CYP3A5 genotype-based model to predict tacrolimus dosage in the early postoperative period after living donor liver transplantation
Received 17 August 2018
Accepted for publication 6 October 2018
Published 25 October 2018 Volume 2018:14 Pages 2119—2126
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 2
Editor who approved publication: Professor Garry Walsh
Eunhee Ji,1,* Myeong Gyu Kim,2,* Jung Mi Oh3
1College of Pharmacy and Research Institute of Pharmaceutical Sciences, Gachon University, Incheon 21936, Republic of Korea; 2Graduate School of Clinical Pharmacy, CHA University, Pocheon 11160, Republic of Korea; 3College of Pharmacy and Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul 08826, Republic of Korea
*These authors contributed equally to this work
Purpose: Liver transplantation is the treatment of choice for patients with end-stage liver disease. Due to the between- and within-individual pharmacokinetic variability in tacrolimus, used to prevent rejection after transplantation, it is difficult to predict the dose needed achieve the target levels in the blood. This study aimed to construct a population pharmacokinetic model of tacrolimus dosage prediction for therapeutic drug monitoring in clinical settings for Korean adult patients receiving living donor liver transplantation (LDLT).
Methods: A total of 58 Korean adult patients receiving LDLT with tacrolimus administration were enrolled. Demographic, clinical, and CYP3A5*1/*3 polymorphism data were collected. Population pharmacokinetic modeling of tacrolimus during the first 14 days after transplantation was performed using NONMEM program. Parameters were estimated by the first-order conditional estimation with interaction method. The internal validation of the final model was assessed by the bootstrap and visual predictive check methods using 500 samples from the original data.
Results: One-compartmental model was selected as a base model. After the stepwise covariate model building process, postoperative day (POD) and combinational CYP3A5 genotype of the recipient and donor were incorporated into clearance (CL/F). The estimated typical values of CL/F and volume of distribution (V/F) were 6.33 L/h and 465 L, respectively. The final model was CL/F =6.33× POD0.257×2.314 (if CYP3A5 expresser recipient grafted from CYP3A5 expresser donor) ×1.523 (if CYP3A5 expresser recipient grafted from CYP3A5 nonexpresser donor) and V/F =465× POD0.322.
Conclusion: A population pharmacokinetic model for tacrolimus was established successfully in Korean adult patients receiving LDLT. This model is expected to contribute to improving patient outcomes by optimizing tacrolimus dose adjustment for liver transplant patients.
Keywords: tacrolimus, dosage prediction, living donor liver transplantation, CYP3A5, population pharmacokinetics, nonlinear mixed-effects modeling
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