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Clinical Infectious Diseases
Article . 2001 . Peer-reviewed
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In Vitro Models, In Vivo Models, and Pharmacokinetics: What Can We Learn from In Vitro Models?

Authors: A, MacGowan; C, Rogers; K, Bowker;

In Vitro Models, In Vivo Models, and Pharmacokinetics: What Can We Learn from In Vitro Models?

Abstract

In vitro pharmacokinetic models of infection can make an important contribution to the study of the pharmacodynamic properties of an antibacterial agent. In conjunction with animal and human pharmacodynamic evaluations, they provide data to allow for the optimization of drug dosing regimens. In vitro models can be used simply to describe the effect of a drug on a bacterial population as well as to provide data for more-analytical studies, including hypothesis testing. Analytical study designs provide information on the pharmacodynamic parameter best related to the chosen outcome, as well as its magnitude. Factors such as the characteristics of the model (method of drug removal, inoculum density, and growth phase), doses simulated, species and susceptibility range of bacteria, and methods and analytical tools used to measure antibacterial effect will have an effect on the conclusions drawn. In vitro models have an important future role in ensuring antibiotic efficacy and in reducing the risks of resistance.

Related Organizations
Keywords

Animals, Humans, Models, Biological, Anti-Bacterial Agents

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
36
Top 10%
Top 10%
Average
bronze