Limited sampling strategy using Bayesian estimation for estimating individual exposure of the once-daily prolonged-release formulation of tacrolimus in kidney transplant children

Background

A limited sampling strategy (LSS) for estimating the area under the curve (AUC) of the prolonged-release formulation of tacrolimus (tacrolimus^PR) is not available in pediatric patients, although the method is of real benefit to children. The objective of this study was to develop and validate a reliable and clinically applicable LSS using Bayesian estimation for estimating tacrolimus^PR AUC in pediatric kidney transplant patients

Methods

The original tacrolimus pharmacokinetic dataset consisted of 22 full profiles from 22 pediatric kidney transplant patients. The Bayesian estimation method was used to develop the LSS. External validation was performed in an independent validation group which consisted of 20 full pharmacokinetic profiles from 12 pediatric kidney transplant patients.

Results

Bayesian estimator using C_0h C_2h and C_3h gave the best predictive performance with a mean prediction error of 2.2 % in the external validation dataset. There was no correlation between the prediction error and age. The Bland–Altman analysis showed that the mean difference between the reference and Bayesian-estimated AUC_0-24 was 3.5 (95 % confidence interval ?3.5–10.5) ng h/mL

Conclusions

A reliable and clinically applicable LSS for estimating AUC_0–24 of tacrolimus^PR was determined and validated in children. The prediction was unbiased and precise. It can be used as a routine procedure to perform AUC-based tacrolimus^PR dosage optimization in pediatric renal transplant patients.