Determination of Antibiotic Effect in an In Vitro Pharmacodynamic Model: Comparison with an Established Animal Model of Infection

AUTOR(ES)

Bonapace, Charles R.

FONTE

American Society for Microbiology

RESUMO

Animal infection models have historically been used to study pharmacodynamic relationships. Similar results could theoretically be produced by using an in vitro pharmacodynamic model as an alternative to animal models. We compared the antibiotic effects of ticarcillin administered in various doses and dosing regimens against Pseudomonas aeruginosa ATCC 27853 under conditions analogous to those previously employed in a neutropenic-mouse thigh infection model (B. Vogelman et al., J. Infect. Dis. 158:831-847, 1988). Ticarcillin dosages of either 96, 192, or 384 mg/day were administered at 1-, 2-, 3-, 4-, 8-, 12-, or 24-h intervals into a two-compartment model in order to duplicate the concentration-time profiles of the animal model. Colony counts were enumerated at 0 and 24 h. Linear regression and sigmoidal maximum-effect (Emax) model fitting were used to assess the relationship between the percentage of time that the concentration remained above the MIC (%T>MIC) or above four times the MIC (%T>4×MIC) and the change in the log10 CFU per milliliter (Δlog10 CFU/ml) in the central and peripheral compartments. Statistical analysis of the Δlog10 CFU/ml values was performed for matched regimens of the in vitro and animal models based on the %T>MICs. The slopes of the regression equations of %T>MICs relative to Δlog10 CFU/ml values were similar for the in vitro and animal models, but the y intercept was greater with the in vitro model. The Δlog10 CFU/ml values of the 0- to 24-h colony counts at equivalent %T>MICs in the two models were not statistically different (P = 0.087). Overall, the peripheral compartment of the in vitro model was a better predictor of effect than the central compartment. This study, which compares pharmacodynamic principles between an in vitro and an animal model, demonstrated similar relationships between %T>MICs and effects.

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