Quantitative analysis of antimicrobial effect kinetics in an in vitro dynamic model

Novel Pharmacokinetic/Pharmacodynamic Parameters Quantify the Exposure-Effect Relationship of Levofloxacin against Fluoroquinolone-Resistant Escherichia coli

Minimal inhibitory concentration-based pharmacokinetic/pharmacodynamic (PK/PD) indices are commonly applied to antibiotic dosing optimisation, but their informative value is limited, as they do not account for bacterial growth dynamics over time. We aimed to comprehensively characterise the exposure–effect relationship of levofloxacin against Escherichia coli and quantify strain-specific characteristics applying novel PK/PD parameters. In vitro infection model experiments were leveraged to explore the exposure–effect relationship of three clinical Escherichia coli isolates, harbouring different genomic fluoroquinolone resistance mechanisms, under constant levofloxacin concentrations or human concentration–time profiles (≤76 h). As an exposure metric, the ‘cumulative area under the levofloxacin–concentration time curve’ was determined. The antibiotic effect was assessed as the ‘cumulative area between the growth control and the bacterial-killing and -regrowth curve’. PK/PD modelling was applied to characterise the exposure–effect relationship and derive novel PK/PD parameters. A sigmoidal E_max model with an inhibition term best characterised the exposure–effect relationship and allowed for discrimination between two isolates sharing the same MIC value. Strain- and exposure-pattern-dependent differences were captured by the PK/PD parameters and elucidated the contribution of phenotypic adaptation to bacterial regrowth. The novel exposure and effect metrics and derived PK/PD parameters allowed for comprehensive characterisation of the isolates and could be applied to overcome the limitations of the MIC in clinical antibiotic dosing decisions, drug research and preclinical development.

Bacterial resistance studies using in vitro dynamic models: the predictive power of the mutant prevention and minimum inhibitory antibiotic concentrations

In light of the concept of the mutant selection window, i.e., the range between the MIC and the mutant prevention concentration (MPC), MPC-related pharmacokinetic indices should be more predictive of bacterial resistance than the respective MIC-related indices. However, experimental evidence of this hypothesis remains limited and contradictory. To examine the predictive power of the ratios of the area under the curve (AUC24) to the MPC and the MIC, the selection of ciprofloxacin-resistant mutants of four Escherichia coli strains with different MPC/MIC ratios was studied. Each organism was exposed to twice-daily ciprofloxacin for 3 days at AUC24/MIC ratios that provide peak antibiotic concentrations close to the MIC, between the MIC and the MPC, and above the MPC. Resistant E. coli was intensively enriched at AUC24/MPCs from 1 to 10 h (AUC24/MIC from 60 to 360 h) but not at the lower or higher AUC24/MPC and AUC24/MIC ratios. AUC24/MPC and AUC24/MIC relationships of the areas under the time courses of ciprofloxacin-resistant E. coli (AUBCM) were bell-shaped. A Gaussian-like function fits the AUBCM-AUC24/MPC and AUBCM-AUC24/MIC data combined for all organisms (r(2) = 0.69 and 0.86, respectively). The predicted anti-mutant AUC24/MPC ratio was 58 ± 35 h, and the respective AUC24/MIC ratio was 1,080 ± 416 h. Although AUC24/MPC was less predictive of strain-independent E. coli resistance than AUC24/MIC, the established anti-mutant AUC24/MPC ratio was closer to values reported for Staphylococcus aureus (60 to 69 h) than the respective AUC24/MIC ratio (1,080 versus 200 to 240 h). This implies that AUC24/MPC might be a better interspecies predictor of bacterial resistance than AUC24/MIC.

Comparative pharmacodynamics and antimutant potentials of doripenem and imipenem with ciprofloxacin-resistant Pseudomonas aeruginosa in an in vitro model

To compare the antipseudomonal efficacy of doripenem and imipenem as well as their abilities to restrict the enrichment of resistant Pseudomonas aeruginosa, multiple-dosing regimens of each drug were simulated at comparable values of the cumulative percentages of a 24-h period that the drug concentration exceeds the MIC under steady-state pharmacokinetic conditions (T(>MIC)) and ratios of the 24-hour area under the curve (AUC(24)) to the MIC. Three clinical isolates of ciprofloxacin-resistant P. aeruginosa (MIC of doripenem, 1 μg/ml; MICs of imipenem, 1, 2, and 2 μg/ml) were exposed to thrice-daily doripenem or imipenem for 3 days at AUC(24)/MIC ratios of from 50 to 170 h (doripenem) and from 30 to 140 h (imipenem). The antimicrobial effects for susceptible and resistant subpopulations of bacteria were expressed by the areas between control growth and time-kill curves (I(E)s) and areas under the bacterial mutant concentration curves (AUBC(M)s), respectively. With each antibiotic, the I(E) and AUBC(M) versus log AUC(24)/MIC relationships were bacterial strain independent. At similar AUC(24)/MIC ratios, doripenem was slightly less efficient than imipenem against susceptible and resistant subpopulations of bacteria. However, doripenem appeared to be somewhat more efficient than imipenem at clinically achievable AUC(24)s related to the means of the MICs for the three studied strains and had higher antimutant potentials for two of the three strains.

