Astrid Heida (1), Nynke Jager (1), Rob Aarnoutse(1), Brenda de Winter(2), Huib de Jong(3), Ron Keizer(4), Elisabeth Cornelissen(5), Rob ter Heine(1)
(1) Department of Pharmacy, Radboud Institute for Medical Innovation, Radboud university medical center Nijmegen, Netherlands (2) Department of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands. (3) The ErasmusMC Transplant Institute, University Medical Center, Rotterdam, The Netherlands (4) Insight Rx, San Francisco, California, USA (5) Department of Pediatric Nephrology, Radboud university medical center, Amalia Children's Hospital, Nijmegen, The Netherlands (4) Insight Rx, San Francisco, California, USA (5) Department of Pediatric Nephrology, Radboud university medical center, Amalia Children's Hospital, Nijmegen, The Netherlands
Introduction:
Mycophenolic acid (MPA), the active compound of the prodrug mycophenolate mofetil (MMF), is a pharmacotherapeutic cornerstone to prevent allograft rejection in pediatric renal transplant patients. Its pharmacokinetics (PK) are characterized by a large inter- and intra-individual variability, particularly in the early post-transplant period [1]. In clinical practice, therapeutic drug monitoring (TDM) is recommended to ensure that exposure remains within the defined therapeutic window of an AUC0-12h 30–60 mg h L−1. The approved dose of MMF for pediatric patients is 1200 mg m-2 day-1 in two divided doses [2-4]. A more personalized dosing regimen may result in better pharmacokinetic target attainment early in treatment. Integrating factors that influence MPA exposure might help to predict the optimal MPA starting dose for the individual patient.
Objectives:
We aimed to develop and validate a population pharmacokinetic model of mycophenolic acid (MPA) in pediatric renal transplant patients to optimize MPA dosing, both empiric dosing as well as TDM based.
Methods:
Data were collected retrospectively from pediatric renal transplant recipients at the Radboudumc, Nijmegen (The Netherlands). Pharmacokinetic model-building and model-validation analyses were performed using NONMEM. To account for changes in PK as result of body size, all volume and flow parameters were allometrically scaled to a total body weight of 70 kg[5]. The allometric coefficients were fixed at 0.75 for flow parameters and 1 for volume parameters and, consequently, at -0.25 for rate constants. We externally evaluated the final model using data from another academic hospital in The Netherlands. The final model was used to determine an weight and covariate based starting dose. The performance of this improved dosing regimen to reach therapeutic exposure was then compared to the licensed dosing regimen of 1200 mg m-2 in a simulated pediatric patient population.
Results:
Thirty patients were included for analysis. Median age of the patients was 13 years (range 4 to 18), median weight was 38.5 kg (range 12.9 to 79.9) and median albumin level was 34 g/L (range 24 to 42). A two-compartment model with Erlang type absorption best described the data. Albumin was included as a covariate, as it significantly improved the model (ΔOFV=-15.29, p<0.05). The final population PK parameter estimates were Ktr (1.48 h−1, 95% CI: 1.15 – 1.84 ), CL/F (16.0 L h−1, 95% CI: 10.3 – 20.4), Vc/F (24.9 L 95% CI: 93.0 – 6.71E25), Vp/F (1590 L, 95% CI: 651 – 2994 ), and Q/F (36.2 L h−1 95% CI: 9.63 – 74.7 ). The PK model performed adequately in the external patient population. An optimized empirical dose scheme was developed based on weight and albumin. Patients with a higher albumin level should be given a lower dose of MMF. In the simulated patient population, 35.6% achieved the target AUC when on the licensed dosing regimen, while on optimized dose, 47.8% achieved the target AUC.
Conclusions:
We have successfully developed a pharmacokinetic model and verified this model using an external dataset. The optimized empirical dosing regimen based on body weight and serum albumin could result in better target attainment early in treatment. It can be used in combination with model-informed follow-up dosing to further individualize the dosing of mycophenolate mofetil.
References:
[1] Rong Y, Jun H, Kiang TKL. Population pharmacokinetics of mycophenolic acid in paediatric patients. Br J Clin Pharmacol. 2021;87(4):1730-57.
[2] Weber LT, Shipkova M, Lamersdorf T, Niedmann PD, Wiesel M, Mandelbaum A, et al. Pharmacokinetics of mycophenolic acid (MPA) and determinants of MPA free fraction in pediatric and adult renal transplant recipients. German Study group on Mycophenolate Mofetil Therapy in Pediatric Renal Transplant Recipients. Journal of the American Society of Nephrology. 1998;9(8):1511-20.
[3] Ettenger R, Sarwal MM. Mycophenolate Mofetil in Pediatric Renal Transplantation. Transplantation. 2005;80(2S):S201-S10.
[4] Roche. Summary of Product Characteristics (SPC) Cellcept: EMA; [Available from: https://www.ema.europa.eu/en/documents/product-information/cellcept-epar-product-information_en.pdf
[5] Anderson BJ, Holford NHG. Tips and traps analyzing pediatric PK data. Pediatric Anesthesia. 2011;21(3):222-37.
Reference: PAGE 32 (2024) Abstr 10775 [www.page-meeting.org/?abstract=10775]
Poster: Clinical Applications