Abstract
We developed and applied pharmacokinetic-pharmacodynamic (PK-PD) models to characterize in vitro bacterial rate of killing as a function of ceftazidime concentrations over time. For PK-PD modeling, data obtained during continuous and intermittent infusion of ceftazidime in Pseudomonas aeruginosa killing experiments with an in vitro pharmacokinetic model were used. The basic PK-PD model was a maximum-effect model which described the number of viable bacteria (N) as a function of the growth rate (lambda) and killing rate (epsilon) according to the equation dN/dt = [lambda - epsilon x [Cgamma(EC50gamma + Cgamma)]] N, where gamma is the Hill factor, C is the concentration of antibiotic, and EC50 is the concentration of antibiotic at which 50% of the maximum effect is obtained. Next, four different models with increasing complexity were analyzed by using the EDSIM program (MediWare, Groningen, The Netherlands). These models incorporated either an adaptation rate factor and a maximum number of bacteria (Nmax) factor or combinations of the two parameters. In addition, a two-population model was evaluated. Model discrimination was by Akaike's information criterion. The experimental data were best described by the model which included an Nmax term and a rate term for adaptation for a period up to 36 h. The absolute values for maximal growth rate and killing rate in this model were different from those in the original experiment, but net growth rates were comparable. It is concluded that the derived models can describe bacterial growth and killing in the presence of antibiotic concentrations mimicking human pharmacokinetics. Application of these models will eventually provide us with parameters which can be used for further dosage optimization.
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Selected References
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- Blaser J. In-vitro model for simultaneous simulation of the serum kinetics of two drugs with different half-lives. J Antimicrob Chemother. 1985 Jan;15 (Suppl A):125–130. doi: 10.1093/jac/15.suppl_a.125. [DOI] [PubMed] [Google Scholar]
- Levy G. Mechanism-based pharmacodynamic modeling. Clin Pharmacol Ther. 1994 Oct;56(4):356–358. doi: 10.1038/clpt.1994.149. [DOI] [PubMed] [Google Scholar]
- Mattie H., Sekh B. A., van Ogtrop M. L., van Strijen E. Comparison of the antibacterial effects of cefepime and ceftazidime against Escherichia coli in vitro and in vivo. Antimicrob Agents Chemother. 1992 Nov;36(11):2439–2443. doi: 10.1128/aac.36.11.2439. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mattie H., van Dokkum A. M., Brus-Weijer L., Krul A. M., van Strijen E. Antibacterial activity of four cephalosporins in an experimental infection in relation to in vitro effect and pharmacokinetics. J Infect Dis. 1990 Sep;162(3):717–722. doi: 10.1093/infdis/162.3.717. [DOI] [PubMed] [Google Scholar]
- Mouton J. W., den Hollander J. G. Killing of Pseudomonas aeruginosa during continuous and intermittent infusion of ceftazidime in an in vitro pharmacokinetic model. Antimicrob Agents Chemother. 1994 May;38(5):931–936. doi: 10.1128/aac.38.5.931. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vogelman B., Craig W. A. Kinetics of antimicrobial activity. J Pediatr. 1986 May;108(5 Pt 2):835–840. doi: 10.1016/s0022-3476(86)80754-5. [DOI] [PubMed] [Google Scholar]
- Yamaoka K., Nakagawa T., Uno T. Application of Akaike's information criterion (AIC) in the evaluation of linear pharmacokinetic equations. J Pharmacokinet Biopharm. 1978 Apr;6(2):165–175. doi: 10.1007/BF01117450. [DOI] [PubMed] [Google Scholar]
- Zhi J. G., Nightingale C. H., Quintiliani R. Microbial pharmacodynamics of piperacillin in neutropenic mice of systematic infection due to Pseudomonas aeruginosa. J Pharmacokinet Biopharm. 1988 Aug;16(4):355–375. doi: 10.1007/BF01062551. [DOI] [PubMed] [Google Scholar]
- Zhi J., Nightingale C. H., Quintiliani R. A pharmacodynamic model for the activity of antibiotics against microorganisms under nonsaturable conditions. J Pharm Sci. 1986 Nov;75(11):1063–1067. doi: 10.1002/jps.2600751108. [DOI] [PubMed] [Google Scholar]