The antistaphylococcal pharmacodynamics of linezolid alone and in combination with doxycycline in an in vitro dynamic model

To delineate the possible advantages of linezolid/doxycycline combinations over either drug alone, the in vitro pharmacodynamics of linezolid, doxycycline and linezolid plus doxycycline were studied with Staphylococcus aureus.S. aureus ATCC 43300 and a clinical isolate S. aureus 479 were exposed to twice-daily linezolid and once-daily doxycycline, alone and in combination, for five consecutive days. Three dosing regimens were simulated with each drug alone: linezolid (AUC(24)/MIC 30, 60 and 200 h-L30, L60 and L200, respectively) and doxycycline (AUC(24)/MIC 90, 180 and 520 h - D90, D180 and D520, respectively) and in combination: linezolid plus doxycycline (L30+D90; L60+D180 and L200+D520).With both S. aureus ATCC 43300 and S. aureus 479 exposed to linezolid or doxycycline, the area between the line crossing each time-kill curve at the level of 10(8) CFU/mL and the respective time-kill curve (I(E)) increased with increasing simulated AUC(24)/MIC ratios. Each of the combined treatments produced greater I(E)s than the sum of linezolid and doxycycline I(E)s observed in the respective single drug treatments.This study suggests that linezolid combinations with doxycycline may be synergistic in treating staphylococcal infections.

Linezolid pharmacodynamics with Staphylococcus aureus in an in vitro dynamic model

To describe the relationship between the ratio of the 24-h area under the concentration-time curve (AUC(24)) to minimum inhibitory concentration (MIC) as well as the effect of linezolid on Staphylococcus aureus, the killing kinetics of three S. aureus strains was studied by in vitro simulation of 5-day antibiotic dosing over a wide range of AUC(24)/MIC ratios. Similarly susceptible meticillin-resistant S. aureus ATCC 43300 and S. aureus 479 and vancomycin-intermediate S. aureus ATCC 700699 (Mu50) at a starting inoculum of 10(8) colony-forming units (CFU)/mL were exposed to multiple-dose pharmacokinetics of twice-daily linezolid for 5 days. The simulated AUC(24)/MIC ratios varied from 30 h to 1200 h (S. aureus ATCC 43300), from 30h to 600 h (S. aureus 479) and from 50h to 400 h (S. aureus ATCC 700699). The cumulative antimicrobial effect was expressed by its intensity (I(E)) measured from the start of treatment to the time after the last antibiotic dose when numbers of antibiotic-exposed bacteria reached >or=10(8)CFU/mL. With each organism, bacterial re-growth followed a pronounced reduction of the starting inoculum that occurred at each simulated AUC(24)/MIC ratio except for the lowest value (30 h). This reduction was AUC(24)/MIC-dependent: the minimum numbers of surviving organisms decreased with increasing AUC(24)/MIC ratios. A sigmoid relationship was established between I(E) and the simulated AUC(24)/MIC ratio. This relationship was bacterial strain-independent; a logistic function fits the combined data with r(2)=0.95. The established AUC(24)/MIC-I(E) relationship is useful to predict the antistaphylococcal effects of linezolid at clinically attainable AUC(24)/MIC values.

Antistaphylococcal effect related to the area under the curve/MIC ratio in an in vitro dynamic model: predicted breakpoints versus clinically achievable values for seven fluoroquinolones

