Literature DB >> 9517948

Inter- and intraquinolone predictors of antimicrobial effect in an in vitro dynamic model: new insight into a widely used concept.

A A Firsov1, A A Shevchenko, S N Vostrov, S H Zinner.   

Abstract

Earlier efforts to search for pharmacokinetic and bacteriological predictors of fluoroquinolone antimicrobial effects (AMEs) have resulted in conflicting findings. To elucidate whether these conflicts are real or apparent, several predictors of the AMEs of two pharmacokinetically different antibiotics, trovafloxacin (TRO) and ciprofloxacin (CIP), as well as different dosing regimens of CIP were examined. The AMEs of TRO given once daily (q.d.) and CIP given q.d. and twice daily (b.i.d.) against Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae were studied in an in vitro dynamic model. Different monoexponential pharmacokinetic profiles were simulated with a TRO half-life of 9.2 h and a CIP half-life of 4.0 h to provide similar eightfold ranges of the area under the concentration-time curve (AUC)-to-MIC ratios, from 54 to 432 and from 59 to 473 (microg x h/ml)/(microg/ml), respectively. In each case the observation periods were designed to incorporate full-term regrowth phases in the time-kill curves, and the AME was expressed by its intensity (IE; the area between the control growth and time-kill and regrowth curves up to the point at which the viable counts of regrowing bacteria are close to the maximum values observed without drug). Species-independent linear relationships were established between IE and log AUC/MIC, log AUC above MIC (log AUCeff), and time above the MIC (Teff). Specific and nonsuperimposed IE versus log AUC/MIC or log AUCeff relationships were inherent in each of the treatments: TRO given q.d. (r2 = 0.97 and 0.96), CIP given q.d. (r2 = 0.98 and 0.96), and CIP given b.i.d. (r2 = 0.95 and 0.93). This suggests that in order to combine data sets obtained with individual quinolones to examine potential predictors, one must be sure that these sets may be combined. Unlike AUC/MIC and AUCeff, the IE-Teff relationships plotted for the different quinolones and dosing regimens were nonspecific and virtually superimposed (r2 = 0.95). Hence, AUC/MIC, AUCeff and Teff were equally good predictors of the AME of each of the quinolones and each dosing regimen taken separately, whereas Teff was also a good predictor of the AMEs of the quinolones and their regimens taken together. However, neither the quinolones nor the dosing regimens could be distinguished solely on the basis of Teff whereas they could be distinguished on the basis of AUC/MIC or AUCeff. Thus, two types of predictors of the quinolone AME may be identified: intraquinolone and/or intraregimen predictors (AUC/MIC, AUCeff and Teff) and an interquinolone and interregimen predictor (Teff). Teff may be able to accurately predict the AME of one quinolone on the basis of the data obtained for another quinolone.

Entities:  

Mesh:

Substances:

Year:  1998        PMID: 9517948      PMCID: PMC105514     

Source DB:  PubMed          Journal:  Antimicrob Agents Chemother        ISSN: 0066-4804            Impact factor:   5.191


  20 in total

1.  Quantitative analysis of antimicrobial effect kinetics in an in vitro dynamic model.

Authors:  A A Firsov; V M Chernykh; S M Navashin
Journal:  Antimicrob Agents Chemother       Date:  1990-07       Impact factor: 5.191

2.  Parameters of bacterial killing and regrowth kinetics and antimicrobial effect examined in terms of area under the concentration-time curve relationships: action of ciprofloxacin against Escherichia coli in an in vitro dynamic model.

Authors:  A A Firsov; S N Vostrov; A A Shevchenko; G Cornaglia
Journal:  Antimicrob Agents Chemother       Date:  1997-06       Impact factor: 5.191

3.  Pharmacokinetics and penetration into inflammatory fluid of trovafloxacin (CP-99,219).

Authors:  R Wise; D Mortiboy; J Child; J M Andrews
Journal:  Antimicrob Agents Chemother       Date:  1996-01       Impact factor: 5.191

4.  A pharmacodynamic evaluation of ciprofloxacin and ofloxacin against two strains of Pseudomonas aeruginosa.

Authors:  K J Madaras-Kelly; A J Larsson; J C Rotschafer
Journal:  J Antimicrob Chemother       Date:  1996-04       Impact factor: 5.790

5.  The comparative pharmacokinetics of five quinolones.

Authors:  R Wise; D Lister; C A McNulty; D Griggs; J M Andrews
Journal:  J Antimicrob Chemother       Date:  1986-11       Impact factor: 5.790

6.  Influence of ampicillin elimination half-life on in-vitro bactericidal effect.

Authors:  C A White; R D Toothaker
Journal:  J Antimicrob Chemother       Date:  1985-01       Impact factor: 5.790

7.  Correlation of antimicrobial pharmacokinetic parameters with therapeutic efficacy in an animal model.

Authors:  B Vogelman; S Gudmundsson; J Leggett; J Turnidge; S Ebert; W A Craig
Journal:  J Infect Dis       Date:  1988-10       Impact factor: 5.226

8.  Comparative study with enoxacin and netilmicin in a pharmacodynamic model to determine importance of ratio of antibiotic peak concentration to MIC for bactericidal activity and emergence of resistance.

