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Drugs

, Volume 66, Issue 1, pp 1–14 | Cite as

Optimising Dosing Strategies of Antibacterials Utilising Pharmacodynamic Principles

Impact on the Development of Resistance
  • C. Andrew DeRyke
  • Su Young Lee
  • Joseph L. Kuti
  • David P. NicolauEmail author
Current Opinion

Abstract

Evolving antimicrobial resistance is of global concern. The impact of decreased susceptibility to current antibacterials coupled with the decline in the marketing of new agents with novel mechanisms of action places a tremendous burden on clinicians to appropriately use available agents. Optimising antibacterial dose administration through the use of pharmacodynamic principles can aid clinicians in accomplishing this task more effectively. Methods to achieve this include: continuous or prolonged infusion, or the use of smaller doses administered more frequently for the time-dependent β-lactam agents; or higher, less frequent dose administration of the concentration-dependent aminoglycosides and fluoroquinolones. Pharmacodynamic breakpoints, which are predictive of clinical and/or microbiological success in the treatment of infection, have been determined for many classes of antibacterials, including the fluoroquinolones, aminoglycosides and β-lactams. Although surpassing these values may predict efficacy, it may not prevent the development of resistance. Recent studies seek to determine the pharmacodynamic breakpoints that prevent the development of resistance. Numerous studies to this point have determined these values in fluoroquinolones in both Gram-positive and Gram-negative bacteria. However, among the other antibacterial classes, there is a lack of sufficient data. Additionally, a new term, the mutant prevention concentration, has been based on the concentrations above which resistance is unlikely to occur. Future work is needed to fully characterise these target concentrations that prevent resistance.

Keywords

Minimum Inhibitory Concentration Fluoroquinolones Levofloxacin Meropenem Moxifloxacin 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

No sources of funding were used in the preparation of this article. The authors have no conflicts of interest to disclose that are directly relevant to the preparation of this review.

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Copyright information

© Adis Data Information BV 2006

Authors and Affiliations

  • C. Andrew DeRyke
    • 1
  • Su Young Lee
    • 1
  • Joseph L. Kuti
    • 1
  • David P. Nicolau
    • 1
    Email author
  1. 1.Center for Anti-Infective Research and DevelopmentHartford HospitalHartfordUSA

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