Prediction of the relative efficacies of different fluoroquinolones is often based on the ratios of the clinically achievable area under the concentration-time curve (AUC) to the MIC, usually with incorporation of the MIC50 or the MIC90 and with the assumption of antibiotic-independent patterns of the AUC/MIC-response relationships. To ascertain whether this assumption is correct, the pharmacodynamics of seven pharmacokinetically different quinolones against two clinical isolates of Staphylococcus aureus were studied by using an in vitro model. Two differentially susceptible clinical isolates of S. aureus were exposed to two 12-h doses of ciprofloxacin (CIP) and one dose of gatifloxacin (GAT), gemifloxacin (GEM), grepafloxacin (GRX), levofloxacin (LVX), moxifloxacin (MXF), and trovafloxacin (TVA) over similar AUC/MIC ranges from 58 to 932 h. A specific bacterial strain-independent AUC/MIC relationship with the antimicrobial effect (I(E)) was associated with each quinolone. Based on the I(E)-log AUC/MIC relationships, breakpoints (BPs) that are equivalent to a CIP AUC/MIC ratio of 125 h were predicted for GRX, MXF, and TVA (75 to 78 h), GAT and GEM (95 to 103 h) and LVX (115 h). With GRX and LVX, the predicted BPs were close to those established in clinical settings (no clinical data on other quinolones are available in the literature). To determine if the predicted AUC/MIC BPs are achievable at clinical doses, i.e., at the therapeutic AUCs (AUC(ther)s), the AUC(ther)/MIC50 ratios were studied. These ratios exceeded the BPs for GAT, GEM, GRX, MXF, TVA, and LVX (750 mg) but not for CIP and LVX (500 mg). AUC/MIC ratios above the BPs can be considered of therapeutic potential for the quinolones. The highest ratios of AUC(ther)/MIC50 to BP were achieved with TVA, MXF, and GEM (2.5 to 3.0); intermediate ratios (1.5 to 1.6) were achieved with GAT and GRX; and minimal ratios (0.3 to 1.2) were achieved with CIP and LVX.

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

The killing kinetics of Escherichia coli and Pseudomonas aeruginosa were compared when exposed to ABT492 and ciprofloxacin. E. coli ATCC 25922 and a clinical isolate of P. aeruginosa 4226 were exposed to ABT492 (single dose) and ciprofloxacin (two 12 h doses) at the ratios of area under the curve (AUC) to MIC varying from 60 to 480 h and at clinically achievable AUC/MIC ratios of ABT492 (1,740 and 140 h, respectively) and ciprofloxacin (2,200 and 120 h, respectively) that correspond to a 400 mg dose of ABT492 and two 500 mg doses of ciprofloxacin. In addition, a double dose of ABT492 (800 mg; AUC/MIC 280 h) and two 12 h doses of ABT492 (2 x 400 mg) were used with P. aeruginosa. Maximal reductions in the starting inoculum of E. coli and P. aeruginosa were greater with ABT492 than with ciprofloxacin at a given AUC/MIC ratio (60-480 h), whereas the times to regrowth were shorter with ABT492. A specific AUC/MIC relationship of the antimicrobial effect was inherent in each quinolone-pathogen pair. With both E. coli and P. aeruginosa, AUC/MIC plots of the area between the control growth and the time-kill curves (I(E)) were steeper for ciprofloxacin than ABT492 and they were species-independent. The effect of ABT492 on E. coli at the clinically achievable AUC/MIC ratio (1740h) was more pronounced than the respective AUC/MIC of ciprofloxacin (2,200 h). With P. aeruginosa, a 140 h AUC/MIC of ABT492 (400 mg as a single dose) provided 1.8-fold less effect than a 120 h AUC/MIC of ciprofloxacin (2 x 500 mg). However, two 12 h doses of ABT492 (AUC/MIC 2 x 140 h) but not a double single dose (800 mg) were more efficient than ciprofloxacin. These findings predict comparable efficacies of clinically achievable AUC/MICs of ABT492 and ciprofloxacin against E. coli (q.d. versus b.i.d. quinolone dosing) and P. aeruginosa at b.i.d. but not at q.d. ABT492.

Prevention of the selection of resistant Staphylococcus aureus by moxifloxacin plus doxycycline in an in vitro dynamic model: an additive effect of the combination

Twenty-four hour ratios of area under the curve (AUC(24)) to MIC of 200-240 h providing quinolone concentrations above the mutant prevention concentration (MPC) protected from enrichment of resistant Staphylococcus aureus in our recent study that simulated the pharmacokinetics of moxifloxacin, gatifloxacin, levofloxacin and ciprofloxacin. These protective AUC(24)/MICs might also be achieved by using antibiotic combinations, assuming additive effects of two anti-staphylococcal agents. To test this hypothesis, changes in S. aureus susceptibility were examined in a dynamic model that simulates 5-day treatment with moxifloxacin and doxycycline, alone and in combination at sub-optimal AUC(24)/MICs of each agent. Significant increases in MIC were observed with monotherapy where moxifloxacin or doxycycline concentrations fell into the mutant selection window (MSW) for more than 80% of the dosing interval (AUC(24)/MIC 60 h). Less pronounced changes in MIC occurred when the summed concentrations of moxifloxacin (AUC(24)/MIC 30 and 60 h) and doxycycline (AUC(24)/MIC 30 and 60 h) were inside the MSWs for the individual drugs for 30-50% of the dosing interval. No loss in susceptibility was found at moxifloxacin or doxycycline AUC(24)/MIC 170 h combined with the smaller AUC(24)/MIC (60 h) of the second compound. These data suggest that the total AUC(24)/MIC of 230 h might protect against S. aureus resistance. As this value is very close to that predicted in monotherapy with moxifloxacin (220 h), an additive protective effect of quinolone+doxycycline on the selection of resistant S. aureus is proposed. The use of drug combinations may be useful for restricting the enrichment of resistant mutants with agents whose clinically achievable AUC(24)/MICs do not provide concentrations above the MPC.

