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European Journal of Clinical Pharmacology

, Volume 74, Issue 11, pp 1437–1447 | Cite as

Evaluating tacrolimus pharmacokinetic models in adult renal transplant recipients with different CYP3A5 genotypes

  • Can Hu
  • Wen-jun Yin
  • Dai-yang Li
  • Jun-jie Ding
  • Ling-yun Zhou
  • Jiang-lin Wang
  • Rong-rong Ma
  • Kun Liu
  • Ge Zhou
  • Xiao-cong Zuo
Pharmacokinetics and Disposition
  • 189 Downloads

Abstract

Purpose

Numerous studies have been conducted on the population pharmacokinetics of tacrolimus in adult renal transplant recipients. It has been reported that the cytochrome P450 (CYP) 3A5 genotype is an important cause of variability in tacrolimus pharmacokinetics. However, the predictive performance of population pharmacokinetic (PK) models of tacrolimus should be evaluated prior to their implementation in clinical practice. The aim of the study reported here was to test the predictive performance of these published PK models of tacrolimus.

Methods

A literature search of the PubMed and Web of Science databases ultimately led to the inclusion of eight one-compartment models in our analysis. We collected a total of 1715 trough concentrations from 174 patients. Predictive performance was assessed based on visual and numerical comparison bias and imprecision and by the use of simulation-based diagnostics and Bayesian forecasting.

Results

Of the eight one-compartment models assessed, seven showed better predictive performance in CYP3A5 extensive metabolizers in terms of bias and imprecision. Results of the simulation-based diagnostics also supported the findings. The model based on a Chinese population in 2013 (model 3) showed the best and most stable predictive performance in all the tests and was more informative in CYP3A5 extensive metabolizers. As expected, Bayesian forecasting improved model predictability. Diversity among models and between different CYP3A5 genotypes of the same model was also narrowed by Bayesian forecasting.

Conclusions

Based on our results, we recommend using model 3 in CYP3A5 extensive metabolizers in clinical practice. All models had a poor predictive performance in CYP3A5 poor metabolizers, and they should be used with caution in this patient population. However, Bayesian forecasting improved the predictability and reduced differences, and thus the models could be applied in this latter patient population for the design of maintenance dose.

Keywords

Population pharmacokinetics Tacrolimus Evaluation Renal transplant 

Notes

Author’s contributions

CH, LYZ, JLW, JJD and XCZ participated in study design. CH, RRM and XCZ performed the research. CH, KL and GZ collected and analysed data. HC, WJY, DYL, and XCZ wrote the paper.

Funding

This study was funded by the National Natural Science Foundation of China (81773822) and the New Xiangya Talent Project of the Third Xiangya Hospital of Central South University (No.20150218).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Ethical and regulatory approval was approved by the Ethical Committee of the Third Xiangya Hospital of Central South University (No. 2018-S225). All procedures in this study were carried out according to the 1964 Helsinki Declaration and its later amendments.

Supplementary material

228_2018_2521_MOESM1_ESM.docx (2.1 mb)
ESM 1 (DOCX 2201 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Pharmacy, The Third Xiangya HospitalCentral South UniversityChangshaPeople’s Republic of China
  2. 2.Department of PharmacyChildren’s Hospital of Fudan UniversityShanghaiPeople’s Republic of China
  3. 3.Department of PharmacyFirst Affiliated Hospital of Xinjiang Medical UniversityUrumqiPeople’s Republic of China
  4. 4.Center of Clinical Pharmacology, The Third Xiangya HospitalCentral South UniversityChangshaPeople’s Republic of China

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