Authors:  J Blaser; B B Stone; M C Groner; S H Zinner
Journal:  Antimicrob Agents Chemother       Date:  1987-07       Impact factor: 5.191

9.  Pharmacokinetics of ciprofloxacin after oral and parenteral administration.

Authors:  G Höffken; H Lode; C Prinzing; K Borner; P Koeppe
Journal:  Antimicrob Agents Chemother       Date:  1985-03       Impact factor: 5.191

Review 10.  Determinants of efficacy and toxicity of aminoglycosides.

Authors:  H Mattie; W A Craig; J C Pechère
Journal:  J Antimicrob Chemother       Date:  1989-09       Impact factor: 5.790

View more
  18 in total

1.  Use of Modeling Techniques to Aid in Antibiotic Selection.

Authors:  Alexander A. Firsov; Stephen H. Zinner
Journal:  Curr Infect Dis Rep       Date:  2001-02       Impact factor: 3.725

2.  Relationships of the area under the curve/MIC ratio to different integral endpoints of the antimicrobial effect: gemifloxacin pharmacodynamics in an in vitro dynamic model.

Authors:  A A Firsov; I Y Lubenko; Y A Portnoy; S H Zinner; S N Vostrov
Journal:  Antimicrob Agents Chemother       Date:  2001-03       Impact factor: 5.191

Review 3.  Issues in pharmacokinetics and pharmacodynamics of anti-infective agents: kill curves versus MIC.

Authors:  Markus Mueller; Amparo de la Peña; Hartmut Derendorf
Journal:  Antimicrob Agents Chemother       Date:  2004-02       Impact factor: 5.191

4.  A concept for pharmacokinetic-pharmacodynamic dosage adjustment in renal impairment: the case of aminoglycosides.

Authors:  D Czock; M Giehl; F Keller
Journal:  Clin Pharmacokinet       Date:  2000-04       Impact factor: 6.447

5.  Using In Vitro Dynamic Models To Evaluate Fluoroquinolone Activity against Emergence of Resistant Salmonella enterica Serovar Typhimurium.

Authors:  Seung-Jin Lee; Elias Gebru Awji; Na-Hye Park; Seung-Chun Park
Journal:  Antimicrob Agents Chemother       Date:  2017-01-24       Impact factor: 5.191

6.  Comparative pharmacodynamics and antimutant potentials of doripenem and imipenem with ciprofloxacin-resistant Pseudomonas aeruginosa in an in vitro model.

Authors:  Alexander A Firsov; Deborah Gilbert; Kenneth Greer; Yury A Portnoy; Stephen H Zinner
Journal:  Antimicrob Agents Chemother       Date:  2011-12-27       Impact factor: 5.191

7.  Pharmacodynamics of gemifloxacin against Streptococcus pneumoniae in an in vitro pharmacokinetic model of infection.

Authors:  A P MacGowan; C A Rogers; H A Holt; M Wootton; K E Bowker
Journal:  Antimicrob Agents Chemother       Date:  2001-10       Impact factor: 5.191

8.  A new approach to in vitro comparisons of antibiotics in dynamic models: equivalent area under the curve/MIC breakpoints and equiefficient doses of trovafloxacin and ciprofloxacin against bacteria of similar susceptibilities.

Authors:  A A Firsov; S N Vostrov; A A Shevchenko; Y A Portnoy; S H Zinner
Journal:  Antimicrob Agents Chemother       Date:  1998-11       Impact factor: 5.191

9.  MIC-based interspecies prediction of the antimicrobial effects of ciprofloxacin on bacteria of different susceptibilities in an in vitro dynamic model.

Authors:  A A Firsov; S N Vostrov; A A Shevchenko; S H Zinner; G Cornaglia; Y A Portnoy
Journal:  Antimicrob Agents Chemother       Date:  1998-11       Impact factor: 5.191

10.  Fluoroquinolones in the Treatment of Meningitis.

Authors:  Philippe Cottagnoud; Martin G. Täuber
Journal:  Curr Infect Dis Rep       Date:  2003-08       Impact factor: 3.725

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.