JAC Advance Access originally published online on October 5, 2006
Journal of Antimicrobial Chemotherapy 2006 58(6):1185-1192; doi:10.1093/jac/dkl387
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Testing the mutant selection window hypothesis with Staphylococcus aureus exposed to daptomycin and vancomycin in an in vitro dynamic model
1 Department of Pharmacokinetics & Pharmacodynamics, Gause Institute of New Antibiotics Russian Academy of Medical Sciences, 11 Bolshaya Pirogovskaya Street, Moscow, 119021 Russia 2 Mount Auburn Hospital, Harvard Medical School Cambridge, MA, USA
*Corresponding author. Tel: +7-495-708-3341; Fax: +7-495-245-0295; E-mail: firsov{at}dol.ru
Received 24 April 2006; returned 14 June 2006; revised 13 August 2006; accepted 2 September 2006
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Abstract |
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Objectives: To extend the mutant selection window (MSW) hypothesis to include antibiotics in addition to fluoroquinolones, the pharmacodynamics of daptomycin (DAP) and vancomycin (VAN) and their ability to prevent the selection of resistant Staphylococcus aureus were studied in an in vitro model that simulates antibiotic concentrations below the MIC, between the MIC and the mutant prevention concentration (MPC), and above the MPC.
Methods: Two clinical isolates of S. aureus, S. aureus 866 (MICDAP 0.35, MICVAN 0.7, MPCDAP 1.1, MPCVAN 2.4 mg/L) and S. aureus 10 (MICDAP 1.1, MICVAN 1.3, MPCDAP 5.5, MPCVAN 11 mg/L), were exposed for five consecutive days to once-daily daptomycin (half-life 9 h) and twice-daily vancomycin (half-life 6 h) at the ratio of 24 h area under the concentration–time curve (AUC24) to MIC that varied over a 16- to 30-fold range. The cumulative antimicrobial effect was expressed by its intensity (IE). Changes in susceptibility and numbers of surviving organisms on agar plates containing 2x and 4x MIC of daptomycin or vancomycin were monitored daily.
Results: The IE-log AUC24/MIC plots were bacterial strain- and antibiotic-independent. This allowed combination of data obtained with both antibiotics and both organisms. Based on the sigmoid relationship between IE and the AUC24/MIC (r2 = 0.9), the antistaphylococcal effect of the therapeutic doses of daptomycin (4 and 6 mg/kg) against a hypothetical S. aureus with MIC equal to the MIC90 (AUC24/MIC90 380 and 570 h, respectively) was predicted to be similar to the effect of two 1 g doses of vancomycin given at a 12 h interval (AUC24/MIC90 200 h). AUC24/MIC relationships of the final-to-initial MIC ratio and logarithm of the ratio of maximal-to-initial numbers of organisms resistant to 2x and 4x MIC of daptomycin or vancomycin were bell-shaped and bacterial strain- and antibiotic-independent. Based on these relationships, an AUC24/MIC ratio that protects against the selection of resistant mutants was predicted at 
200 h. This protective value is less than the AUC24/MIC90s provided by the 4 mg/kg dose and considerably less than the 6 mg/kg dose of daptomycin, but it is close to the AUC24/MIC90 provided by two 1 g doses of vancomycin.
Conclusions: 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.
Keywords: S. aureus , pharmacodynamics , resistance , in vitro model
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Introduction |
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The hypothesis of the mutant selection window (MSW), that is the concentration range from the MIC to the mutant prevention concentration (MPC), within which it is proposed that resistant mutants are enriched or selected1 has passed the test successfully with Staphylococcus aureus2–6 and Streptococcus pneumoniae7 exposed to fluoroquinolones in dilution2,4–6 and hollow-fibre in vitro models.3,7 Despite the use of different dynamic models, the most pronounced loss in susceptibility of antibiotic-exposed organisms and the enrichment of resistant mutants were reported over a comparable range of simulated ratios of 24 h area under the concentration–time curve (AUC24) to MIC (from 25 to 100–150 h), when antibiotic concentrations fell into the MSW for most of the dosing interval.
