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Background: Various population pharmacokinetic models have been developed todescribe the pharmacokinetics of tacrolimus in adult liver transplantation.However, their extrapolated predictive performance remains unclear in clinicalpractice. The purpose of this study was to predict concentrations using aselected literature model and to improve these predictions by tweaking themodel with a subset of the target population.Methods: A literature review wasconducted to select an adequate population pharmacokinetic model (L).Pharmacokinetic data from therapeutic drug monitoring of tacrolimus inliver-transplanted adults were retrospectively collected. A subset of thesedata (70%) was exploited to tweak the L-model using the PRIOR subroutine of theNONMEM software, with 2 strategies to weight the prior information: fullinformative (F) and optimized (O). An external evaluation was performed on theremaining data; bias and imprecision were evaluated for predictions a prioriand Bayesian forecasting.Results: Seventy-nine patients (851 concentrations)were enrolled in the study. The predictive performance of L-model wasinsufficient for a priori predictions, whereas it was acceptable with Bayesianforecasting, from the third prediction (ie, with $\ge$2 previously observedconcentrations), corresponding to 1 week after transplantation. Overall, thetweaked models showed a better predictive ability than the L-model. The bias ofa priori predictions was --41% with the literature model versus --28.5% and--8.73% with tweaked F and O models, respectively. The imprecision was 45.4%with the literature model versus 38.0% and 39.2% with tweaked F and O models,respectively. For Bayesian predictions, whatever the forecasting state, thetweaked models tend to obtain better results.Conclusions: A pharmacokineticmodel can be used, and to improve the predictive performance, tweaking theliterature model with the PRIOR approach allows to obtain better predictions.

Can We Predict Individual Concentrations of Tacrolimus After Liver  Transplantation? Application and Tweaking of a Published Population  Pharmacokinetic Model in Clinical Practice