PRELIMINARY RESULTS OF THE ADOPT TRIAL: TOTAL AND UNBOUND MYCOPHENOLIC ACID CONCENTRATION CHANGES BEFORE AND AFTER KIDNEY TRANSPLANTATION.

D METZ¹, NHOLFORD², J KAUSMAN¹, N CRANSWICK¹, A WALKER¹, F IERINO^3
1Royal Children’s Hospital, Parkville, Australia, ²University of Auckland, Auckland, New Zealand, ³St Vincent’s Hospital Melbourne, Fitzroy, Australia

Mycophenolic acid (MPA) underexposure in the immediate post-transplant period occurs in ~25% of kidney transplant recipients receiving tacrolimus. In high-risk candidates this is associated with over twice the rejection rate (23.9% versus 10.4%, p=0.012). Optimising mycophenolate dose based on a pre-transplant PK assessment could ameliorate this risk.
Aim: To describe the period effect – pre- to post-transplant – on MPA pharmacokinetics (PK), and the ability to predict post-transplant mycophenolate mofetil (MMF) dose requirement.
Methods: 45 kidney transplant recipients had PK profiles for total MPA (MPAt) and unbound MPA (MPAu) on steady-state dosing both pre- and post-transplant. MPA AUC was estimated using the log-linear trapezoid method over a 12 h period. Change in MPA exposure was tested using the Wilcoxon signed-rank test. After adjustment for median change in exposure, the precision of pre-transplant AUC to predict post-transplant AUC was tested by median absolute percentage prediction error (MAPE), and the proportion within 20% of the observed post-transplant AUC, equivalent to a range of 36mg/L*h to 54mg/L*h around an MPAt target of 45mg/L*h.
Results: Estimated MPA AUC (0-12) values were significantly higher pre-transplant for both MPAt (median 63.05mg/L*h versus 42.53mg/L*h, p<0.001) and MPAu AUC (1067.4mcg/L*h versus 520.9mcg/L*h, p=<0.00001). MAPE was 31.4% for MPAt and 42.9% for MPAu. Only 19.4% of MPAt and 33.3% of MPAu exposure predictions were within 20% of observed post-transplant predictions.
Conclusions: Exposure to both MPAt and MPAu was significantly higher pre- versus post kidney transplantation. Pre-transplant PK profile was not highly predictive using the trapezoidal method. This could be in part be due to this method calculating AUC. A model-based Bayesian prediction method may be more useful, with pharmacometric analysis of ADOPT data underway.

Biography:
Dr David Metz is a Paediatric Nephrologist and Clinical Pharmacologist based at the Royal Children’s Hospital in Melbourne. He is interested in quantitative pharmacology, and pharmacometric techniques to optimizing immunosuppression.