To extend the MSW hypothesis beyond fluoroquinolones, two strains of S. aureus were exposed to daptomycin and vancomycin pharmacokinetics at concentrations below the MICs, between the MICs and MPCs, and above the MPCs in a dynamic model that simulates 5 day treatments with the two antibiotics.
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Antimicrobial agents, bacterial strain and susceptibility testing
Daptomycin and vancomycin were kindly provided by Cubist Pharmaceuticals, Inc. (Lexington, MA, USA) and MP Biomedicals, Inc. (Solon, CA, USA), respectively.
Two clinical isolates of S. aureus, that is S. aureus 866 (methicillin-resistant S. aureus, MRSA) and S. aureus 10 (methicillin-susceptible S. aureus, MSSA) were selected for the study. Susceptibility testing was performed in triplicate by broth microdilution techniques at 24 h post-exposure with the organism grown in Mueller–Hinton broth (MHB) at an inoculum size of 106 cfu/mL. Because daptomycin antimicrobial activity is influenced by the presence of Ca2+,8 MHB supplemented with 50 mg of Ca2+/L was used for all susceptibility studies. With S. aureus 866 and S. aureus 10, the MICs of daptomycin were estimated at 0.35 and 1.1 mg/L, respectively, and the MICs of vancomycin were 0.7 and 1.3 mg/L, respectively. To reveal possible changes in susceptibility of antibiotic-exposed staphylococci, the MICs were determined prior, during and after a 5 day treatment.
The MPCs were determined as described elsewhere.1 Briefly, the tested microorganisms were cultured in MHB and incubated for 24 h. Then, the suspension was centrifuged (4000 g for 10 min) and re-suspended in MHB to yield a concentration of 1011 cfu/mL. A series of agar plates containing known antibiotic concentrations was then inoculated with 
1011 cfu of S. aureus. The inoculated plates were incubated for 48 h at 37°C and screened visually for growth. To estimate the MPC, logarithms of bacterial numbers were plotted against antibiotic concentrations (Figure 1). MPC was taken as the point where the plot intersected the theoretical limit of detection (log cfu/mL = 1).
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The MPCs of daptomycin and vancomycin were estimated at 1.1 and 2.4 mg/L for S. aureus 866, and 5.5 and 11 mg/L for S. aureus 10, respectively.
Simulated pharmacokinetic profiles
Mono-exponential concentration decays of daptomycin (as a single dose) and vancomycin (as two 12 hourly doses) were simulated for five consecutive days with half-lives of 9 and 6 h, respectively, in accordance with values reported in humans.9–11 With S. aureus 866 exposed to both antibiotics and with daptomycin-exposed S. aureus 10, the simulated AUC24/MIC ratios were 16, 32, 64, 128 and 256 h, and with S. aureus 10 exposed to vancomycin the simulated AUC24/MIC ratios were 13, 26, 54, 108, 216 and 432 h. Peak concentrations (Cmax values) of the antibiotics were equal to the MIC, located between the MIC and the MPC, that is within the MSW, and above the MPC. With S. aureus 866 exposed to both antibiotics and daptomycin-exposed S. aureus 10, the steady-state Cmax/MIC ratios varied from 1.2 to 20.0 and with S. aureus 10 exposed to vancomycin the ratios varied from 1.5 to 50. Most experiments were performed at least in duplicate.
In vitro dynamic model
A previously described dynamic model was used in this study.12 Briefly, the model consisted of two connected flasks, one containing fresh MHB supplemented with 50 mg of Ca2+/L (daptomycin experiments) and the other with a magnetic stirrer, the central unit, with the same broth containing either a bacterial culture alone13 or a bacterial culture plus antibiotic (killing/regrowth experiments). Peristaltic pumps circulated fresh nutrient medium to the flasks and from the central 60 mL unit at a flow rate of 4.6 mL/h with daptomycin and 6.9 mL/h with vancomycin. The reliability of antibiotic pharmacokinetic simulations and the high reproducibility of the time–kill curves provided by the model have been reported elsewhere.12
The system was filled with sterile MHB and placed in an incubator at 37°C. The central unit containing 54 mL of fresh MHB was inoculated with 6 mL of an 18 h culture of S. aureus (109 cfu/mL). After a 30 min incubation daptomycin or vancomycin was injected into the central unit.
