1. Ther Drug Monit. 2010 Dec;32(6):749-56.

Population pharmacokinetic modeling and optimal sampling strategy for Bayesian
estimation of amikacin exposure in critically ill septic patients.

Delattre IK, Musuamba FT, Nyberg J, Taccone FS, Laterre PF, Verbeeck RK, Jacobs
F, Wallemacq PE.

Louvain Centre for Toxicology and Applied Pharmacology, Université catholique de 
Louvain, Brussels, Belgium.

Because the sepsis-induced pharmacokinetic (PK) modifications need to be
considered in aminoglycoside dosing, the present study aimed to develop a
population PK model for amikacin (AMK) in severe sepsis and to subsequently
propose an optimal sampling strategy suitable for Bayesian estimation of the drug
PK parameters. Concentration-time profiles for AMK were obtained from 88
critically ill septic patients during the first 24 hours of antibiotic treatment.
The population PK model was developed using a nonlinear mixed effects modeling
approach. Covariate analysis included demographic data, pathophysiological
characteristics, and comedication. Optimal sampling times were selected based on 
a robust Bayesian design criterion. Taking into account clinical constraints, a
two-point sampling approach was investigated. A two-compartment model with
first-order elimination best fitted the AMK concentrations. Population PK
estimates were 19.2 and 9.34 L for the central and peripheral volume of
distribution and 4.31 and 2.21 L/h for the intercompartmental and total body
clearance. Creatinine clearance estimated using the Cockcroft-Gault equation was 
retained in the final model. The two optimal sampling times were 1 hour and 6
hours after onset of the drug infusion. Predictive performance of individual
Bayes estimates computed using the proposed optimal sampling strategy was
reported: mean prediction errors were less than 5% and root mean square errors
were less than 30%. The present study confirmed the significant influence of the 
creatinine clearance on the PK disposition of AMK during the first hours of
treatment in critically ill septic patients. Based on the population estimates,
an optimal sampling strategy suitable for Bayesian estimation of the drug PK
parameters was developed, meeting the need of clinical practice.


PMID: 20962708 [PubMed - in process]