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.
Posaconazole is often used for the prophylaxis and treatment of invasive fungal infections (IFI). However, intra- and inter-individual differences and drug interactions affect the efficacy and safety of posaconazole. Precision dosing of posaconazole based on the population pharmacokinetic (PopPK) model may assist in making significant clinical decisions. This review aimed to comprehensively summarize the published PopPK models of posaconazole and analyze covariates that significantly influence posaconazole exposure. Articles published until May 2022 for PopPK analysis of posaconazole were searched in PubMed and EMBASE databases. Demographic characteristics, model characteristics, and results of PopPK analysis were extracted from the selected articles. In addition, the steady-state pharmacokinetic profiles of posaconazole were simulated at different covariate levels and dosing regimens. Out of the 13 studies included in our review, nine studies included adults, three included children, and one included both adults and children. All oral administration models were one-compartment models, and all intravenous administration models were two-compartment models. Body weight, proton pump inhibitors, and incidence of diarrhea were found to be important covariates. Clinically, the potential impact of factors such as patient physiopathologic characteristics and comorbid medications on posaconazole pharmacokinetics should be considered. Dose adjustment in combination with TDM or replacement with a tablet or intravenous formulation with higher exposure may be an effective way to ensure drug efficacy as well as to reduce fungal resistance. Meanwhile, published models require further external evaluation to examine extrapolation.
Aims: Posaconazole is often used for the prophylaxis and treatment of invasive fungal infections (IFI). However, intra- and inter-individual differences and drug interactions affect the efficacy and safety of posaconazole. Precision dosing of posaconazole based on the population pharmacokinetic (PopPK) model may assist in making significant clinical decisions. This review aimed to comprehensively summarize the published PopPK models of posaconazole and analyze covariates that significantly influence posaconazole exposure. Methods: Articles published until May 2022 for PopPK analysis of posaconazole were searched in PubMed and EMBASE databases. Demographic characteristics, model characteristics, and results of PopPK analysis were extracted from the selected articles. In addition, the steady-state pharmacokinetic profiles of posaconazole were simulated at different covariate levels and dosing regimens. Results: Out of the 13 studies included in our review, nine studies included adults, three included children, and one included both adults and children. All oral administration models were one-compartment models, and all intravenous administration models were two-compartment models. Body weight, proton pump inhibitors, and incidence of diarrhea were found to be important covariates. In addition, age, sex, total protein, rifampin, phenytoin, intake of nutritional supplements, levels of bilirubin and gamma-glutamyl transferase, and administration of chemotherapy also appeared as covariates in several PopPK models. Conclusion: Posaconazole exposure was found to be influenced by various factors such as the type of formulation, the incidence of diarrhea, body weight, and use of concomitant medications. It was concluded that routine therapeutic drug monitoring was required for dose adjustment and in promoting individualized dosing.
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