Quantification of the antimicrobial effect and susceptibility changes
In each experiment, multiple sampling of bacteria-containing medium from the central compartment was performed throughout the observation period. Samples (100 µL) were serially diluted as appropriate, and 100 µL was plated onto Mueller–Hinton agar plates. The duration of the experiments was defined in each case as the time after the last dose until antibiotic-exposed bacteria reached the maximum numbers observed in the absence of antibiotic (109 cfu/mL). The lower limit of accurate detection was 2x102 cfu/mL.
Based on time–kill data, the intensity of the antimicrobial effect (IE)13 was determined from time zero to the time at which the number of antibiotic-exposed bacteria reached 108 cfu/mL. The computation of IE is depicted graphically in Figure 2.
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To reveal possible changes in susceptibility during treatment, MICs for bacterial cultures sampled from the model were determined daily for 5 days. Moreover, each sample was plated onto agar plates containing 2x and 4x MIC of daptomycin or vancomycin.
Relationships of the antimicrobial effect to AUC24/MIC
The IE-log AUC24/MIC curve was fitted by the logistic function:
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Relationships of the emergence of resistance to AUC24/MIC
To relate both the enrichment of resistant mutants [expressed as the logarithm of the ratio of maximal number (Nmax) to the initial number (Ninitial) of organisms resistant to 2x and 4x MIC of daptomycin or vancomycin] and the increase in MIC [expressed as the final-to-initial MIC ratio (MICfinal/MICinitial)] to the simulated AUC24/MICs, a Gaussian-type function was used:
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To relate the emergence of resistance with the time during which antibiotic concentrations are within the MSW (TMSW6), the log Nmax/Ninitial or MICfinal/MICinitial ratio was fitted to the TMSWs using Equation 1, where E is either log Nmax/Ninitial or the MICfinal/MICinitial, x is TMSW and x50 is the TMSW that corresponds to (Emin + Emax)/2.
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Pharmacodynamics
The time courses of killing and regrowth of S. aureus 866 exposed to daptomycin and vancomycin are shown in Figure 3. The lowest simulated AUC24/MIC ratio (16 h) with Cmax/MICs close to the MICs did not reduce the starting inoculum. The higher AUC24/MICs, with daptomycin and vancomycin Cmax/MICs exceeding the MICs over a considerable part of the dosing interval (AUC24/MIC 32 h) or the entire dosing interval (AUC24/MIC 64–256 h), resulted in pronounced reductions in bacterial counts, although regrowth occurred by the end of each treatment. In general, an increase in the simulated AUC24/MIC ratio led to the lower minimal numbers of surviving organisms and to later regrowth. Similar AUC24/MIC-dependent killing was observed with daptomycin- and vancomycin-exposed S. aureus 10 (data not shown).
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Plotting IE versus log AUC24/MIC (Figure 4) gives a sigmoid curve that is not specific for antibiotic or for bacterial strain: Equation 1 fits combined data obtained with each antibiotic–pathogen pair. Given the strain-independent pattern of the IE-log AUC24/MIC relationship, it can predict daptomycin and vancomycin effects on a hypothetical strain of S. aureus, for example, a strain with MICs equal to the MIC90s (1 and 2 mg/L, respectively).14 As seen in the figure, at the clinically achievable AUC24/MIC90 ratios (380 and 570 h for 4 and 6 mg/kg daptomycin, respectively, and 200 h for 2x 1 g vancomycin), the predicted effects of both antibiotics are quite similar.
