A double absorption-phase model adequately describes mycophenolic acid plasma profiles in de novo renal transplant recipients given oral mycophenolate mofetil

Mycophenolic acid (MPA) shows complex plasma concentration-time profiles, particularly in the immediate (first month) post-transplantation phase for which no relevant pharmacokinetic model has been proposed thus far. The aim of this study was to develop a model to accurately describe the time profile of plasma MPA concentrations after oral administration of mycophenolate mofetil in adult kidney transplant patients, in any post-transplantation period. Full interdose pharmacokinetic profiles were collected in 45 adult renal transplant patients who were orally administered mycophenolate mofetil and ciclosporin; 25 patients were de novo transplant patients for whom individual pharmacokinetics were assessed at three post-transplantation periods (days 3, 7 and 30) and 20 patients were stable transplant patients (>3 months post-transplantation). MPA was determined in plasma by liquid chromatography-mass spectrometry. Models combining a single- or double-input (described as single or double gamma distributions) with one- or two-compartments were developed using in-house software and fitted to the individual profiles by nonlinear regression. Visual inspection of the pharmacokinetic profiles showed highly variable absorption profiles and secondary peaks of various intensity. The pharmacokinetic models including a double gamma distribution best fitted these various profiles in the immediate post-transplantation period (mean bias and precision of -0.92% and 20.19%; -1.5% and 18.02%, on day 7 and day 30, respectively), while in the stable post-grafting phase (beyond 3 months), the single- and double-absorption models performed similarly (mean bias and precision of -3.37% and 17.64%; -3.12% and 18.44%, on day 7 and day 30, respectively). The proposed pharmacokinetic models adequately describe the concentration-time profiles of MPA in renal transplant patients and could be helpful in the development of tools for MPA monitoring.