ArticleFrontiers in pharmacology2022
External evaluation of published population pharmacokinetic models of posaconazole.
Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Evaluation of a model averaging algorithm for model-informed precision dosing in the context of parameter misspecifications.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- Leveraging Model-Informed Drug Development to Predict Asciminib Efficacy in Second-Line Treatment of Chronic Myeloid Leukemia in Chronic Phase.Clinical pharmacokinetics · 2026Article
- Toward adaptive therapeutic timing: integration of mechanistic pharmacology and artificial intelligence in precision dosing.Frontiers in pharmacology · 2026Review
- Guidance for External Evaluation and Selection of Population Pharmacokinetic Models for Precision Dosing.Clinical pharmacokinetics · 2026Review
- Does Sample Size, Sampling Strategy, or Handling of Concentrations Below the Lower Limit of Quantification Matter When Externally Evaluating Population Pharmacokinetic Models?European journal of drug metabolism and pharmacokinetics · 2024Article
- Personalized Antifungal Therapy Through Model-Informed Precision Dosing of Posaconazole.Clinical pharmacokinetics · 2024Article
- External validation of population pharmacokinetic models of vancomycin in postoperative neurosurgical patients.European journal of clinical pharmacology · 2023Article
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Authors and funding
10 authors.
Funding
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Abstract
Population pharmacokinetic (PopPK) models of posaconazole have been established to promote the precision dosing. However, the performance of these models extrapolated to other centers has not been evaluated. This study aimed to conduct an external evaluation of published posaconazole PopPK models to evaluate their predictive performance. Posaconazole PopPK models screened from the PubMed and MEDLINE databases were evaluated using an external dataset of 213 trough concentration samples collected from 97 patients. Their predictive performance was evaluated by prediction-based diagnosis (prediction error), simulation-based diagnosis (visual predictive check), and Bayesian forecasting. In addition, external cohorts with and without proton pump inhibitor were used to evaluate the models respectively. Ten models suitable for the external dataset were finally included into the study. In prediction-based diagnostics, none of the models met pre-determined criteria for predictive indexes. Only M4, M6, and M10 demonstrated favorable simulations in visual predictive check. The prediction performance of M5, M7, M8, and M9 evaluated using the cohort without proton pump inhibitor showed a significant improvement compared to that evaluated using the whole cohort. Consistent with our expectations, Bayesian forecasting significantly improved the predictive per-formance of the models with two or three prior observations. In general, the applicability of these published posaconazole PopPK models extrapolated to our center was unsatisfactory. Prospective studies combined with therapeutic drug monitoring are needed to establish a PopPK model for posaconazole in the Chinese population to promote individualized dosing.
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