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Emergence of resistance
Figures 5 and 6 present the time courses of numbers of surviving bacteria on daptomycin- or vancomycin-containing agar plates (2x and 4x MIC) and the concomitant changes in susceptibility at antibiotic concentrations within or out of the MSWs over most of the dosing interval (three of five or six dosing regimens simulated for each antibiotic–pathogen pair are shown). As seen in Figure 5, at both the lowest (AUC24/MIC 16 h) and the highest (AUC24/MIC 256 h) concentrations, no mutant of S. aureus 866 resistant to 2x and 4x MIC of daptomycin or vancomycin was selected, and no loss in susceptibility occurred. At AUC24/MIC of 32 h, when antibiotic concentrations fell into the MSWs, the population was enriched with resistant mutants, and the susceptibility of bacteria sampled from the model decreased gradually. Similar data were obtained with S. aureus 10 (Figure 6): no selection of resistant mutants at AUC24/MIC of 13–16 h and 216–256 h in contrast to the pronounced selection at AUC24/MIC of 54–64 h.
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Based on data obtained over the entire simulated AUC24/MIC ranges (five or six AUC24/MICs with each antibiotic–pathogen pair), ratios of the maximal to the initial bacterial numbers on plates containing 2x or 4x MIC and ratio of the final-to-initial MICs were plotted against the simulated AUC24/MICs. As seen in Figure 7, both log Nmax/Ninitial and MICfinal/MICinitial ratios were AUC24/MIC-dependent in a bell-shaped fashion. The respective Gaussian relationships (Equation 2) were not specific for antibiotic or bacterial strain (r2s 0.64–0.68). Moreover, regardless of the method used to demonstrate resistance (population analysis or susceptibility testing), maximal enrichment of resistant mutants and maximal loss in susceptibility occurred at similar AUC24/MIC ratios (50 and 48 h, respectively). Furthermore, an AUC24/MIC ratio that protects against the selection of resistant mutants appears to be the same for both antibiotics:
200 h. This value corresponds to the clinically achievable AUC24/MIC90 provided by 2x 1 g vancomycin (200 h) but it is 2- to 3-fold less than what is provided by 4 and 6 mg/kg daptomycin (380 and 570 h, respectively).
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To relate the observed selection of resistant staphylococci or the lack of such selection to the time period when antibiotic concentrations are within the MSW, log Nmax/Ninitial (on plates containing 2x MIC of daptomycin or vancomycin) and MICfinal/MICinitial were plotted against TMSW (Figure 8). TMSW plots were sigmoid and fitted by Equation 1 with smaller r2s (0.5–0.6) than those established for the respective AUC24/MIC plots. An even looser correlation was established between TMSW and log Nmax/Ninitial on plates containing 4x MIC of antibiotic (r2 = 0.3; data not shown).
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Discussion |
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The MSW hypothesis was shown to be relevant to the studied lipopeptide and glycopeptide antibiotics: both selection of organisms resistant to 2x and 4x MIC of daptomycin or vancomycin and decreased susceptibility of staphylococci occurred at antibiotic concentrations that fell into the MSWs. Antibiotic- and bacterial strain-independent bell-shaped relationships between MICfinal/MICinitial and AUC24/MIC were similar to those reported in in vitro studies with fluoroquinolones5–7 although AUC24/MIC plots of resistance of S. aureus to daptomycin and vancomycin were more scattered. However, maximal enrichment of resistant mutants and significant loss in susceptibility of daptomycin- or vancomycin-exposed S. aureus were observed at AUC24/MIC ratios (30–60 h) that are comparable with those reported with the fluoroquinolones and S. aureus: from 25 to 100 h6 and from 30 to 150 h3 for ciprofloxacin, from 25 to 100 h for gatifloxacin,4,6 levofloxacin5,6 and moxifloxacin6 and from 60 to 120 h for ABT-492,5 but not with findings reported in a recent study with levofloxacin-exposed staphylococci,15 where the enrichment of resistant mutants was observed only at an AUC24/MIC of 30 h but not at 60 h.
