Examination of time-kill curves of antibiotic-exposed bacteria using in vitro dynamic models allows pharmacokinetically related comparisons of antimicrobial effects but may or may not directly reflect the selective enrichment of resistant mutants. Bacterial resistance has been studied infrequently using these models. Limited observations reported from earlier timekill studies (3, 8, 21-23) precluded delineation of relationships of the area under the concentration-time curve (AUC)/MIC ratio with resistance because the ranges of the simulated AUCto-MIC ratios were too narrow. In fact, the first attempts to relate resistance to the AUC/MIC or peak concentration (C max )/MIC ratio were reported quite recently from studies that declared resistance analysis as a primary goal (1,7,17,18,20,(25)(26)(27)30,33,34; A. MacGowan and K. Bowker, Abstr. 41st Intersci. Conf. Antimicrob. Agents Chemother., poster A-440, 2001). Despite wide ranges of AUC/MIC ratios simulated in some recent studies (17)(18)(19)(20)27,33; MacGowan and Bowker, 41st ICAAC), reasonable relationships with resistance were not established. The relatively few studies of these relationships can be classified as those that directly attempt to relate resistance to the simulated pharmacokinetics but do not (17,20) and those that imply the existence of relationships with the AUC/MIC ratio measured within a 24-h dosing interval (AUC 24 /MIC) or with the C max /MIC ratio but do not actually report them (26,27,30). One study did report a complex effect of AUC 24 /MIC and duration of moxifloxacin treatment on bacterial resistance (MacGowan and Bowker, 41st ICAAC), but the three-dimensional plots masked rather than highlighted these links. For example, according to an analysis of these data (A. Firsov, S. Vostrov, I. Lubenko, S. Zinner, and Y. Portnoy, Abstr. 42nd Intersci. Conf. Antimicrob. Agents Chemother., abstr. A-1210Chemother., abstr. A- , p. 10, 2002, the reported 72-h area under the population analysis profile-time curve as an index of pneumococcal resistance did not correlate with simulated AUC 24 /MIC ratios (r 2 , 0.04).

These findings support the MSW hypothesis and suggest comparable antistaphylococcal effects of clinically achievable AUC24/MIC90s of daptomycin and vancomycin but slightly better prevention against the selection of resistant S. aureus by daptomycin.

Although many parameters have been described to quantitate the killing and regrowth of bacteria, substantial shortcomings are inherent in most of them, such as low sensitivity to pharmacokinetic determinants of the antimicrobial effect, an inability to predict a total effect, insufficient robustness, and uncertain interrelations between the parameters that prevent an ultimate determination of the effect. To examine different parameters, the kinetics of killing and regrowth of Escherichia coli (MIC, 0.013 microg/ml) were studied in vitro by simulating a series of ciprofloxacin monoexponential pharmacokinetic profiles. Initial ciprofloxacin concentrations varied from 0.02 to 19.2 microg/ml, whereas the half-life of 4 h was the same in all experiments. The following parameters were calculated and estimated: the time to reduce the initial inoculum (N0) 10-, 100-, and 1,000-fold (T90%, T99%, and T99.9%, respectively), the rate constant of bacterial elimination (k(elb)), the nadir level (Nmin) in the viable count (N)-versus-time (t) curve, the time to reach Nmin (t(min)), the numbers of bacteria that survived (Ntau) by the end of the observation period (tau), the area under the bacterial killing and regrowth curve (log N(A)-t curve) from the zero point (time zero) to tau (AUBC), the area above this curve (AAC), the area between the control growth curve (log N(C)-t curve) and the bacterial killing and regrowth curve (log N(A)-t curve) from the zero point to tau (ABBC) or to the time point when log N(A) reaches the maximal values observed in the log N(C)-t curve (I(E); intensity of the effect), and the time shift between the control growth and regrowth curves (T(E); duration of the effect). Being highly sensitive to the AUC, I(E), and T(E) showed the most regular AUC relationships: the effect expressed by I(E) or T(E) increased systematically when the AUC or initial concentration of ciprofloxacin rose. Other parameters, especially T90%, T99%, T99.9%, t(min), and log N0 - log Nmin = delta log Nmin, related to the AUC less regularly and were poorly sensitive to the AUC. T(E) proved to be the best predictor and t(min) proved to be the worst predictor of the total antimicrobial effect reflected by I(E). Distinct feedback relationships between the effect determination and the experimental design were demonstrated. It was shown that unjustified shortening of the observation period, i.e., cutting off the log N(A)-t curves, may lead to the degeneration of the AUC-response relationships, as expressed by log N0 - log Ntau = delta log Ntau, AUBC, AAC, or ABBC, to a point where it gives rise to the false idea of an AUC- or concentration-independent effect. Thus, use of I(E) and T(E) provides the most unbiased, robust, and comprehensive means of determining the antimicrobial effect.

No abstract

Overall, these findings predict greater efficacy of clinically achievable AUC/MIC (or AUC24/MIC) of ABT492 both in terms of the anti-staphylococcal effect and prevention of the selection of resistant mutants.