Individualization of piperacillin dosing for critically ill patients: dosing software to optimize antimicrobial...

Area of Science:

• Pharmacokinetics and Pharmacodynamics
• Critical Care Medicine
• Infectious Diseases

Background:

• Piperacillin-tazobactam is crucial for treating infections in critically ill patients.
• Significant pharmacokinetic variability necessitates individualized dosing strategies.
• Bayesian estimation offers a method for optimizing drug regimens based on individual patient data.

Purpose of the Study:

• To develop a population pharmacokinetic (PK) model for piperacillin in critically ill patients.
• To evaluate the performance of this PK model within the BestDose software for piperacillin regimen optimization.
• To assess the precision of dose predictions based on the number of observed piperacillin concentrations.

Main Methods:

• Fitted linear, Michaelis-Menten, and parallel linear/MM models to data from 146 critically ill patients.
• Used creatinine clearance and weight as covariates in the PK model.
• Integrated the population model with observed piperacillin concentrations into the BestDose software for 8 additional patients.

Main Results:

• A linear clearance model incorporating creatinine clearance and weight best described piperacillin PK.
• The BestDose software accurately predicted piperacillin dosages (mean 4.02 g vs. 4.00 g administered) with at least two concentration measurements.
• Observed versus predicted piperacillin concentrations showed strong correlation (r² > 0.89) after 24 hours.

Conclusions:

• Individualized piperacillin dosing to achieve target serum concentrations is feasible in critically ill patients.
• The developed population PK model and BestDose software show promise for optimizing piperacillin therapy.
• Further clinical validation of the dose optimization software is warranted.