The aim of this study was to develop maximum a posteriori probability (MAP) Bayesian estimators of mycophenolic acid (MPA) pharmacokinetics (PK) capable of accurately estimating the MPA interdose AUC in renal transplant patients using a limited number of blood samples. The individual MPA plasma concentration-time profiles of 44 adult kidney transplant recipients were retrospectively studied: in 24 de novo transplant patients, 2 profiles were obtained on day 7 and day 30 after transplantation, and in 20 stable transplant patients, 1 profile was obtained in the stable period (>3 months). MPA was assayed by liquid chromatography-mass spectrometry. Concentration data were fitted using previously designed PK models, including 1 or 2Gamma-distribution to describe the absorption rate. MAP-Bayesian estimations were performed using an in-house program. For each posttransplantation period, the limited sampling strategies (LSS) providing either the best determination coefficient or the lowest bias for AUC estimates with respect to trapezoidal AUCs were selected and compared with respect to the percentage of "clinically acceptable" AUC estimates (ie, within -20% to +20% of the true value) they yielded. A common LSS (blood samples collected at T20 min, T1 h, and T3 h postdosing), convenient for all 3 periods, was also selected and validated: bias (RMSE%) values were -5.7% (20.5%), -8.2% (14.4%), and +0.4% (12.0%) on D7, D30, and for >M3 with respect to the reference values obtained using the trapezoidal rule, respectively. For the first time, MAP-Bayesian estimators of MPA systemic exposure at different posttransplantation periods (early as well as later periods) could be designed. They have since been used for MPA dose adaptation in concentration-controlled studies as well as for MPA therapeutic drug monitoring in clinical practice.