Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2013, Article ID 202818, 8 pages
Research Article

Amikacin Population Pharmacokinetics in Critically Ill Kuwaiti Patients

1Department of Pharmacology & Therapeutics, Faculty of Pharmacy, Kuwait University, P.O. Box 24923, Kuwait City 13110, Kuwait
2Department of Pharmacy, Al-Amiri Hospital, Ministry of Health, P.O. Box 491, Kuwait City 32005, Kuwait
3Intensive Care Unit, Al-Amiri Hospital, Ministry of Health, P.O. Box 491, Kuwait City 32005, Kuwait
4Laboratory of Applied Pharmacokinetics, School of Medicine, University of Southern California, Los Angeles, CA 90033, USA

Received 19 September 2012; Revised 30 November 2012; Accepted 30 November 2012

Academic Editor: Abdelwahab Omri

Copyright © 2013 Kamal M. Matar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Amikacin pharmacokinetic data in Kuwaiti (Arab) intensive care unit (ICU) patients are lacking. Fairly sparse serum amikacin peak and trough concentrations data were obtained from adult Kuwaiti ICU patients. The data were analysed using a nonparametric adaptive grid (NPAG) maximum likelihood algorithm. The estimations of the developed model were assessed using mean error (ME) as a measure of bias and mean squared error (MSE) as a measure of precision. A total of 331 serum amikacin concentrations were obtained from 56 patients. The mean (±SD) model parameter values found were = 0.2302 ± 0.0866 L/kg, = 0.004045 ± 0.00705 min per unit of creatinine clearance, = 2.2121 ± 5.506 h−1, and = 1.431 ± 2.796 h−1. The serum concentration data were estimated with little bias (ME = −0.88) and good precision (MSE = 13.08). The present study suggests that amikacin pharmacokinetics in adult Kuwaiti ICU patients are generally rather similar to those found in other patients. This population model would provide useful guidance in developing initial amikacin dosage regimens for such patients, especially using multiple model (MM) dosage design, followed by appropriate Bayesian adaptive control, to optimize amikacin dosage regimens for each individual patient.