of PSA kinetic individual parameters was estimated, given individual observations, with each software. Samples of individual parameters were drawn from the posterior distribution. Bias and imprecision of individual parameters as well as coverage of 95% credibility interval for PSA and risk of death were evaluated. All software performed equally well with small biases on individual parameters. Imprecision on individual parameters was comparable across software and showed marked improvements with increasing landmark time. In terms of coverage, results were also comparable and all software were able to well predict PSA kinetics and survival. As for computing time, Stan was faster than Monolix and NONMEM to obtain individual parameters. Stan 2.18, Monolix 2018R2 and NONMEM 7.4 are able to characterize IDP of biomarkers and risk of event in a nonlinear joint modelling framework with correct uncertainty and hence could be used in the context of individualized medicine.