Literature DB >> 15478070

Selection of a moxifloxacin dose that suppresses drug resistance in Mycobacterium tuberculosis, by use of an in vitro pharmacodynamic infection model and mathematical modeling.

Tawanda Gumbo1, Arnold Louie, Mark R Deziel, Linda M Parsons, Max Salfinger, George L Drusano.   

Abstract

BACKGROUND: Moxifloxacin is a quinolone antimicrobial that has potent activity against Mycobacterium tuberculosis. To optimize moxifloxacin dose and dose regimen, pharmacodynamic antibiotic-exposure targets associated with maximal microbial kill and complete suppression of drug resistance in M. tuberculosis must be identified.
METHODS: We used a novel in vitro pharmacodynamic infection model of tuberculosis in which we exposed M. tuberculosis to moxifloxacin with a pharmacokinetic half-life of decline similar to that encountered in humans. Data obtained from this model were mathematically modeled, and the drug-exposure breakpoint associated with the suppression of drug resistance was determined. Monte-Carlo simulations were performed to determine the probability that 10,000 clinical patients taking different doses of moxifloxacin would achieve or exceed the drug-exposure breakpoint needed to suppress resistance to moxifloxacin in M. tuberculosis.
RESULTS: The ratio of the moxifloxacin-free (non-protein-bound) area under the concentration-time curve from 0 to 24 h to the minimum inhibitory concentration associated with complete suppression of the drug-resistant mutant population was 53. For patients taking moxifloxacin doses of 400, 600, or 800 mg/day, the calculated target-attainment rates to suppress drug resistance were 59%, 86%, and 93%, respectively.
CONCLUSION: A moxifloxacin dose of 800 mg/day is likely to achieve excellent M. tuberculosis microbial kill and to suppress drug resistance. However, tolerability of this higher dose is still unknown.

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Year:  2004        PMID: 15478070     DOI: 10.1086/424849

Source DB:  PubMed          Journal:  J Infect Dis        ISSN: 0022-1899            Impact factor:   5.226


  137 in total

1.  In silico children and the glass mouse model: clinical trial simulations to identify and individualize optimal isoniazid doses in children with tuberculosis.

Authors:  Prakash M Jeena; William R Bishai; Jotam G Pasipanodya; Tawanda Gumbo
Journal:  Antimicrob Agents Chemother       Date:  2010-11-22       Impact factor: 5.191

2.  The combination of meropenem and levofloxacin is synergistic with respect to both Pseudomonas aeruginosa kill rate and resistance suppression.

Authors:  Arnold Louie; Caroline Grasso; Nadzeya Bahniuk; Brian Van Scoy; David L Brown; Robert Kulawy; G L Drusano
Journal:  Antimicrob Agents Chemother       Date:  2010-04-05       Impact factor: 5.191

Review 3.  An oracle: antituberculosis pharmacokinetics-pharmacodynamics, clinical correlation, and clinical trial simulations to predict the future.

Authors:  Jotam Pasipanodya; Tawanda Gumbo
Journal:  Antimicrob Agents Chemother       Date:  2010-10-11       Impact factor: 5.191

Review 4.  Suppression of Emergence of Resistance in Pathogenic Bacteria: Keeping Our Powder Dry, Part 1.

Authors:  G L Drusano; Arnold Louie; Alasdair MacGowan; William Hope
Journal:  Antimicrob Agents Chemother       Date:  2015-12-28       Impact factor: 5.191

5.  Limited sampling strategy and target attainment analysis for levofloxacin in patients with tuberculosis.

Authors:  Abdullah Alsultan; Guohua An; Charles A Peloquin
Journal:  Antimicrob Agents Chemother       Date:  2015-04-13       Impact factor: 5.191

6.  Resistance emergence mechanism and mechanism of resistance suppression by tobramycin for cefepime for Pseudomonas aeruginosa.

Authors:  G L Drusano; Robert A Bonomo; Nadzeya Bahniuk; Juergen B Bulitta; Brian Vanscoy; Holland Defiglio; Steven Fikes; David Brown; Sarah M Drawz; Robert Kulawy; Arnold Louie
Journal:  Antimicrob Agents Chemother       Date:  2011-10-17       Impact factor: 5.191

7.  Mechanism-based pharmacodynamic models of fluoroquinolone resistance in Staphylococcus aureus.

Authors:  Philip Chung; Patrick J McNamara; Jeffrey J Campion; Martin E Evans
Journal:  Antimicrob Agents Chemother       Date:  2006-09       Impact factor: 5.191

8.  Thioridazine pharmacokinetic-pharmacodynamic parameters "Wobble" during treatment of tuberculosis: a theoretical basis for shorter-duration curative monotherapy with congeners.

Authors:  Sandirai Musuka; Shashikant Srivastava; Chandima Wasana Siyambalapitiyage Dona; Claudia Meek; Richard Leff; Jotam Pasipanodya; Tawanda Gumbo
Journal:  Antimicrob Agents Chemother       Date:  2013-09-16       Impact factor: 5.191

9.  New susceptibility breakpoints for first-line antituberculosis drugs based on antimicrobial pharmacokinetic/pharmacodynamic science and population pharmacokinetic variability.

Authors:  Tawanda Gumbo
Journal:  Antimicrob Agents Chemother       Date:  2010-01-19       Impact factor: 5.191

10.  Development and qualification of a pharmacodynamic model for the pronounced inoculum effect of ceftazidime against Pseudomonas aeruginosa.

Authors:  Jürgen B Bulitta; Neang S Ly; Jenny C Yang; Alan Forrest; William J Jusko; Brian T Tsuji
Journal:  Antimicrob Agents Chemother       Date:  2008-10-13       Impact factor: 5.191

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