Literature DB >> 8837524

A pharmacodynamic model for the action of the antibiotic imipenem on Pseudomonas aeruginosa populations in vitro.

P H Berg1, E O Voit, R L White.   

Abstract

The standard method for measuring in vitro antibiotic efficacy is based on a point observation of bacterial activity 18 hours after inoculation. The method, while simple, forgoes significant information by ignoring the dynamics of the interactions between antibiotic and bacteria. This paper proposes a simple dynamic model describing these interactions. The model consists of two non-linear differential equations of the S-system type. Its parameter values are estimated, through the minimization of residual errors, from data on the effect of the carbapenem antibiotic imipenem on Pseudomonas aeruginosa. The model adequately describes the dynamic behavior of the bacterial populations in the presence of the antibiotic: beginning with drug administration, then through the decline of the bacterial population and possibly ending with bacterial resurgence.

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Year:  1996        PMID: 8837524     DOI: 10.1007/bf02459490

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  14 in total

1.  Allometric morphogenesis of complex systems: Derivation of the basic equations from first principles.

Authors:  M A Savageau
Journal:  Proc Natl Acad Sci U S A       Date:  1979-12       Impact factor: 11.205

2.  Growth of complex systems can be related to the properties of their underlying determinants.

Authors:  M A Savageau
Journal:  Proc Natl Acad Sci U S A       Date:  1979-11       Impact factor: 11.205

3.  Predictive value of susceptibility tests for the outcome of antibacterial therapy.

Authors:  V Lorian; L Burns
Journal:  J Antimicrob Chemother       Date:  1990-01       Impact factor: 5.790

4.  Impact of dosage schedule on the efficacy of gentamicin, tobramycin, or amikacin in an experimental model of Serratia marcescens endocarditis: in vitro-in vivo correlation.

Authors:  G Potel; J Caillon; B Fantin; J Raza; F Le Gallou; J Y Lepage; P Le Conte; D Bugnon; D Baron; H Drugeon
Journal:  Antimicrob Agents Chemother       Date:  1991-01       Impact factor: 5.191

5.  Comparative in vitro pharmacodynamics of imipenem and meropenem against Pseudomonas aeruginosa.

Authors:  R White; L Friedrich; D Burgess; D Warkentin; J Bosso
Journal:  Antimicrob Agents Chemother       Date:  1996-04       Impact factor: 5.191

Review 6.  Imipenem.

Authors:  W C Hellinger; N S Brewer
Journal:  Mayo Clin Proc       Date:  1991-10       Impact factor: 7.616

7.  Single daily dosing of antibiotics: importance of in vitro killing rate, serum half-life, and protein binding.

Authors:  G Potel; N P Chau; B Pangon; B Fantin; J M Vallois; F Faurisson; C Carbon
Journal:  Antimicrob Agents Chemother       Date:  1991-10       Impact factor: 5.191

8.  Analysis of vancomycin time-kill studies with Staphylococcus species by using a curve stripping program to describe the relationship between concentration and pharmacodynamic response.

Authors:  B H Ackerman; A M Vannier; E B Eudy
Journal:  Antimicrob Agents Chemother       Date:  1992-08       Impact factor: 5.191

9.  Examination of gram-negative bacilli from meningitis patients who failed or relapsed on moxalactam therapy.

Authors:  R H Eng; C Cherubin; S M Smith; F Buccini
Journal:  Antimicrob Agents Chemother       Date:  1984-12       Impact factor: 5.191

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  5 in total

1.  System estimation from metabolic time-series data.

Authors:  Gautam Goel; I-Chun Chou; Eberhard O Voit
Journal:  Bioinformatics       Date:  2008-09-04       Impact factor: 6.937

2.  Studies of antibiotic resistance within the patient, hospitals and the community using simple mathematical models.

Authors:  D J Austin; R M Anderson
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1999-04-29       Impact factor: 6.237

Review 3.  The best models of metabolism.

Authors:  Eberhard O Voit
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2017-05-19

Review 4.  Recent developments in parameter estimation and structure identification of biochemical and genomic systems.

Authors:  I-Chun Chou; Eberhard O Voit
Journal:  Math Biosci       Date:  2009-03-25       Impact factor: 2.144

5.  Parameter optimization in S-system models.

Authors:  Marco Vilela; I-Chun Chou; Susana Vinga; Ana Tereza R Vasconcelos; Eberhard O Voit; Jonas S Almeida
Journal:  BMC Syst Biol       Date:  2008-04-16
  5 in total

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