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.

Earlier efforts to search for pharmacokinetic and bacteriological predictors of fluoroquinolone antimicrobial effects (AMEs) have resulted in conflicting findings. To elucidate whether these conflicts are real or apparent, several predictors of the AMEs of two pharmacokinetically different antibiotics, trovafloxacin (TRO) and ciprofloxacin (CIP), as well as different dosing regimens of CIP were examined. The AMEs of TRO given once daily (q.d.) and CIP given q.d. and twice daily (b.i.d.) against Escherichia coli,Pseudomonas aeruginosa, and Klebsiella pneumoniae were studied in an in vitro dynamic model. Different monoexponential pharmacokinetic profiles were simulated with a TRO half-life of 9.2 h and a CIP half-life of 4.0 h to provide similar eightfold ranges of the area under the concentration-time curve (AUC)-to-MIC ratios, from 54 to 432 and from 59 to 473 (μg · h/ml)/(μg/ml), respectively. In each case the observation periods were designed to incorporate full-term regrowth phases in the time-kill curves, and the AME was expressed by its intensity (IE ; the area between the control growth and time-kill and regrowth curves up to the point at which the viable counts of regrowing bacteria are close to the maximum values observed without drug). Species-independent linear relationships were established between IE and log AUC/MIC, log AUC above MIC (log AUCeff), and time above the MIC (T eff). Specific and nonsuperimposedIE versus log AUC/MIC or log AUCeffrelationships were inherent in each of the treatments: TRO given q.d. (r 2 = 0.97 and 0.96), CIP given q.d. (r 2 = 0.98 and 0.96), and CIP given b.i.d. (r 2 = 0.95 and 0.93). This suggests that in order to combine data sets obtained with individual quinolones to examine potential predictors, one must be sure that these sets may be combined. Unlike AUC/MIC and AUCeff, the IE -T effrelationships plotted for the different quinolones and dosing regimens were nonspecific and virtually superimposed (r 2 = 0.95). Hence, AUC/MIC, AUCeff, and T eff were equally good predictors of the AME of each of the quinolones and each dosing regimen taken separately, whereas T eff was also a good predictor of the AMEs of the quinolones and their regimens taken together. However, neither the quinolones nor the dosing regimens could be distinguished solely on the basis of T eff, whereas they could be distinguished on the basis of AUC/MIC or AUCeff. Thus, two types of predictors of the quinolone AME may be identified: intraquinolone and/or intraregimen predictors (AUC/MIC, AUCeff and Teff) and an interquinolone and interregimen predictor (T eff). T eff may be able to accurately predict the AME of one quinolone on the basis of the data obtained for another quinolone.

No abstract

Multiple predictors of fluoroquinolone antimicrobial effects (AMEs) are not usually examined simultaneously in most studies. To compare the predictive potentials of the area under the concentration-time curve (AUC)-to-MIC ratio (AUC/MIC), the AUC above MIC (AUCeff), and the time above MIC (T eff), the kinetics of killing and regrowth of four bacterial strains exposed to monoexponentially decreasing concentrations of ciprofloxacin were studied in an in vitro dynamic model. The MICs of ciprofloxacin for clinical isolates ofStaphylococcus aureus, Escherichia coli11775 (I) and 204 (II), and Pseudomonas aeruginosa were 0.6, 0.013, 0.08, and 0.15 μg/ml, respectively. The simulated values of AUC were designed to provide similar 1,000-fold (S. aureus, E. coli I, and P. aeruginosa) or 2,000-fold (E. coli II) ranges of the AUC/MIC. In each case except for the highest AUC/MIC ratio, the observation periods included complete regrowth in the time-kill curve studies. The AME was expressed by its intensity,I E (the area between the control growth and time-kill and regrowth curves up to the point where the viable counts of regrowing bacteria are close to the maximum values observed without drug). For most AUC ranges the I E-AUC curves were fitted by an E max (maximal effect) model, whereas the effects observed at very high AUCs were greater than those predicted by the model. The AUCs that produced 50% of maximal AME were proportional to the MICs for the strains studied, but maximal AMEs (I E max ) and the extent of sigmoidicity (s) were not related to the MIC. BothT eff and log AUC/MIC correlated well withI E (r 2 = 0.98 in both cases) in a species-independent fashion. UnlikeT eff or log AUC/MIC, a specific relationship between I E and log AUCeff was inherent in each strain. Although each I E and log AUCeff plot was fitted by linear regression (r 2 = 0.97 to 0.99), these plots were not superimposed and therefore are bacterial species dependent. Thus, AUC/MIC and T eff were better predictors of ciprofloxacin’s AME than AUCeff. This study suggests that optimal predictors of the AME produced by a given quinolone (intraquinolone predictors) may be established by examining its AMEs against bacteria of different susceptibilities.T eff was shown previously also to be the best interquinolone predictor, but unlike AUC/MIC, it cannot be used to compare different quinolones. AUC/MIC might be the best predictor of the AME in comparisons of different quinolones.

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.