In vitro pharmacodynamic evaluation of the mutant selection window hypothesis using four fluoroquinolones against Staphylococcus aureus

To study the hypothesis of the mutant selection window (MSW) in a pharmacodynamic context, the susceptibility of a clinical isolate of methicillin-resistant Staphylococcus aureus exposed to moxifloxacin (MOX), gatifloxacin (GAT), levofloxacin (LEV), and ciprofloxacin (CIP) was tested daily by using an in vitro dynamic model that simulates human pharmacokinetics. A series of monoexponential pharmacokinetic profiles that mimic once-daily administration of MOX (half-life, 12 h), GAT (half-life, 7 h), and LEV (half-life, 6.8 h) and twice-daily administration of CIP (half-life, 4 h) provided peak concentrations (C(max)) that either equaled the MIC, fell between the MIC and the mutant prevention concentration (MPC) (i.e., within or "inside" the MSW), or exceeded the MPC. The respective ratios of the area under the curve (AUC) over a 24-h dosing interval (AUC(24)) to the MIC varied from 13 to 244 h, and the starting inoculum was 10(8) CFU/ml (6 x 10(9) CFU per 60-ml central compartment). With all four quinolones, the greatest increases in MIC were observed at those AUC(24)/MIC values (from 24 to 62 h) that corresponded to quinolone concentrations within the MSW over most of the dosing interval (>20%). Less-pronounced increases in MIC were associated with the smallest simulated AUC(24)/MIC values (15 to 16 h) of GAT and CIP, whose C(max) exceeded the MICs. No such increases were observed with the smallest AUC(24)/MIC values (13 to 17 h) of MOX and LEV, whose C(max) were close to the MICs. Also, less pronounced but significant increases in MIC occurred at AUC(24)/MIC values (107 to 123 h) that correspond to quinolone concentrations partly overlapping the MIC-to-MPC range. With all four drugs, no change in MIC was seen at the highest AUC(24)/MIC values (201 to 244 h), where quinolone concentrations exceeded the MPC over most of the dosing interval. These "protective" AUC(24)/MIC ratios correspond to 66% of the usual clinical dose of MOX (400 mg), 190% of a 400-mg dose of GAT, 220% of a 500-mg dose of LEV, and 420% of two 500-mg doses of CIP. Thus, MOX may protect against resistance development at subtherapeutic doses, whereas GAT, LEV, and CIP provide similar effects only at doses that exceed their usual clinical doses. These data support the concept that resistant mutants are selectively enriched when antibiotic concentrations fall inside the MSW and suggest that in vitro dynamic models can be used to predict the relative abilities of quinolones to prevent mutant selection.

Species-independent pharmacodynamics of gemifloxacin and ciprofloxacin with Haemophilus influenzae and Moraxella catarrhalis in an in vitro dynamic model

To demonstrate the antimicrobial effects of the different pharmacokinetics of gemifloxacin and ciprofloxacin, the pharmacodynamics of gemifloxacin and ciprofloxacin were studied using two clinical isolates each of Haemophilus influenzae and Moraxella catarrhalis. Monoexponentially decreasing concentrations of gemifloxacin (single dose, half-life 7.4 h) and ciprofloxacin (two 12-h doses, half-life 4 h) were simulated in an in vitro dynamic model over 8-fold ranges of the area under the curve (AUC)-to-MIC ratio: from 56 to 466 and 112-932 h, respectively. With each quinolone, log-linear relationships were established between the intensity of the antimicrobial effect (I(E)) and AUC/MIC. The I(E)-log AUC/MIC plots were bacterial strain- and species-independent and the gemifloxacin and ciprofloxacin plots were not superimposable. To generalize the findings obtained with the studied organisms, the effects of gemifloxacin and ciprofloxacin on hypothetical strains of H. influenzae and M. catarrhalis with MICs equal to the respective MIC(90)s were predicted. Based on these predictions, the AUC/MIC(90)s of 320 mg gemifloxacin (800 h with H. influenzae and 400 h with M. catarrhalis) may be 31-34% more efficient than those of 2 x 500 mg ciprofloxacin (730 and 365 h, respectively). These data suggest greater efficacy of gemifloxacin against H. influenzae and M. catarrhalis relative to ciprofloxacin at clinically achievable AUC/MIC ratios.

