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

Bulletin of Mathematical Biology

Volumn 58, Issue 5, 1996, Pages 923-938

  Berg, Paul H ^a   Voit, Eberhard O ^a   White, Roger L ^a  

^a MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACTERIA (MICROORGANISMS); PSEUDOMONAS; PSEUDOMONAS AERUGINOSA;

EID: 0030238601     PISSN: 00928240     EISSN: None     Source Type: Journal    
DOI: 10.1007/bf02459490     Document Type: Article

References (25)

1. Abboud, F. M. and B. A. Waisbren. 1959. Correlation of results of the tube dilution method for determining bacterial sensitivity to antibiotics and the results of the administration of these antibiotics to patients with staphylococcic bacteremia. Antibiotic. Ann. 9, 748-756.
2. Ackerman, B. H., A. M. Vannier, and E. B. Eudy. 1992. Analysis of vancomycin time-kill studies with staphylococcus species by using a curve stripping program to describe the relationship between concentration and response. Antimicrob. Agents Chemother. 36, 1766-1769.
3. Berk, S. L. and W. R. McCabe. 1980. Meningitis caused by Gram-negative bacilli. Ann. Intern. Med. 93, 253-260.
4. Buckley, M. M., R. N. Brogden, L. B. Barradell, and K. L. Goa. 1992. Imipenem/cilastatin. A preappraisal of its antibacterial activity, pharmacokinetic properties and therapeutic efficacy. Drugs 44, 408-444.
5. Drake, T. A., C. J. Hackbarth, and M. A. Sande. 1983. Value of serum tests in combined drug therapy of endocarditis. Antimicrob. Agents Chemother. 24, 653-657.
6. Eng, R. H. K., C. Cherubin, S. M. Smith, and F. Buccini. 1984. Examination of Gram-negative bacilli from meningitis patients who failed or relapsed on moxalactam therapy. Antimicrob. Agents Chemother. 26, 850-856.
7. Hellinger, W. C. and N. S. Brewer. 1991. Imipenem. Mayo Clin. Proc. 66, 1074-1081.
8. Lorian, V., L. Burns, and J. Ernst. 1990. Predictive values of susceptibility tests for the outcome of antibiotic therapy. J. Antimicrob. Chemother. 25, 175-181.
9. NCCLS. 1992. Methods for determining bactericidal activity of antimicrobial agents. Tentative guideline M26-T. National Committee for Clinical Laboratory Standards, Villanova, PA.
10. NCCLS. 1993. Methods for dilution antimicrobial susceptibility tests for bacteria that grow aerobically. Approved standard M7-A3. National Committee for Clinical Laboratory Standards, Villanova, PA.
11. Potel, G., J. Caillon, B. Fantin, J. Raza, F. Le Gallou, J. Y. Lepage, P. Le Conte, D. Bugnon, D. Baron, and H. B. Drugeon. 1991a. 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. Antimicrob Agents Chemother. 35, 111-116.
12. Potel, G., N. P. Chau, B. Pangon, B. Fantin, J. M. Vallois, F. Faurisson, and C. Carbon. 1991b. Single daily dosing of antibiotics: importance of in vitro killing rate, serum half-life, and protein binding. Antimicrob. Agents Chemother. 35, 2085-2090.
13. Sands, P. J. and E. O. Voit. 1996. Flux-based estimation of parameters in S-systems. Ecol. Model., to appear.
14. Savageau, M. A. 1969. Biochemical systems analysis: II. The steady-state solutions for an n-pool system using a power-law approximation. J. Theor. Biol. 25, 370-379.
15. Savageau, M. A. 1979a. Growth of complex systems can be related to the properties of their underlying determinants. Proc. Natl. Acad. Sci. U.S.A. 76, 5413-5417.
16. Savageau, M. A. 1979b. Allometric morphogenesis of complex systems: derivation of the basic equations from first principles. Proc. Natl. Acad. Sci. U.S.A. 76, 6023-6025.
17. Simulation Resources, Inc. 1992. SCoP: a general-purpose simulation package, version 3.4. Simulation Resources, Inc., Berrien Springs, MI.
18. Voit, E. O. 1988. Dynamics of self-thinning plant stands. Ann. Bot. 62, 67-78.
19. Voit, E. O. (Ed.). 1991. Canonical Nonlinear Modeling, S-System Approach to Understanding Complexity. New York: Van Nostrand Reinhold.
20. Voit, E. O. 1992. The S-distribution: a tool for approximation and classification of univariate, unimodal probability distributions. Biometrical J. 34, 855-878.
21. Voit, E. O. and P. J. Sands. 1996a. Modeling forest growth. I. Canonical approach. Ecol. Model. 86, 51-71.
22. Voit, E. O. and P. J. Sands. 1996b. Modeling forest growth. II. Biomass partitioning in Scots pine. Ecol. Model. 86, 73-89.
23. Voit, E. O. and M. A. Savageau. 1982. Power-law approach to modeling biological systems: II. Application to ethanol production. J. Ferment. Technol. 60, 229-232.
24. Voit, E. O. and S. Yu. 1994. The S-distribution: approximation of discrete distributions. Biometrical J. 36, 205-219.
25. White, R., Friedrich, L., Burgess, D., Warkentin, D., and Bosso, J. 1996. Comparative in vitro pharmacodynamics of imipenem and meropenem against P. aeruginosa. Antimicrob. Agents and Chemother., to appear.