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Population pharmacokinetics; Ceftriaxone; Critically ill patients; Renal function; Drug clearance; Dose adjustment; Pharmacokinetic variability; Therapeutic drug monitoring; Clinical dosing; Antibiotic therapy

Introduction

Ceftriaxone, a third-generation cephalosporin antibiotic, is frequently used in intensive care settings due to its broad-spectrum activity and favorable safety profile. However, critically ill patients often exhibit altered pharmacokinetics due to physiological changes such as fluid shifts, organ dysfunction, and variable renal function [1-5]. These factors can significantly impact drug clearance, volume of distribution, and half-life, complicating dosing decisions. Population pharmacokinetic (PopPK) modeling provides a robust approach to quantify variability and optimize ceftriaxone dosing in this complex patient group. This study utilizes PopPK modeling to evaluate how renal function influences ceftriaxone pharmacokinetics and to propose individualized dosing strategies [6-10].

Discussion

Data were collected from ICU patients with varying levels of renal function, and a nonlinear mixed-effects model was developed to describe ceftriaxone kinetics. Creatinine clearance (CrCl) was identified as a significant covariate influencing drug clearance. Patients with augmented renal clearance required higher doses to maintain therapeutic concentrations, while those with renal impairment needed dose reduction to prevent accumulation and toxicity. The model demonstrated good predictive performance and was externally validated. Simulations suggested optimal dosing regimens across renal function categories. Integration of PopPK models with bedside TDM can further enhance dosing precision. Challenges include accounting for dynamic changes in renal function and variability in fluid status. Nonetheless, PopPK modeling serves as a valuable tool in precision dosing and stewardship of antibiotics in the ICU.

Conclusion

Population pharmacokinetic modeling enables personalized ceftriaxone dosing in critically ill patients by incorporating renal function variability. This approach supports rational antibiotic use, minimizes toxicity, and maximizes clinical efficacy, especially in the high-risk ICU setting.

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