What in vitro models of infection can and cannot do

The science of pharmacodynamics analyzes the relationship between an antimicrobial's bactericidal effects and its pharmacokinetics. Ideally, randomized and well-controlled clinical trials are the best way to determine pharmacodynamic properties. However, in vitro models that recapitulate in vivo drug clearance profiles represent an increasingly important technology for carrying out pharmacodynamic studies in a more cost-effective, timely, and easily controlled fashion. Although in vitro pharmacodynamic models cannot incorporate all variables seen in vivo, they do provide valuable information for the drug development process and the determination of optimal dosing regimens.

Comparative anti-staphylococcal effects of gemifloxacin and trovafloxacin in an in vitro dynamic model in terms of AUC/MIC and dose relationships

To compare the antimicrobial effects of gemifloxacin and trovafloxacin on Staphylococcus aureus, their pharmacodynamics were studied in an in vitro dynamic model. A series of pharmacokinetic profiles of gemifloxacin and trovafloxacin with half-lives of 7.4 and 9.2 h, respectively, were simulated in vitro over an eightfold range of area under the curve (AUC)-to-MIC ratio, from 58 to 466 h. The relationships observed between the intensity of antimicrobial effect (I(E)) and log AUC/MIC were linear, species- and strain-independent and were distinct (not superimposed) for both gemifloxacin and trovafloxacin (r(2) = 0.99 in both cases). At AUC/MICs > 100 h, trovafloxacin had greater effects than gemifloxacin. For example, at an AUC/MIC of 250 h, the antimicrobial effect of trovafloxacin was 17% higher than gemifloxacin. However, due to its higher intrinsic activity, gemifloxacin may be as efficient as trovafloxacin at their clinical doses (320 and 200 mg, respectively): the I(E)s on a hypothetical strain of S. aureus with gemifloxacin's and trovafloxacin's MICs corresponding to the MIC(50)s were similar-290 and 310 (log CFU/mL)x h, respectively. This analysis suggests that both AUC/MIC and dose relationships of the antimicrobial effect are needed for comprehensive comparisons of fluoroquinolone pharmacodynamics.

Relationships of the area under the curve/MIC ratio to different integral endpoints of the antimicrobial effect: gemifloxacin pharmacodynamics in an in vitro dynamic model

Most integral endpoints of the antimicrobial effect are determined over an arbitrarily chosen time period, such as the dosing interval (tau), regardless of the actual effect duration. Unlike the tau-related endpoints, the intensity of the antimicrobial effect (I(E)) does consider its duration-from time zero to the time when bacterial counts on the regrowth curve achieve the same maximal numbers as in the absence of the antimicrobial. To examine the possible impact of this fundamental difference on the relationships of the antimicrobial effect to the ratio of the area under the concentration-time curve (AUC) to the MIC, a clinical isolate of Staphylococcus aureus was exposed to simulated gemifloxacin pharmacokinetics over a 40-fold range of AUC/MIC ratios, from 11 to 466 h. In each run, I(E) and four tau-related endpoints, including the area under the time-kill curve (AUBC), the area above the curve (AAC), the area between the control growth and time-kill curves (ABBC), and the ABBC related to the area under the control growth curve (AUGC), were calculated for tau = 24 h. Unlike the I(E), which displayed pseudolinear relationships with the AUC/MIC ratio; each tau-related endpoint showed a distinct saturation at potentially therapeutic AUC/MIC ratios (116 to 466 h) when the antimicrobial effect persisted longer than tau. This saturation results from the underestimation of the true effect and may be eliminated if ABBC, AAC, and AUBC (but not AUGC) are modified and determined in the same manner as the I(E) to consider the actual effect duration. These data suggest a marginal value of the tau-related endpoints as indices of the total antimicrobial effect. Since all of them respond to AUC/MIC ratio changes less than the I(E), the latter is preferable in comparative pharmacodynamic studies.

Use of Modeling Techniques to Aid in Antibiotic Selection

Over the past decade, the use of modeling techniques in the development of novel antibiotics has been primarily associated with in vitro dynamic models. These models allow comparisons among different antibiotics by simulating human pharmacokinetics. Although dynamic models have been used extensively, their full potential has not been achieved because of inadequate experimental design and/or suboptimal quantitation of bacterial killing/regrowth curves inherent in many studies. These issues are discussed in this review, which is based on recent pharmacodynamic findings with novel fluoroquinolones.

