Monte Carlo simulations: Maximizing antibiotic pharmacokinetic data to optimize clinical practice for critically ill patients

Roberts, Jason, Kirkpatrick, Carl M.J. and Lipman, Jeffrey (2011) Monte Carlo simulations: Maximizing antibiotic pharmacokinetic data to optimize clinical practice for critically ill patients. Journal of Antimicrobial Chemotherapy, 66 2: 227-231. doi:10.1093/jac/dkq449


Author Roberts, Jason
Kirkpatrick, Carl M.J.
Lipman, Jeffrey
Title Monte Carlo simulations: Maximizing antibiotic pharmacokinetic data to optimize clinical practice for critically ill patients
Journal name Journal of Antimicrobial Chemotherapy   Check publisher's open access policy
ISSN 0305-7453
1460-2091
Publication date 2011-02-01
Year available 2010
Sub-type Article (original research)
DOI 10.1093/jac/dkq449
Volume 66
Issue 2
Start page 227
End page 231
Total pages 5
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Collection year 2011
Language eng
Formatted abstract
Infections in critically ill patients continue to result in unacceptably high morbidity and mortality. Although few data exist for correlating antibiotic exposure with outcome, antibiotic dosing is likely to be highly important for maximizing resolution of infection in many patients. The practical and financial difficulties of performing pharmacokinetic (PK) studies in critically ill patients mean that analyses to maximize data such as Monte Carlo simulation (MCS) are highly valuable. MCS uses computer software to perform virtual clinical trials. The building blocks for MCS are: firstly, a robust population PK model from the patient population of interest; secondly, descriptors of the effect of covariates that influence the PK parameters; thirdly, description of the susceptibility of bacteria to the antibiotic and finally a PK/pharmacodynamic (PD) target associated with antibiotic efficacy. Probability of target attainment (PTA) outputs can then be generated that describe the proportion of patients that will achieve a pre-specified PD target for an MIC distribution. Such analyses can then inform dosing requirements, which can be used to have a high likelihood of achieving PK/PD targets for organisms with different MICs. In this issue of JAC, Zelenitsky et al. provide a very useful example of MCS for interpreting the optimal methods for dosing meropenem, piperacillin/tazobactam, cefepime and ceftobiprole in critically ill patients.
© The Author 2010. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.
Keyword Dosing
Minimum inhibitory concentration
Pharmacodynamics
Population pharmacokinetics
Susceptibility
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes First published online: November 30, 2010

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
School of Medicine Publications
School of Pharmacy Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 51 times in Thomson Reuters Web of Science Article | Citations
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Created: Tue, 15 Feb 2011, 22:40:52 EST by Charna Kovacevic on behalf of Anaesthesiology and Critical Care - RBWH