Literature DB >> 7965677

Pharmacodynamic modeling of bacterial kinetics: beta-lactam antibiotics against Escherichia coli.

R C Li1, D E Nix, J J Schentag.   

Abstract

A simple pharmacodynamic model has been developed to describe the bacterial kinetics exhibited by beta-lactam antibiotics. In contrast with previous models that only characterized the early killing phase of a time-kill curve, the present model is capable of simultaneously describing both the killing and regrowth phases. The model relied on the use of both first-order bactericidal and resistance formation rate constants to accurately define the time-dependent changes in the bacterial populations of an antibiotic-treated culture. The concentration dependency of the bactericidal rate constant was further delineated using a saturable-receptor model. Furthermore, an exponential decrease in the resistance formation rate with increasing antibiotic concentrations was demonstrated. The evolving pharmacodynamic model was also explored via computer simulations by perturbing the two governing rate constants. The model was subsequently applied to the description of time-kill data for amoxicillin, penicillin G, and cephalexin against Escherichia coli. The description of amdinocillin's action against E. coli was not as comprehensive because of the existence of a second killing phase. However, this model can be applicable to many classes of antibiotics that display the usual killing and regrowth phases in time-kill studies. The pharmacodynamic model can potentially improve the prediction of bacterial killing and regrowth and foster an improved understanding of complex antimicrobial pharmacodynamics.

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Year:  1994        PMID: 7965677     DOI: 10.1002/jps.2600830711

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  11 in total

Review 1.  Achieving an optimal outcome in the treatment of infections. The role of clinical pharmacokinetics and pharmacodynamics of antimicrobials.

Authors:  R C Li; M Zhu; J J Schentag
Journal:  Clin Pharmacokinet       Date:  1999-07       Impact factor: 6.447

2.  Pharmacodynamic modeling of in vitro activity of marbofloxacin against Escherichia coli strains.

Authors:  M Andraud; C Chauvin; P Sanders; M Laurentie
Journal:  Antimicrob Agents Chemother       Date:  2010-11-15       Impact factor: 5.191

3.  Pharmacodynamic modeling of ciprofloxacin resistance in Staphylococcus aureus.

Authors:  Jeffrey J Campion; Patrick J McNamara; Martin E Evans
Journal:  Antimicrob Agents Chemother       Date:  2005-01       Impact factor: 5.191

4.  Simultaneous pharmacodynamic analysis of the lag and bactericidal phases exhibited by beta-lactams against Escherichia coli.

Authors:  R C Li
Journal:  Antimicrob Agents Chemother       Date:  1996-10       Impact factor: 5.191

5.  The population dynamics of antimicrobial chemotherapy.

Authors:  M Lipsitch; B R Levin
Journal:  Antimicrob Agents Chemother       Date:  1997-02       Impact factor: 5.191

6.  Antibiotic exposure and its relationship to postantibiotic effect and bactericidal activity: constant versus exponentially decreasing tobramycin concentrations against Pseudomonas aeruginosa.

Authors:  R C Li; Z Y Zhu; S W Lee; K Raymond; J M Ling; A F Cheng
Journal:  Antimicrob Agents Chemother       Date:  1997-08       Impact factor: 5.191

Review 7.  Translational PK/PD of anti-infective therapeutics.

Authors:  Chetan Rathi; Richard E Lee; Bernd Meibohm
Journal:  Drug Discov Today Technol       Date:  2016-10-28

8.  Pharmacodynamic modeling of the evolution of levofloxacin resistance in Staphylococcus aureus.

Authors:  Jeffrey J Campion; Philip Chung; Patrick J McNamara; William B Titlow; Martin E Evans
Journal:  Antimicrob Agents Chemother       Date:  2005-06       Impact factor: 5.191

Review 9.  Mechanism-based pharmacokinetic-pharmacodynamic modeling of antimicrobial drug effects.

Authors:  David Czock; Frieder Keller
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-09-29       Impact factor: 2.410

10.  How fitness reduced, antimicrobial resistant bacteria survive and spread: a multiple pig-multiple bacterial strain model.

Authors:  Kaare Græsbøll; Søren Saxmose Nielsen; Nils Toft; Lasse Engbo Christiansen
Journal:  PLoS One       Date:  2014-07-09       Impact factor: 3.240

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