Tacrolimus population pharmacokinetics in paediatric kidney transplant patients
Shaun S Kumar, Xiaoxi Liu, Silvia Martinez, Jahidur Rashid, Kathleen Job, Alfred Balch, Joseph Rower, Joseph Sherbotie, Catherine M Sherwin
Dept. of Pediatrics, University of Utah, SLC, Utah, USA
Objectives: 1. To describe the pharmacokinetics (PK) of tacrolimus in paediatric kidney transplant recipients. 2. To determine the relationship between measures of tacrolimus exposure and renal function. 3. To determine if there were any differences in either the PK or pharmacodynamics (PD) of tacrolimus in brand versus generic formulations.
Methods: Data from 1999-2014 were extracted from the electronic medical records from Intermountain Healthcare network. Data were available on 95 paediatric patients with kidney transplant taking oral tacrolimus. Reliable data was available in 77 patients. Using the individual predicted PK parameters from the population model several exposure metrics were derived for each dosing interval including; Cmin, Cmax and partial AUCs (2, 4, 6, 8, 10, 12h). We investigated the relationship between tacrolimus exposure and creatinine clearance in the first 30 days post-transplantation, using a simple slope-intercept model as well as an Emax model.
Results: A total of 598 concentrations of tacrolimus were available for analysis. A one-compartment model described the final PK model, the significant covariates on clearance were haematocrit, body weight and post-transplant day. A total of 43 patients had data in the first 30 days post-transplant with a total of 470 creatinine concentrations available. The model that best described the relationship between tacrolimus exposure and creatinine clearance was an Emax model using a partial AUC of 4 hours. The significant covariates of this analysis were age, albumin, and formulation of the ED50 equivalent partial AUC 4h. The generic formulation (Sandoz) had a 35% increase partial AUC50 4h compared to the brand formulation.
Conclusions: In the present work we developed a population PK model for tacrolimus in pediatric kidney transplant recipients the significant covariates have been previously identified [1]. We also determined an exposure-response relationship between tacrolimus and creatinine clearance. This relationship was influenced by patients age and albumin concentrations. Furthermore, we show that there is a difference in the pharmacodynamic effects of tacrolimus when comparing the brand formulation to the generic.
References:
[1] Brooks et al. Population pharmacokinetic modelling and Bayesian estimation of tacrolimus exposure: Is this clincally useful for dosage prediction yet? Clin Pharmacokinet. 2016 May;55:1295-1335.