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

Abstract

Time-kill studies, even those performed with in vitro dynamic models, often do not provide definitive comparisons of different antimicrobial agents. Also, they do not allow determinations of equiefficient doses or predictions of area under the concentration-time curve (AUC)/MIC breakpoints that might be related to antimicrobial effects (AMEs). In the present study, a wide range of single doses of trovafloxacin (TR) and twice-daily doses of ciprofloxacin (CI) were mimicked in an in vitro dynamic model. The AMEs of TR and CI against gram-negative bacteria with similar susceptibilities to both drugs were related to AUC/MICs that varied over similar eight-fold ranges [from 54 to 432 and from 59 to 473 (μg · h/ml)/(μg/ml), respectively]. The observation periods were designed to include complete bacterial regrowth, and the AME was expressed by its intensity (the area between the control growth in the absence of antibiotics and the antibiotic-induced time-kill and regrowth curves up to the point where viable counts of regrowing bacteria equal those achieved in the absence of drug [I E]). In each experiment monoexponential pharmacokinetic profiles of TR and CI were simulated with half-lives of 9.2 and 4.0 h, respectively. Linear relationships between I E and log AUC/MIC were established for TR and CI against three bacteria: Escherichia coli (MIC of TR [MICTR] = 0.25 μg/ml; MIC of CI [MICCI] = 0.12 μg/ml), Pseudomonas aeruginosa (MICTR = 0.3 μg/ml; MICCI = 0.15 μg/ml), and Klebsiella pneumoniae(MICTR = 0.25 μg/ml; MICCI = 0.12 μg/ml). The slopes and intercepts of these relationships differed for TR and CI, and the I E-log AUC/MIC plots were not superimposed, although they were similar for all bacteria with a given antibiotic. By using the relationships betweenI E and log AUC/MIC, TR was more efficient than CI. The predicted value of the AUC/MIC breakpoint for TR [mean for all three bacteria, 63 (μg · h/ml)/(μg/ml)] was approximately twofold lower than that for CI. Based on theI E-log AUC/MIC relationships, the respective dose (D)-response relationships were reconstructed. Like the I E-log AUC/MIC relationships, theI E-log D plots showed TR to be more efficient than CI. Single doses of TR that are as efficient as two 500-mg doses of CI (500 mg given every 12 h) were similar for the three strains (199, 226, and 203 mg). This study suggests that in vitro evaluation of the relationships between I E and AUC/MIC or D might be a reliable basis for comparing different fluoroquinolones and that the results of such comparative studies may be highly dependent on their experimental design and datum quantitation.

Use of modeling techniques to aid in antibiotic selection

“…The latter case may be illustrated by an in vitro pharmacodynamic study with moxifloxacin against pneumococci [44]. Having only three values of AUBC determined over a 48-hour period (AUBC 48 ) that corresponded to a single value of T eff < 50%, the reported correlation of AUBC 48 to Teff was really based mostly on 0% (three points) and 100% values of T eff (six points). Obviously, the reported correlation coefficient (r 2 0.48) may not be completely reliable.…”

Comparative pharmacodynamics of the new fluoroquinolone ABT492 and ciprofloxacin with Escherichia coli and Pseudomonas aeruginosa in an in vitro dynamic model

“…4. Like other quinolones [10][11][12][13], a specific relationship was inherent in each quinolone-pathogen pair. With both E. coli and P. aeruginosa, AUC/MIC plots of I E were steeper for ciprofloxacin than ABT492, and the I E s produced by ciprofloxacin at a given AUC/MIC ratio (from 120 to 480 h with E. coli and from 60 to 480 h with P. aeruginosa), were greater than after ABT492 exposure.…”

“…As with other quinolones [10][11][12][13], AUC/MIC plots of the I E were superimposed for E. coli and P. aeruginosa (Fig. 5).…”

The classifications of antibiotics

“…Commonly used predictors of antimicrobial effect (AUC/MIC and t > MIC) were examined for pharmacokinetically different quinolones. Linear correlations were established between IE and log AUC/MIC and log t > MIC [38][39][40][41][42].…”