Population pharmacokinetics and Bayesian estimation of mycophenolate mofetil in patients with autoimmune hepatitis

Aims Mycophenolate mofetil (MMF) is the most widely used second‐line agent in autoimmune hepatitis (AIH). Individual dose adjustment of MMF may avoid adverse outcomes while maximizing efficacy. The aim of the present study was to develop population pharmacokinetic (popPK) models and maximum a posteriori Bayesian estimators (MAP‐BEs) to estimate mycophenolic acid interdose area under the curve in AIH patients administered MMF using nonlinear mixed effect modelling. Methods We analysed 50 mycophenolic acid PK profiles from 34 different patients, together with some demographic, clinical, and laboratory test data. The median number of plasma samples per profile, immediately preceding and following the morning MMF dose, was 7. PopPK modelling was performed using parametric, top‐down, nonlinear mixed effect modelling with NONMEM 7.3. MAP‐BEs were developed based on the best popPK model and the best limited sampling strategy selected among several. Results The pharmacokinetic data were best described by a 2‐compartment model, Erlang distribution to describe the absorption phase, and a proportional error. The mean (relative standard error) of popPK parameter estimates of clearance, intercompartmental clearance, central volume and absorption rate with the final model were: 21.6 L h −1 (11%), 22.7 L h −1 (19%), 35.9 L (21%) and 8.7 h −1 (9%), respectively. The peripheral volume was fixed to 300 L. The best MAP‐BE relied on the limited sampling strategy at 0.33, 1 and 3 hours after MMF dose administration and was very accurate (bias = 5.6%) and precise (root mean squared prediction error <20%). Conclusion The precise and accurate Bayesian estimator developed in this study for AIH patients on MMF can be used to improve the therapeutic management of these patients.