Comparative pharmacodynamics of gatifloxacin and ciprofloxacin in an in vitro dynamic model: prediction of equiefficient doses and the breakpoints of the area under the curve/MIC ratio

To demonstrate the impact of the pharmacokinetics of gatifloxacin (GA) relative to those of ciprofloxacin (CI) on the antimicrobial effect (AME), the killing and regrowth kinetics of two differentially susceptible clinical isolates each of Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae were studied. With each organism, a series of monoexponential pharmacokinetic profiles of GA (half-life [t(1/2)], 7 h) and CI (t(1/2) = 4 h) were simulated to mimic different single doses of GA and two 12-h doses of CI. The respective eightfold ranges of the ratios of the area under the concentration-time curve (AUC) to the MIC were 58 to 466 and 116 to 932 (microg. h/ml)/(microg/ml). The species- and strain-independent linear relationships observed between the intensity of AME (I(E)) and log AUC/MIC were not superimposed for GA and CI (r(2) = 0.99 in both cases). The predicted AUC/MIC ratio for GA that might be equivalent to a clinically relevant AUC/MIC breakpoint for CI was estimated to be 102 rather than 125 (microg. h/ml)/(microg/ml). The respective MIC breakpoints were 0.32 microg/ml (for a 400-mg dose of GA) and 0.18 microg/ml (for two 500-mg doses of CI). On the basis of the I(E)-log AUC/MIC relationships, equiefficient 24-h doses (D(24h)s) of GA and CI were calculated for hypothetical strains of S. aureus, E. coli, and K. pneumoniae for which the MICs were equal to the MICs at which 50% of isolates are inhibited. To provide an "acceptable" I(E) equal to 200 (log CFU/ml). h, i.e., the I(E) provided by AUC/MIC of 125 (microg. h/ml)/(microg/ml) for ciprofloxacin, the D(24h)s of GA for all three organisms were much lower (115, 30, and 60 mg) than the clinically proposed 400-mg dose. Although the usual dose of CI (two doses of 500 mg) would be in excess for E. coli and K. pneumoniae (D(24h) = two doses of 40 mg and two doses of 115 mg, respectively), even the highest clinical dose of CI (two doses of 750 mg) might be insufficient for S. aureus (D(24h), > two doses of 1,000 mg). The method of generalization of data obtained with specific organisms to other representatives of the same species described in the present report might be useful for prediction of the AMEs of new quinolones.

Prediction of the effects of inoculum size on the antimicrobial action of trovafloxacin and ciprofloxacin against Staphylococcus aureus and Escherichia coli in an in vitro dynamic model

The effect of inoculum size (N0) on antimicrobial action has not been extensively studied in in vitro dynamic models. To investigate this effect and its predictability, killing and regrowth kinetics of Staphylococcus aureus and Escherichia coli exposed to monoexponentially decreasing concentrations of trovafloxacin (as a single dose) and ciprofloxacin (two doses at a 12-h interval) were compared at N0 = 10(6) and 10(9) CFU/ml (S. aureus) and at N0 = 10(6), 10(7), and 10(9) CFU/ml (E. coli). A series of pharmacokinetic profiles of trovafloxacin and ciprofloxacin with respective half-lives of 9.2 and 4 h were simulated at different ratios of area under the concentration-time curve (AUC) to MIC (in [micrograms x hours/milliliter]/[micrograms/milliliter]): 58 to 466 with trovafloxacin and 116 to 932 with ciprofloxacin for S. aureus and 58 to 233 and 116 to 466 for E. coli, respectively. Although the effect of N0 was more pronounced for E. coli than for S. aureus, only a minor increase in minimum numbers of surviving bacteria and an almost negligible delay in their regrowth were associated with an increase of the N0 for both organisms. The N0-induced reductions of the intensity of the antimicrobial effect (IE, area between control growth and the killing-regrowth curves) were also relatively small. However, the N0 effect could not be eliminated either by simple shifting of the time-kill curves obtained at higher N0s by the difference between the higher and lowest N0 or by operating with IEs determined within the N0-adopted upper limits of bacterial numbers (IE's). By using multivariate correlation and regression analyses, linear relationships between IE and log AUC/MIC and log N0 related to the respective mean values [(log AUC/MIC)average and (log N0)average] were established for both trovafloxacin and ciprofloxacin against each of the strains (r2 = 0.97 to 0.99). The antimicrobial effect may be accurately predicted at a given AUC/MIC of trovafloxacin or ciprofloxacin and at a given N0 based on the relationship IE = a + b [(log AUC/MIC)/(log AUC/MIC)average] - c [(log N0)/(log N0)average]. Moreover, the relative impacts of AUC/MIC and N0 on IE may be evaluated. Since the c/b ratios for trovafloxacin and ciprofloxacin against E. coli were much lower (0.3 to 0.4) than that for ampicillin-sulbactam as examined previously (1.9), the inoculum effect with the quinolones may be much less pronounced than with the beta-lactams. The described approach to the analysis of the inoculum effect in in vitro dynamic models might be useful in studies with other antibiotic classes.

