Three methods to optimise polymyxin B dosing using estimated AUC after first dose: validation with the data generated...

Area of Science:

• Pharmacokinetics and Pharmacodynamics
• Clinical Pharmacology
• Drug Dosing Optimization

Background:

• Polymyxin B dosing requires precise therapeutic drug monitoring.
• Estimating steady-state AUC (AUC_SS,24h) from limited data is clinically relevant.
• Existing methods for AUC estimation may lack accuracy with sparse sampling.

Purpose of the Study:

• To develop and validate methods for estimating polymyxin B AUC_SS,24h using limited post-first-dose concentrations.
• To compare the accuracy of two-point, three-point, and four-point PK approaches.
• To assess the utility of these methods in patients with normal and impaired renal function.

Main Methods:

• Monte Carlo simulations using a population PK model for 1000 virtual patients.
• Estimation of AUC_SS,24h via two-point, three-point, and four-point PK methods.
• Comparison of estimated AUC with AUC calculated by the linear-trapezoidal formula.

Main Results:

• The four-point PK approach demonstrated the lowest mean bias (-0.48% in normal renal function, -0.28% in renal impairment).
• The two-point approach showed the highest mean bias (-8.73% and -11.15%, respectively).
• Sampling time shifts minimally impacted the four-point method's accuracy compared to others.

Conclusions:

• The proposed three methods, especially the four-point approach, accurately estimate polymyxin B AUC_SS,24h.
• Excel calculators based on these methods can aid in optimizing polymyxin B dosing.
• Accurate AUC estimation supports therapeutic drug monitoring and improved patient outcomes.