External validation of population pharmacokinetic models of tacrolimus in Thai adult liver transplant recipients

Abstract

Abstract Objective Several population pharmacokinetic models of tacrolimus in liver transplant patients were built and the predictability was evaluated in their own setting. However, the extrapolation in the prediction was unclear. This study aimed to evaluate the predictive performance of published tacrolimus models in adult liver transplant recipients using data from the Thai population as an external dataset. Methods The selected published models were systematically searched and evaluated for their quality. The external dataset of patients who underwent the first liver transplant and received immediate-release tacrolimus was used to evaluate the predictive performance of each selected model. Trough concentrations between 3 and 6 months were retrospectively collected to evaluate the predictability of each model using prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. Results Sixty-seven patients with 360 trough concentrations and 8 selected published models were included in this study. None of the models met the predictive precision criteria in prediction-based diagnostics. Meanwhile, there were four published population pharmacokinetic models that showed a normal distribution in NPDE testing. Regarding Bayesian forecasting, all models improved their forecasts with at least one prior information data point. Conclusion Bayesian forecasting is more accurate and precise than other testing methods for predicting drug levels. However, no model provides satisfactory predictive performance that meets all the testing criteria when generalized to Thai liver transplant patients. Therefore, appropriate population pharmacokinetic models for the Thai population should be developed in the future.