Format

Send to

Choose Destination
Clin Microbiol Infect. 2015 Oct;21(10):886-93. doi: 10.1016/j.cmi.2015.05.002. Epub 2015 May 14.

Optimization of dosing regimens and dosing in special populations.

Author information

1
School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, Australia; Therapeutics Research Centre, Basil Hetzel Institute for Translational Health Research, The Queen Elizabeth Hospital, Adelaide, Australia.
2
School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, Australia; Therapeutics Research Centre, Basil Hetzel Institute for Translational Health Research, The Queen Elizabeth Hospital, Adelaide, Australia; Therapeutics Research Centre, School of Medicine, University of Queensland, Herston, Brisbane, Queensland, Australia.
3
School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, Australia; Royal Brisbane and Women's Hospital, Herston, Brisbane, Queensland, Australia; Burns, Trauma and Critical Care Research Centre, University of Queensland, Herston, Brisbane, Queensland, Australia; Institute of Translational Medicine, University of Liverpool, Liverpool, UK. Electronic address: j.roberts2@uq.edu.au.

Abstract

Treatment of infectious diseases is becoming increasingly challenging with the emergence of less-susceptible organisms that are poorly responsive to existing antibiotic therapies, and the unpredictable pharmacokinetic alterations arising from complex pathophysiologic changes in some patient populations. In view of this fact, there has been a progressive work on novel dose optimization strategies to renew the utility of forgotten old antibiotics and to improve the efficacy of those currently in use. This review summarizes the different approaches of optimization of antibiotic dosing regimens and the special patient populations which may benefit most from these approaches. The existing methods are based on monitoring of antibiotic concentrations and/or use of clinical covariates. Measured concentrations can be correlated with predefined pharmacokinetic/pharmacodynamic targets to guide clinicians in predicting the necessary dose adjustment. Dosing nomograms are also available to relate observed concentrations or clinical covariates (e.g. creatinine clearance) with optimal dosing. More precise dose prediction based on observed covariates is possible through the application of population pharmacokinetic models. However, the most accurate estimation of individualized dosing requirements is achieved through Bayesian forecasting which utilizes both measured concentration and clinical covariates. Various software programs are emerging to ease clinical application. Whilst more studies are warranted to clarify the clinical outcomes associated with the different dose optimization approaches, severely ill patients in the course of marked infections and/or inflammation including those with sepsis, septic shock, severe trauma, burns injury, major surgery, febrile neutropenia, cystic fibrosis, organ dysfunction and obesity are those groups which may benefit most from individualized dosing.

KEYWORDS:

Antibiotics; dose optimization; pharmacodynamics; pharmacokinetics; therapeutic drug monitoring

PMID:
25980350
DOI:
10.1016/j.cmi.2015.05.002
[Indexed for MEDLINE]
Free full text

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center