Recently, the ratio of AUC to MPC of ciprofloxacin was suggested to be a better predictor of the enrichment of resistant Escherichia coli than AUC/MIC,16 although this statement was not entirely supported by the presented data. In the present study, neither MICfinal/MICinitial (Figure 9) nor Nmax/Ninitial (data not shown) correlated with the AUC24/MPC ratio. Further studies examining AUC24/MPC relationships of resistance with additional antibiotics are needed to compare different predictors of resistant mutant enrichment.
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Unlike our earlier findings with fluoroquinolones,6 less accurate relationships were established in this study when log Nmax/Ninitial or MICfinal/MICinitial were plotted against the TMSW. At first glance, this is consistent with the unsuccessful attempts to relate resistance of ciprofloxacin-exposed S. aureus to TMSW as reported by Campion et al.3 However, this similarity is more apparent than real. Looking closely at the MICfinal/MICinitial versus TMSW data reported in the ciprofloxacin study, a reasonable TMSW relationship of resistance could be seen in simulations of conventional dosing regimens but not continuous infusions (Cmax-to-trough ratios of 6.6 and unity, respectively). It is possible that these data cannot be combined because the enrichment of the resistant mutants might depend on the shape of the simulated pharmacokinetic profile. In our study that simulated normal and impaired gatifloxacin elimination,4 more pronounced loss in susceptibility of S. aureus was observed when concentrations oscillated significantly (Cmax/trough ratio of 10.8) compared with less oscillating concentrations (Cmax/trough ratio of 1.7). On the other hand, the simulated constant ciprofloxacin concentrations were so close to the MIC (antibiotic concentrations exceeded the MICs by a factor of 1.2) that the actual TMSW might better be described equal to zero rather than 100%. Another study that also declared the inability of TMSW to predict the selection of resistant staphylococci based their conclusions on single bolus dose or infusion of ciprofloxacin.16 In this design the true TMSW relationships with resistance may not be demonstrated. Further studies that simulate multiple-dose pharmacokinetics are needed to better examine TMSW and other potential in vitro predictors of resistant mutant selection.
AUC24/MIC relationships of the IE and Nmax/Ninitial or MICfinal/MICinitial ratios established in this study predict similar effects of clinical doses of both antibiotics and a greater ability of daptomycin to prevent the selection of resistant staphylococci relative to vancomycin. However, these predictions ignore the different protein binding of daptomycin (92%)9 and vancomycin (from 8% to 70%, average 42%17 and from 20% to 80%, average 55%18). It would seem that this factor could be easily accounted for if clinically achievable AUC24/MIC90 ratios that correspond to total concentrations (380 h for 4 mg/kg daptomycin, 570 h for 6 mg/kg daptomycin and 200 h for 2x 1 g vancomycin) were simply replaced by the respective ratios calculated by multiplying AUC24/MIC90s by the free fractions determined in equilibrium dialysis or ultrafiltration studies. Assuming daptomycin binding of 92%9 and vancomycin binding of 42%,17 the respective AUC24,free/MIC90s in this scenario would be as low as 30–45 h and 116 h. As a result, the predicted effects of daptomycin on susceptible and resistant sub-populations would be much less than those based on total concentrations.
