Population pharmacokinetics and Bayesian estimator of mycophenolic acid in children with idiopathic nephrotic syndrome

Abstract

Aims: To develop a population pharmacokinetic model for mycophenolic acid (MPA) in children with idiopathic nephrotic syndrome (INS) treated with mycophenolate mofetil (MMF), identify covariates that explain variability and determine the Bayesian estimator of the area under the concentration-time curve over 12 h (AUC(0-12)).

Methods: The pharmacokinetic model of MMF was described from 23 patients aged 7.4 +/- 3.9 years (range 2.9-14.9) using nonlinear mixed-effects modelling (NONMEM) software. A two-compartment model with lag-time and first-order absorption and elimination was developed. The final model was validated using visual predictive check. Bayesian estimator was validated using circular permutation method.

Results: The population pharmacokinetic parameters were apparent oral clearance 9.7 l h(-1), apparent central volume of distribution 22.3 l, apparent peripheral volume of distribution 250 l, inter-compartment clearance 18.8 l h(-1), absorption rate constant 5.16 h(-1), lag time 0.215 h. The covariate analysis identified body weight and serum albumin as individual factors influencing the apparent oral clearance. Accurate Bayesian estimation of AUC(0-12) was obtained using the combination of three MPA concentrations measured just before (T(0)), 1 and 4 h (T(1) and T(4)) after drug intake with a small error of 0.298 microg h(-1) ml(-1) between estimated and reference AUC(0-12).

Conclusions: The population pharmacokinetic model of MPA was developed in children with INS. A three-point (T(0), T(1) and T(4)h) Bayesian estimator of AUC(0-12) was developed and might be used to investigate the relation between MPA pharmacokinetic and pharmacodynamics in children with INS and determine if there is any indication to monitor MPA exposure in order to improve patient outcome based on individual AUC-controlled MMF dosing.

Figure 1

Goodness-of-fit plots for the final population pharmacokinetic model of mycophenolic acid (MPA). (a) Weighted residuals (WRES) vs. model-predicted concentration (PRED). (b) Weighted residuals (WRES) vs. time

Figure 2

Visual predictive check of the model. The 50th percentile concentration is shown by a solid line and the 5th–95th percentiles simulated from the final model are encompassed by the broken lines

Figure 3

Bland and Altman plot of difference against mean for mycophenolic acid (MPA) AUC_0–12 determined by Bayesian estimation (‘MAXEVAL = 0’ and ‘Posthoc’ in the $ESTIMATION step) using all the available time points and Bayesian estimator (T₀, T₁ and T₄ after drug intake). Difference (•); Mean Diff. ± 2SD (—)