MIC-based interspecies prediction of the antimicrobial effects of ciprofloxacin on bacteria of different susceptibilities in an in vitro dynamic model

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 (Teff), 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 of Staphylococcus aureus, Escherichia coli 11775 (I) and 204 (II), and Pseudomonas aeruginosa were 0.6, 0.013, 0.08, and 0.15 microg/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, IE (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 IE-AUC curves were fitted by an Emax (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 (IEmax) and the extent of sigmoidicity (s) were not related to the MIC. Both Teff and log AUC/MIC correlated well with IE (r2 = 0.98 in both cases) in a species-independent fashion. Unlike Teff or log AUC/MIC, a specific relationship between IE and log AUCeff was inherent in each strain. Although each IE and log AUCeff plot was fitted by linear regression (r2 = 0.97 to 0.99), these plots were not superimposed and therefore are bacterial species dependent. Thus, AUC/MIC and Teff 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. Teff 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.

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

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 (microg . h/ml)/(microg/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 [IE]). 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 IE and log AUC/MIC were established for TR and CI against three bacteria: Escherichia coli (MIC of TR [MICTR] = 0.25 microg/ml; MIC of CI [MICCI] = 0.12 microg/ml), Pseudomonas aeruginosa (MICTR = 0.3 microg/ml; MICCI = 0.15 microg/ml), and Klebsiella pneumoniae (MICTR = 0.25 microg/ml; MICCI = 0.12 microg/ml). The slopes and intercepts of these relationships differed for TR and CI, and the IE-log AUC/MIC plots were not superimposed, although they were similar for all bacteria with a given antibiotic. By using the relationships between IE 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 (microg . h/ml)/(microg/ml)] was approximately twofold lower than that for CI. Based on the IE-log AUC/MIC relationships, the respective dose (D)-response relationships were reconstructed. Like the IE-log AUC/MIC relationships, the IE-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 IE 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.

Inter- and intraquinolone predictors of antimicrobial effect in an in vitro dynamic model: new insight into a widely used concept

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 (microg x h/ml)/(microg/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 (Teff). Specific and nonsuperimposed IE versus log AUC/MIC or log AUCeff relationships were inherent in each of the treatments: TRO given q.d. (r2 = 0.97 and 0.96), CIP given q.d. (r2 = 0.98 and 0.96), and CIP given b.i.d. (r2 = 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-Teff relationships plotted for the different quinolones and dosing regimens were nonspecific and virtually superimposed (r2 = 0.95). Hence, AUC/MIC, AUCeff and Teff were equally good predictors of the AME of each of the quinolones and each dosing regimen taken separately, whereas Teff 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 Teff 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 (Teff). Teff may be able to accurately predict the AME of one quinolone on the basis of the data obtained for another quinolone.

Parameters of bacterial killing and regrowth kinetics and antimicrobial effect examined in terms of area under the concentration-time curve relationships: action of ciprofloxacin against Escherichia coli in an in vitro dynamic model

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.

Relationships between antimicrobial effect and area under the concentration-time curve as a basis for comparison of modes of antibiotic administration: meropenem bolus injections versus continuous infusions

In comparative studies of different modes of administration (MAs) simulated in in vitro dynamic models, only one dose of antibiotic is usually mimicked. Such an experimental design can provide a prediction of the antimicrobial effect (AME) of a given combination of drug, clinical isolate, and infection site, but may be inappropriate for accurate comparison of MAs. An alternative design providing comparison of different MAs with various antibiotic doses in a wide range and with evaluation of the respective relationships between AME and the AUC was proposed and examined. Two series of meropenem pharmacokinetic profiles, i.e., monoexponentially decreasing concentrations (bolus doses) and constant concentrations (6-h continuous infusion), were in vitro simulated. The simulated initial concentrations (Co[from 0.62 to 48 micrograms/ml]) and steady-state concentrations (Css[from 0.016 to 8 micrograms/ml]) were chosen to provide similar AUC for 0 to 6 h (AUC0-6) ranges for both MAs (from 0.070 to 50.0 micrograms.h/ml and from 0.09 to 48.0 micrograms.h/ml, respectively). The AME of meropenem on Staphylococcus aureus ATCC 25923 (MIC, 0.06 micrograms/ml) was determined at each time (t) point as a difference (E) between the logarithms of viable counts (N) in the control cultures without antibiotic (NC) and in cultures exposed to antibiotics (NA). Time courses of E observed at different Co of Css levels were compared in terms of the areas under the E-t curves (ABBCt). The finite values of the ABBCt observed by the end of the 6 -h observation period, which are equivalent to the area between bacterial count-time curves observed in the absence and presence of antibiotic (ABBC), were plotted versus the respective AUCs produced by each of the MAs. The ABBC versus AUC curves had a similar pattern: a plateau achieved at high AUCs followed by a steep rise in ABBC at relatively low AUCs was inherent in both of the MAs. The superiority of bolus dosing over the infusions could be documented only for meropenem concentrations below the MIC. At higher Co or Css (i.e., at an AUC of > or = 0.4 micrograms.h/ml), the ABBC versus AUC curves plotted for each of the MAs could practically be superimposed. On the whole, both MAs appeared to be equiefficient in terms of the ABBC. These results suggest that AUC analysis of the AME may be a useful tool for comparing different MAs. Such comparative studies should be designed in a manner that provides the use of similar AUC ranges, since the AUC may be considered as a common pharmacokinetic denominator in comparing one MA or dosing regimen to another.

