Literature DB >> 11524721

In vitro models, in vivo models, and pharmacokinetics: what can we learn from in vitro models?

A MacGowan1, C Rogers, K Bowker.   

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.

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Year:  2001        PMID: 11524721     DOI: 10.1086/321850

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


  11 in total

Review 1.  Setting and revising antibacterial susceptibility breakpoints.

Authors:  John Turnidge; David L Paterson
Journal:  Clin Microbiol Rev       Date:  2007-07       Impact factor: 26.132

Review 2.  Alternative strategies for proof-of-principle studies of antibacterial agents.

Authors:  Axel Dalhoff; Andrej Weintraub; Carl Erik Nord
Journal:  Antimicrob Agents Chemother       Date:  2014-05-27       Impact factor: 5.191

3.  Exposure-response analyses of tigecycline efficacy in patients with complicated skin and skin-structure infections.

Authors:  A K Meagher; J A Passarell; B B Cirincione; S A Van Wart; K Liolios; T Babinchak; E J Ellis-Grosse; P G Ambrose
Journal:  Antimicrob Agents Chemother       Date:  2007-03-12       Impact factor: 5.191

4.  In vitro pharmacokinetic and pharmacodynamic evaluation of S-013420 against Haemophilus influenzae and Streptococcus pneumoniae.

Authors:  Tomoyuki Homma; Toshihiko Hori; Merime Ohshiro; Hideki Maki; Yoshinori Yamano; Jingoro Shimada; Shogo Kuwahara
Journal:  Antimicrob Agents Chemother       Date:  2010-07-26       Impact factor: 5.191

5.  Antimicrobial breakpoints for gram-negative aerobic bacteria based on pharmacokinetic-pharmacodynamic models with Monte Carlo simulation.

Authors:  Christopher R Frei; Nathan P Wiederhold; David S Burgess
Journal:  J Antimicrob Chemother       Date:  2008-02-04       Impact factor: 5.790

Review 6.  Evaluating drug resistance in visceral leishmaniasis: the challenges.

Authors:  S Hendrickx; P J Guerin; G Caljon; S L Croft; L Maes
Journal:  Parasitology       Date:  2016-11-21       Impact factor: 3.234

7.  A novel in vitro metric predicts in vivo efficacy of inhaled silver-based antimicrobials in a murine Pseudomonas aeruginosa pneumonia model.

Authors:  Parth N Shah; Kush N Shah; Justin A Smolen; Jasur A Tagaev; Jose Torrealba; Lan Zhou; Shiyi Zhang; Fuwu Zhang; Patrick O Wagers; Matthew J Panzner; Wiley J Youngs; Karen L Wooley; Carolyn L Cannon
Journal:  Sci Rep       Date:  2018-04-23       Impact factor: 4.379

8.  Optimization and Characterization of a Galleria mellonella Larval Infection Model for Virulence Studies and the Evaluation of Therapeutics Against Streptococcus pneumoniae.

Authors:  Freya Cools; Eveline Torfs; Juliana Aizawa; Bieke Vanhoutte; Louis Maes; Guy Caljon; Peter Delputte; Davie Cappoen; Paul Cos
Journal:  Front Microbiol       Date:  2019-02-21       Impact factor: 5.640

9.  Effect of Predatory Bacteria on Human Cell Lines.

Authors:  Shilpi Gupta; Chi Tang; Michael Tran; Daniel E Kadouri
Journal:  PLoS One       Date:  2016-08-31       Impact factor: 3.240

Review 10.  Silver Nanoparticle-Mediated Cellular Responses in Various Cell Lines: An in Vitro Model.

Authors:  Xi-Feng Zhang; Wei Shen; Sangiliyandi Gurunathan
Journal:  Int J Mol Sci       Date:  2016-09-22       Impact factor: 5.923

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