Population pharmacokinetic and pharmacogenetic analysis of tacrolimus in paediatric liver transplant patients

Authors

  • Mariam H. Abdel Jalil,

    1. Clinical and Practice Research Group, School of Pharmacy, Medical Biology Centre, Queen's University Belfast, Belfast, UK
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  • Ahmed F. Hawwa,

    1. Clinical and Practice Research Group, School of Pharmacy, Medical Biology Centre, Queen's University Belfast, Belfast, UK
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  • Patrick J. McKiernan,

    1. The Liver Unit, Birmingham Children's Hospital NHS Trust, Birmingham, UK
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  • Michael D. Shields,

    1. Institute of Clinical Research, School of Medicine, Queen's University Belfast, Belfast, UK
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  • James C. McElnay

    Corresponding author
    1. Clinical and Practice Research Group, School of Pharmacy, Medical Biology Centre, Queen's University Belfast, Belfast, UK
    • Correspondence

      Professor James C. McElnay PhD, FPSNI, FRPharmS, Clinical and Practice Research Group, School of Pharmacy, Medical Biology Centre, Queen's University Belfast, 97 Lisburn Road, Belfast BT9 7BL, UK.

      Tel.: +44 28 9097 5221

      Fax: +44 28 9024 7794

      E-mail: j.mcelnay@qub.ac.uk

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Abstract

Aims

To build a population pharmacokinetic model that describes the apparent clearance of tacrolimus and the potential demographic, clinical and genetically controlled factors that could lead to inter-patient pharmacokinetic variability within children following liver transplantation.

Methods

The present study retrospectively examined tacrolimus whole blood pre-dose concentrations (n = 628) of 43 children during their first year post-liver transplantation. Population pharmacokinetic analysis was performed using the non-linear mixed effects modelling program (nonmem) to determine the population mean parameter estimate of clearance and influential covariates.

Results

The final model identified time post-transplantation and CYP3A5*1 allele as influential covariates on tacrolimus apparent clearance according to the following equation:

display math

where TVCL is the typical value for apparent clearance, TPT is time post-transplantation in days and the CYP3A5 is 1 where *1 allele is present and 0 otherwise. The population estimate and inter-individual variability (%CV) of tacrolimus apparent clearance were found to be 0.977 l h−1 kg−1 (95% CI 0.958, 0.996) and 40.0%, respectively, while the residual variability between the observed and predicted concentrations was 35.4%.

Conclusion

Tacrolimus apparent clearance was influenced by time post-transplantation and CYP3A5 genotypes. The results of this study, once confirmed by a large scale prospective study, can be used in conjunction with therapeutic drug monitoring to recommend tacrolimus dose adjustments that take into account not only body weight but also genetic and time-related changes in tacrolimus clearance.

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