OBJECTIVE To investigate the population pharmacokinetic factors significantly influencing voriconazole in hematologic malignancy patients with invasive fungal infections, and to optimize individualized dosing regimens.

METHODS A total of 135 voriconazole trough concentration measurements were retrospectively collected from 80 patients with hematologic malignancies and secondary invasive fungal infections who received intravenous voriconazole therapy in the Department of Hematology at the First Affiliated Hospital of Nanchang University between January 2021 and October 2024. Nonlinear mixed-effects modeling(NONMEM) was employed for model development and data analysis, with covariates incorporated into the model. A stepwise approach was used for covariate selection: forward inclusion was set at a significance level of ΔOFV>6.64(P<0.01), and backward elimination was set at ΔOFV>10.83(P<0.001). Following internal validation(including bootstrap and visual predictive checks) and independent external validation to assess model stability and predictive performance, the final model was established.

RESULTS A one-compartment pharmacokinetic model was established for intravenous administration in patients with hematologic malignancies and secondary invasive fungal infections. The final model demonstrated robust stability and satisfactory predictive performance through internal validation(bootstrap 1000 times, success rate 100%) and external validation(mean prediction error, MPE%=8.0%; mean absolute prediction error, MAPE%=14.7%), meeting the predefined acceptance criteria(MPE%≤±20%, MAPE%≤30%).The population pharmacokinetic parameters were estimated as follows: clearance(CL) was 2.61 L·h⁻¹(95% confidence interval: 2.06–3.76 L·h⁻¹), and volume of distribution(V) was 100.07 L(95% confidence interval: 36.26–190.26 L).Covariate analysis revealed that rs10912675 and alanine aminotransferase(ALT) significantly influenced the apparent volume of distribution(V), while white blood cell count(WBC) significantly affected the apparent clearance(CL).

CONCLUSION The final model demonstrated satisfactory stability and predictive performance, confirming that rs10912675, ALT, and WBC are the primary factors contributing to the pharmacokinetic variability of voriconazole. Rs10912675, alanine aminotransferase (ALT), and white blood cell count (WBC) can induce alterations in voriconazole pharmacokinetics. In patients with hematological malignancies complicated by invasive fungal infections, the narrow therapeutic index and pathophysiological heterogeneity necessitate the development of individualized dosing regimens.