Related Experiment Video
Updated: Jun 4, 2025

Multiplex Therapeutic Drug Monitoring by Isotope-dilution HPLC-MS/MS of Antibiotics in Critical Illnesses
Published on: August 30, 2018
A Pooled Pharmacokinetic Analysis for Piperacillin/Tazobactam Across Different Patient Populations: From Premature
Daming Kong1, Jason A Roberts2,3,4,5, Jeffrey Lipman5,6
1Department of Anesthesiology, University of Groningen, University Medical Center Groningen, P. O. Box 30001, 9700 RB, Groningen, The Netherlands.
Background And Objectives:
The pharmacokinetics (PK) of piperacillin/tazobactam (PIP/TAZ) is highly variable across different patient populations and there are controversies regarding non-linear elimination as well as the fraction unbound of PIP (fUNB_PIP). This has led to a plethora of subgroup-specific models, increasing the risk of misusing published models when optimising dosing regimens. In this study, we aimed to develop a single model to simultaneously describe the PK of PIP/TAZ in diverse patient populations and evaluate the current dosing recommendations by predicting the PK/pharmacodynamics (PD) target attainment throughout life.
Methods:
Population PK models were separately built for PIP and TAZ based on data from 13 studies in various patient populations. In the development of those single-drug models, postnatal age (PNA), postmenstrual age (PMA), total body weight (TBW), height, and serum creatinine (SCR) were tested as covariates. Subsequently, a combined population PK model was established and the correlations between the PK of PIP and TAZ were tested. Monte Carlo simulations were performed based on the final combined model to evaluate the current dosing recommendations.
Results:
The final combined model for PIP/TAZ consisted of four compartments (two for each drug), with covariates including TBW, PMA, and SCR. For a 70-kg, 35-year-old patient with SCR of 0.83 mg L-1, the PIP values for V1, CL, V2 and Q2 were 10.4 L, 10.6 L h-1, 11.6 L and 15.2 L h-1, respectively, and the TAZ values were 10.5 L, 9.58 L h-1, 13.7 L and 16.8 L h-1, respectively. The CL for both drugs show maturation in early life, reaching 50% at 54.2 weeks PMA. With advancing age, CL of TAZ declines to 50% at 61.6 years PMA, whereas CL of PIP declines more slowly, reaching 50% at 89.1 years PMA. The fUNB_PIP was estimated as 64.5% and non-linear elimination was not supported by our data. The simulation results indicated considerable differences in PK/PD target attainment for different patient populations under current recommended dosing regimens.
Conclusions:
We developed a combined population PK model for PIP/TAZ across a broad range of patients covering the extremes of patient characteristics. This model can be used as a robust a priori model for Bayesian forecasting to achieve individualised dosing. The simulations indicate that adjustments based on the allometric theory as well as maturation and decline of CL of PIP may help the current dosing recommendations to provide consistent target attainment across patient populations.
More Related Videos
09:17A Robust Pneumonia Model in Immunocompetent Rodents to Evaluate Antibacterial Efficacy against S. pneumoniae, H. influenzae, K. pneumoniae, P. aeruginosa or A. baumannii
Published on: January 2, 2017
06:08Evaluation of Drug Sorption to PVC- and Non-PVC-based Tubes in Administration Sets Using a Pump
Published on: March 11, 2017
Related Concept Videos
Analysis of Population Pharmacokinetic Data
Noncompartmental Analysis: Miscellaneous Pharmacokinetic Parameters
One key aspect of the noncompartmental approach is determining a drug's total clearance. This can be done by dividing the drug dose by the area under the concentration-time curve from zero to infinity. The area under the concentration-time curve represents the drug's...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
Nonlinear Pharmacokinetics: Dependence of Elimination Half-Life and Dose Clearance
A study on guinea pigs examined the...