Background: Daptomycin is an important antibiotic against multidrug-resistant Gram-positive infections, but its wide interindividual variability and narrow therapeutic window pose challenges for optimal dosing. Population pharmacokinetic (PopPK) models provide a quantitative framework for precision dosing, yet a systematic evaluation of existing models and their clinical application method remains lacking. Methods: Model structures, demographic characteristics, and covariate effects were systematically summarized from previously published papers. Predictive performance was compared through simulations in virtual populations with varying renal function. Monte Carlo simulations were performed to evaluate the probability of target attainment (PTA; AUC24 h /MIC ≥ 666) and the probability of toxicity (Cmin ≥ 24.3 mg/L). Furthermore, an open-access precision dosing tool was developed based on maximum a posteriori Bayesian estimation using representative model structure and parameters. Results: Eighteen PopPK studies were included in this analysis. Renal function was the most frequently identified covariate influencing clearance. Model comparisons revealed variability in predicting exposure and PTA. Simulations indicated that patients with impaired renal function face a higher risk of exceeding the toxicity threshold, even at moderate doses. The developed Shiny-based tool enables real-time estimation of AUC and Cmin, integration of therapeutic drug monitoring data, and individualized dose adjustment. Conclusion: This study provides a comprehensive evaluation of daptomycin PopPK models and translates these findings into a practical precision dosing tool. This work enhances understanding of interindividual variability of daptomycin and offers clinicians a scientifically grounded resource to optimize daptomycin therapy in diverse patient populations. Keywords: population pharmacokinetic, precision dosing, daptomycin, renal impairment
Xie et al. (Sun,) studied this question.