Abstract
PURPOSE: Critically ill patients exhibit significant pharmacokinetic alterations, necessitating population pharmacokinetic (PPK) modeling of piperacillin to optimize dosing regimens. This study aimed to develop a PPK model for piperacillin in critically ill patients from China and optimize dosing regimens based on model predictions. PATIENTS AND METHODS: A nonlinear mixed-effects modeling approach was applied to characterize piperacillin pharmacokinetics. Covariate analysis identified significant predictors of CL and V. Monte Carlo simulations assessed dosing regimens against pharmacodynamic targets. RESULTS: The final model estimated population typical CL and V as 6.48 L/h and 19 L, respectively. Estimated glomerular filtration rate and body weight significantly influenced CL, while plasma albumin affected V. Simulations revealed that continuous intravenous infusion achieved higher probability of target attainment (PTA) than intermittent dosing, particularly for pathogens with elevated MICs. Obesity and augmented renal clearance reduced PTA, necessitating dose escalation or more frequent administration. CONCLUSION: This study highlights the interplay between host pathophysiology, pathogen susceptibility, and drug exposure. Guided by the PPK model and susceptibility testing, tailored dosing strategies are crucial for optimizing therapeutic outcomes in critical populations.