Using PK/PD to Optimize Antibiotic Dosing for Critically Ill Patients

Roberts, Jason A. (2011) Using PK/PD to Optimize Antibiotic Dosing for Critically Ill Patients. Current Pharmaceutical Biotechnology, 12 12: 2070-2079. doi:10.2174/138920111798808329

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Author Roberts, Jason A.
Title Using PK/PD to Optimize Antibiotic Dosing for Critically Ill Patients
Journal name Current Pharmaceutical Biotechnology   Check publisher's open access policy
ISSN 1389-2010
Publication date 2011-12-01
Year available 2011
Sub-type Article (original research)
DOI 10.2174/138920111798808329
Open Access Status Not Open Access
Volume 12
Issue 12
Start page 2070
End page 2079
Total pages 10
Place of publication Bussum, The Netherlands
Publisher Bentham Science Publishers
Language eng
Abstract Critically ill patients with severe infections are at high risk of suboptimal antimicrobial dosing. The pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobials in these patients differ significantly from the patient groups from whose data the conventional dosing regimens were developed. Use of such regimens often results in inadequate antimicrobial concentrations at the site of infection and is associated with poor patient outcomes. In this article, we describe the potential of in vitro and in vivo infection models, clinical pharmacokinetic data and pharmacokinetic/pharmacodynamic models to guide the design of more effective antimicrobial dosing regimens. Individualised dosing, based on population PK models and patient factors (e.g. renal function and weight) known to influence antimicrobial PK, increases the probability of achieving therapeutic drug exposures while at the same time avoiding toxic concentrations. When therapeutic drug monitoring (TDM) is applied, early dose adaptation to the needs of the individual patient is possible. TDM is likely to be of particular importance for infected critically ill patients, where profound PK changes are present and prompt appropriate antibiotic therapy is crucial. In the light of the continued high mortality rates in critically ill patients with severe infections, a paradigm shift to refined dosing strategies for antimicrobials is warranted to enhance the probability of achieving drug concentrations that increase the likelihood of clinical success.
Formatted abstract
Antibiotic prescription for critically ill patients is a complicated process because of the pharmacokinetic differences of this patient population with non-critically ill patients and the lack of robust informative studies. This article seeks to review the available literature describing dosing requirements for optimized treatment of critically ill patients and to discuss a framework to rationally address complex cases by outlining the suggested processes for optimal achievement of pharmacokinetic/ pharmacodynamic targets. A variety of papers exist describing the effect of pathophysiology on antibiotic kinetics. In the critically ill patient, dysfunction of almost any organ system can result in significant changes to drug volume of distribution and clearance. Dysfunction of the cardiovascular and renal systems in particular is problematic and can lead to potentially sub-therapeutic antibiotic concentrations in blood and in interstitial fluid. In response to altered pharmacokinetics, dose regimens that adhere to the pharmacodynamics of the antibiotic are essential. In the absence of validated dosing algorithms, therapeutic drug monitoring data and susceptibility data of the infecting pathogen should be inputted into a Bayesian software program that include population pharmacokinetic models to calculate dosing regimens that are personalized for the critically ill patient.
Keyword Pharmacokinetics
Volume Of Distribution
Renal failure
Renal Replacement Therapy
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID R01 HD070886
R01 GM068968
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2012 Collection
School of Medicine Publications
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Citation counts: TR Web of Science Citation Count  Cited 21 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 29 times in Scopus Article | Citations
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