However, recent studies that simulate antibiotic concentrations with and without albumin or blood serum19–23 raise questions of whether the described method to consider protein-binding effects is correct. For example, in an in vitro study with seven differentially bound antibiotics (from 2% to 94%), simulated ‘free’ concentrations, that is those derived from reported percentage of protein binding, exhibited much less killing of S. aureus than their total concentrations in the presence of albumin.23 In a previous study, no protein-binding effects on the killing of S. aureus, S. pneumoniae and E. coli were found with three differentially bound quinolones in a static in vitro study.22 In another static study that exposed the same bacterial species plus Klebsiella pneumoniae to 95% bound ertapenem and faropenem,21 their antibacterial activity was dramatically decreased in the presence of 50% human serum. These effects were observed at low but not at higher antibiotic concentrations, which, at least with S. aureus, were still much lower than clinically achievable values making the clinical relevance of these reported effects unclear. In addition, another study reported only minor effects of bovine albumin on the killing of S. pneumoniae and E. coli exposed to constant concentrations of 95–98% bound ceftriaxone.20 Recently, only minimal, if any, differences in the antistaphylococcal effects of 94%-bound telavancin were found in the presence or absence of albumin.19
Unfortunately, several reported in vitro studies with highly bound daptomycin24–30 have not resulted in a better understanding of protein-binding effects on bacterial killing and susceptibility. For example, killing of daptomycin-exposed S. aureus at simulated total concentrations plus albumin was less than without albumin but greater than that with simulated ‘free’ concentrations.28 In another study with the same bacterial strain, simulated ‘free’ concentrations were more efficient than simulated total concentrations in the presence of albumin.24 Therefore, insistence on simulations of ‘free’ daptomycin concentrations is not well-founded. Moreover, a 4- to 5-fold increase in daptomycin MICs determined in albumin-supplemented broth or human serum31 suggests that daptomycin is more active than might be predicted from reported free fractions. On the other hand, the difference between daptomycin MICs determined with and without albumin should not be the basis for estimating the ‘effective value’ of protein binding and the respective correction of the total concentration-based AUC24/MIC relationships of bacterial killing and resistance. For example, albumin-induced increases in daptomycin MICs reported with various strains of S. aureus varied from 2- to 16-fold28 and from 4- to 32-fold.27
Taken together these findings suggest that attempts to interpret the pharmacodynamics of antibiotics using reported percentages of protein binding are inappropriate and fraught with serious underestimation of the true antimicrobial activity, both in vitro and in vivo. For example, an attempt in infected neutropenic mice to relate the antistaphylococcal effects of free concentrations of telavancin calculated from reported percentages of protein binding was disappointing: pronounced reductions in bacterial titres were observed at ‘free’ concentrations below the MIC throughout the entire dosing interval (time above MIC of zero).32
As for in vitro studies that examine bacterial killing kinetics in the presence of serum, albumin and/or other macromolecules, the definitive methodology is still to be established. Until then, incorrect considerations of protein-binding effects might be even more dangerous than ignoring this factor.
Turning back to the primary goal of this study, we can conclude that data obtained with daptomycin- and vancomycin-exposed S. aureus are in support of the MSW hypothesis. Also, this study suggests that an antibiotic- and bacterial strain-independent relationship exists between an integral index of the entire antimicrobial effect, IE and the AUC24/MIC ratio as simulated in vitro.
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None to declare.
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Acknowledgements |
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This study was supported by Cubist Pharmaceuticals, Inc.
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1 Zhao X and Drlica K. (2001) Restricting the selection of antibiotic-resistant mutants: a general strategy derived from fluoroquinolone studies. Clin Infect Dis 33:147–56.
2 Firsov AA, Vostrov SN, Lubenko IY, et al. (2004) Prevention of the selection of resistant Staphylococcus aureus by moxifloxacin plus doxycycline in an in vitro dynamic model: an additive effect of the combination. Int J Antimicrob Agents 23:451–6.
3 Campion JJ, McNamara PJ, Evans ME. (2004) Evolution of ciprofloxacin-resistant Staphylococcus aureus in in vitro pharmacokinetic environments. Antimicrob Agents Chemother 48:4733–44.
4 Firsov AA, Vostrov SN, Lubenko IY, et al. (2004) Concentration-dependent changes in the susceptibility and killing of Staphylococcus aureus in an in vitro dynamic model that simulates normal and impaired gatifloxacin elimination. Int J Antimicrob Agents 23:60–6.
5 Firsov AA, Vostrov SN, Lubenko IY, et al. (2004) ABT492 and levofloxacin: comparison of their pharmacodynamics and their abilities to prevent the selection of resistant Staphylococcus aureus in an in vitro dynamic model. J Antimicrob Chemother 54:178–86.
6 Firsov AA, Vostrov SN, Lubenko IY, et al. (2003) In vitro pharmacodynamic evaluation of the mutant selection window hypothesis using four fluoroquinolones against Staphylococcus aureus. Antimicrob Agents Chemother 47:1604–13.