Net effect of inoculum size on antimicrobial action of ampicillin-sulbactam: studies using an in vitro dynamic model

To examine the predictable effect of inoculum size on the kinetics of the antimicrobial action of ampicillin-sulbactam, five TEM-1 beta-lactamase-producing Escherichia coli strains were studied in an in vitro dynamic model at two different initial inocula (N0S). All bacteria were exposed to ampicillin-sulbactam in a simulated system reflecting the pharmacokinetic profiles in human tissue after the administration of a single intravenous dose of ampicillin (2 g) plus sulbactam (1 g). Each strain was studied at low (4.0 to 5.2 log CFU/ml) and high (5.0 to 7.1 log CFU/ml) N0S. Despite pronounced differences in susceptibilities, the patterns of the killing curves observed with a given strain at different N0S were similar. As expected, viable bacterial counts increased with inoculum size. Striking visual contrasts in the respective curves for each organism were reflected by the area under the bacterial count-time curve (AUBC) but not by the difference between the N0 and the lowest bacterial counts (Nmin) at the nadir of the killing curve: the N0-associated changes in the AUBC on average were 75%, versus 2.5% for log N0--logNmin. To examine qualitative differences in antimicrobial effects at different N0S (i.e., the net effect of the inoculum), the difference in the high and low N0S was subtracted from each point on the killing curve obtained at the higher N0 for each strain. These adjusted curves were virtually superimposable on the observed killing curves obtained at the lower N0. Moreover, by using adjusted data, the AUBC values were similar at the two inocula, although slight (average, 11%) but systematic increases in the AUBC occurred at high N0S. Thus, there was only a weak net effect of inoculum size on the antibacterial effect of ampicillin-sulbactam. Due to similar slopes of the AUBC-log N0 plots, the antibacterial action at different N0S may be easily predicted by an approximate equation; the predicted AUBCs were unbiased and well correlated with the observed AUBCs (r = 0.997). Compiled data obtained with normalized AUBCs for different strains at different N0S yielded a positive correlation (r = 0.963) between the N0-normalized AUBC and the MIC of ampicillin-sulbactam. The adjustment and normalization procedure described might be a useful tool for revealing the net effect of the inoculum and to predict the inoculum effect if there are no qualitative differences in antimicrobial action at different inocula.

Predictors of effect of ampicillin-sulbactam against TEM-1 beta-lactamase-producing Escherichia coli in an in vitro dynamic model: enzyme activity versus MIC

The clinical outcome in patients treated with ampicillin-sulbactam may not always be predictable by disc susceptibility testing or with the MIC as determined with a constant level (4 micrograms/ml) of the beta-lactamase inhibitor (MIC1). The enzyme activities (EA) and the MICs estimated at a constant ratio of ampicillin to sulbactam of 2:1 (MIC2) for 15 TEM-1 beta-lactamase-producing strains of Escherichia coli were examined as alternatives to MIC1 as predictors of the antibacterial effects of this combined drug as studied in an in vitro model which simulates ampicillin-sulbactam pharmacokinetic profiles observed in human peripheral tissues. Integral parameters describing the area under the bacterial count-time curve (AUBC), the area between the normal growth curve, and the killing curve of bacteria exposed to antibiotic (ABBC), and the second parameter expressed as a percentage of its maximal hypothetical value (ABBC/ABBCmax) were calculated. All three parameters correlated well with EA (AUBC, r = 0.93; ABBC, r = -0.88; ABBC/ABBCmax, r = -0.91) and with MIC2 (r = 0.94, -0.94, and -0.95, respectively) but not with MIC1. Both EA and MIC2 can be considered reliable predictors of the antibacterial effect of ampicillin-sulbactam in an in vitro model. These correlations suggest that in vitro kinetic-dynamic models might be useful to reexamine established susceptibility breakpoints obtained with data based on the MIC1 (MICs obtained with constant levels of beta-lactamase inhibitors). These data also suggest that quantitative determinations of bacterial beta-lactamase production and MICs based on the component concentration ratio observed in vivo might be useful predictors of the effect of ampicillin-sulbactam and other beta-lactam-inhibitor combinations.