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Objectives: Patients with hematological malignancies are prone to invasive fungal disease due to long-term chemotherapy or radiotherapy. Voriconazole is a second-generation triazole broad-spectrum antibiotic used to prevent or treat invasive fungal infections. Many population pharmacokinetic (pop PK) models have been published for voriconazole, and various diagnostic methods are available to validate the performance of these pop PK models. However, most of the published models have not been strictly evaluated externally. The purpose of this study is to evaluate these models externally and assess their predictive capabilities. Methods: The external dataset consists of adults receiving voriconazole treatment at Fujian Medical University Union Hospital. We re-established the published models based on their final estimated values in the literature and used our external dataset for initial screening. Each model was evaluated based on the following outcomes: prediction-based diagnostics, prediction- and variability-corrected visual predictive check (pvcVPC), normalized prediction distribution errors (NPDE), and Bayesian simulation results with one to two prior observations. Results: A total of 237 samples from 166 patients were collected as an external dataset. After screening, six candidate models suitable for the external dataset were finally obtained for comparison. Among the models, none demonstrated excellent predictive performance. Bayesian simulation shows that all models' prediction precision and accuracy were significantly improved when one or two prior concentrations were given. Conclusions: The published pop PK models of voriconazole have significant differences in prediction performance, and none of the models could perfectly predict the concentrations of voriconazole for our data. Therefore, extensive evaluation should precede the adoption of any model in clinical practice. [ABSTRACT FROM AUTHOR]

Busulfan is a bifunctional alkylating agent that is widely used before hematopoietic stem cell transplantation (HSCT), in combination with other chemotherapeutic drugs. As of 2020, there is no population pharmacokinetic (popPK) model for busulfan in Chinese pediatric patients. A systemic external evaluation of 11 published popPK models was conducted in Chinese pediatric patients undergoing HSCT. Forty pediatric patients were enrolled in this study, with a total of 183 blood concentrations. The relative prediction error (PE%), median PE%, median absolute PE%, and percentage of PE% within ±20% and ±30% were calculated in prediction‐based diagnostics. Simulation‐based diagnostics were conducted through a prediction‐ and variability‐corrected visual predictive check and the normalized prediction distribution error. The relative individual prediction error was calculated using Bayesian forecasting with 1 to 3 concentration points. The 1‐compartment open linear popPK model, which was built by Su‐jin Rhee et al (model H), incorporating the patient's body surface area, age, dosing day, and aspartate aminotransferase as significant covariates had preferable predictability than other popPK models. In prediction‐based diagnostics, the median PE%, percentage of PE% within ±20%, and percentage of PE% within ±30% of model H were 8.48%, 45.35%, and 59.56%, respectively. The normalized prediction distribution error of model H showed that it followed the normal distribution. Based on Bayesian forecasting, model H showed good predictive performance. Thus, model H was the most appropriate model that can be used clinically for individualized dosage adjustments in Chinese pediatric HSCT patients. [ABSTRACT FROM AUTHOR]