7 Zinner SH, Lubenko IY, Gilbert D, et al. (2003) Emergence of resistant Streptococcus pneumoniae in an in vitro dynamic model that simulates moxifloxacin concentrations inside and outside the mutant selection window: related changes in susceptibility, resistance frequency and bacterial killing. J Antimicrob Chemother 52:616–22.
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20 Schmidt S, Burkhardt O, Sahre M, et al. (2006) Experimental pitfalls in protein binding measurements. Clin Microbiol Infect 12:Suppl 4, 1541.
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22 Rubinstein E, Diamantstein L, Yoseph G, et al. (2000) The effect of albumin globulin, pus and dead bacteria in aerobic and anaerobic conditions on the antibacterial activity of moxifloxacin, trovafloxacin and ciprofloxacin against Streptococcus pneumoniae, Staphylococcus aureus and Escherichia coli. Clin Microbiol Infect 6:678–81.
23 Wiedemann B and Fuhst C. (2004) Revising the effect of protein binding on the pharmacodynamics of antibiotics. Abstracts of the Forty-fourth Interscience Conference on Antimicrobial Agents and ChemotherapyWashington, DC(American Society for Microbiology, Washington, DC, USA) Abstract A-1466.
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30 Garrison MW, Vance-Bryan K, Larson TA, et al. (1990) Assessment of effects of protein binding on daptomycin and vancomycin killing of Staphylococcus aureus by using an in vitro pharmacodynamic model. Antimicrob Agents Chemother 34:1925–31.
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R. E. Warren Daptomycin in endocarditis and bacteraemia: a British perspective J. Antimicrob. Chemother., November 1, 2008; 62(suppl_3): iii25 - iii33. [Abstract] [Full Text] [PDF]
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D. M. Livermore Future directions with daptomycin J. Antimicrob. Chemother., November 1, 2008; 62(suppl_3): iii41 - iii49. [Abstract] [Full Text] [PDF]
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X. Zhao and K. Drlica A unified anti-mutant dosing strategy J. Antimicrob. Chemother., September 1, 2008; 62(3): 434 - 436. [Abstract] [Full Text] [PDF]
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A. A. Firsov, I. Y. Lubenko, M. V. Smirnova, E. N. Strukova, and S. H. Zinner Enrichment of Fluoroquinolone-Resistant Staphylococcus aureus: Oscillating Ciprofloxacin Concentrations Simulated at the Upper and Lower Portions of the Mutant Selection Window Antimicrob. Agents Chemother., June 1, 2008; 52(6): 1924 - 1928. [Abstract] [Full Text] [PDF]
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S. H. Zinner, D. Gilbert, I. Yu. Lubenko, K. Greer, and A. A. Firsov Selection of linezolid-resistant Enterococcus faecium in an in vitro dynamic model: protective effect of doxycycline J. Antimicrob. Chemother., March 1, 2008; 61(3): 629 - 635. [Abstract] [Full Text] [PDF]
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B. Quinn, S. Hussain, M. Malik, K. Drlica, and X. Zhao Daptomycin inoculum effects and mutant prevention concentration with Staphylococcus aureus J. Antimicrob. Chemother., December 1, 2007; 60(6): 1380 - 1383. [Abstract] [Full Text] [PDF]
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S. K. Olofsson, L. L. Marcusson, A. Stromback, D. Hughes, and O. Cars Dose-related selection of fluoroquinolone-resistant Escherichia coli J. Antimicrob. Chemother., October 1, 2007; 60(4): 795 - 801. [Abstract] [Full Text] [PDF]
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D. Sevillano, M. J. Gimenez, L. Alou, L. Aguilar, F. Cafini, M. Torrico, N. Gonzalez, O. Echeverria, P. Coronel, and J. Prieto Effects of human albumin and serum on the in vitro bactericidal activity of cefditoren against penicillin-resistant Streptococcus pneumoniae J. Antimicrob. Chemother., July 1, 2007; 60(1): 156 - 158. [Abstract] [Full Text] [PDF]
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