TY - JOUR
AU1 - Wright, David, H.
AU2 - Brown, Gigi, H.
AU3 - Peterson, Marnie, L.
AU4 - Rotschafer, John, C.
AB - Abstract Pharmacodynamics provides a rational basis for optimizing dosing regimens by describing the relationship between drug, host and antimicrobial effect. The successful identification of meaningful pharmacodynamic outcome parameters can, therefore, greatly assist clinicians in making objective prescribing decisions rather than relying on static in vitro MIC data. While pharmacodynamic outcome parameters have been proposed for select antimicrobial agents, their clinical application remains to be defined fully. Quinolone antibiotics are generally considered to have concentration-dependent bactericidal activity and peak/MIC and AUC/MIC ratios have been identified as possible pharmacodynamic predictors of clinical and microbiological outcome as well as the development of bacterial resistance. Investigators have suggested that AUC/MIC ratios of 100–125 or peak/MIC ratios of >10 are required to predict clinical and microbiological success and to limit the development of bacterial resistance. These conclusions are derived primarily from studies of Gram-negative bacteria, and recent data suggest that these ratios may not be applicable for Streptococcus pneumoniae, where an AUC/MIC ratio of <40 appears to be a more accurate predictor. There is considerable variation in pharmacodynamic calculations and outcome parameters appear to be quinolone- and pathogen-specific. Additional prospective clinical research is needed to characterize quinolone pharmacodynamic parameters and answer unresolved questions regarding optimal pharmacodynamic outcome predictors for Gram-positive bacteria, anaerobes and atypical respiratory pathogens. Introduction One of the greatest factors in the reduction in morbidity and mortality of bacterial infections achieved in the last 50 years has been the discovery, refinement and clinical use of antibiotics. Indeed, clinicians have become so comfortable with these agents that one of society’s looming problems is antimicrobial overuse and the subsequent dilemma of increasing resistance. As a result of the lack of objective clinical information, the selection of an appropriate antimicrobial regimen is often difficult. Initial antibiotic therapy is, by definition, empirical and use of broad-spectrum agents, such as fluoroquinolones, or combination therapy is sometimes justified. Bacterial culture and antibiotic susceptibility testing are time consuming and cannot provide useful data at the initiation of antimicrobial therapy. Furthermore, there is considerable debate about whether the results of such studies represent accurately the clinical situation, since these data are obtained in a static in vitro setting. Meaningful outcome parameters that allow the prescriber to evaluate the clinical situation objectively and to determine whether monotherapy and/or standard dosing is adequate to treat the infection successfully do not currently exist. The prescribing of antibiotics therefore still remains as much an art as a science. The evolution of pharmacokinetics and pharmacodynamics During the modern antibiotic era, bacterial behaviour and antimicrobial pharmacology have been extensively studied and described. Significant strides have been made in delineating the many complex interactions that occur between antibiotics and bacteria. Understanding the sequential actions of antibiotics and the subsequent responses by bacteria are integral steps in delineating the time–activity profile of antibiotic dosing. With a fundamental understanding of these interactions, clinicians may be able to predict therapeutic responses more accurately based on the pathogen and antimicrobial agent. In the late 1960s and early 1970s, the science of pharmacokinetics evolved and was incorporated ultimately into the new drug development process. Pharmacokinetics provided the basis to study the physiological behaviour of drugs in vivo, allowing for mathematical modelling of the relationship between drug concentration and time. Drug absorption, distribution, metabolism and excretion can be characterized using standard pharmacokinetic mathematical models. Given these pharmacokinetic data, drug dose and dosage interval can be modified based on the patient’s underlying renal and/or hepatic function, thus avoiding concentration-related adverse drug reactions. Although pharmacokinetics defines the spatial relationship between drug concentration and time, it does not consider any effects changing drug concentrations might have on bacterial pathogens. This void was filled in the 1980s with the development of pharmacodynamics, i.e. the study of the relationship between drug, host and antimicrobial effect.1 After studying the relationship between antibiotic concentration and resultant bacterial killing, investigators have suggested that antibacterials can be classified by their pattern of bactericidal activity.2–4 Antibiotics exhibiting concentration-dependent (time-independent) effects are characterized by an increased rate and extent of bacterial killing over a wide range of concentrations. Additionally, persistent antibiotic effects [such as the post-antibiotic effect (PAE) and sub-MIC effects] tend to be prolonged and related to concentration for antibiotics characterized by concentration-dependent killing. For concentration-independent (time-dependent) antibiotics, once a threshold antibiotic concentration is achieved, the rate and extent of bacterial killing remain relatively constant over increasing antibiotic concentrations. This saturation of bactericidal activity typically occurs at low multiples (four to five times) of the MIC. Fluoroquinolones, aminoglycosides and metronidazole have concentration-dependent bactericidal activity while β-lactams and vancomycin are concentration-independent. Understanding the interactions between bacteria and clinically relevant drug concentrations can provide critical insight into how to administer optimally a particular antibiotic against a specific pathogen.1–4 Pharmacodynamics is now emerging as an extremely important tool in deciding which antibiotic to use,5 enabling clinicians to make objective rather than subjective prescribing decisions. Clearly, such data are not yet completely available or accepted universally. This review will focus on the pharmacodynamics of fluoroquinolones. Our purpose is to review critically the presently available data, identify shortcomings that may exist in the understanding of fluoroquinolone pharmacodynamics—especially as applied to Gram-positive bacteria—and evaluate the potential clinical use of these data. Pharmacodynamic strategies Traditionally, antimicrobial therapy has been guided by in vitro data such as MICs and MBCs. Generally, the MIC is the only measure of pathogen susceptibility provided to clinicians. MICs are determined after exposure to a fixed concentration of an antibiotic, effectively ignoring the fact that, in vivo, antibiotic concentrations are in a constant state of flux. Pharmacodynamic parameters integrate both pharmacokinetic and MIC data. Such parameters include: (i) the time for which antibiotic concentration remains above the MIC (t > MIC) for concentration-independent antibiotics; (ii) the ratio between the peak concentration and the MIC (peak/MIC) for concentration-dependent antibiotics; and (iii) the ratio between the area under the serum concentration–time curve (AUC) and the MIC ratio (AUC/MIC) for concentration-dependent or -independent antibiotics.6–10 To optimize antibiotic performance, a basic understanding of whether the drug kills in a concentration-dependent or -independent fashion is necessary. For concentration-independent agents, there are several strategies for maximizing t > MIC: (i) for antibiotics with a short serum half-life, the dose can be divided into smaller units administered more frequently (continuous iv infusion is an extension of this concept); (ii) repository dosage forms such as procaine or benzathine penicillin G have been used to promote the continuous release of antibiotic into the serum; (iii) since the 1950s, concomitant administration of probenecid in order to inhibit renal tubular secretion has been used to maintain serum penicillin concentrations;11 and (iv) active metabolites with a lower MIC than the parent compound can make it easier to keep antibiotic concentrations above the MIC, as evident with clarithromycin. For concentration-dependent antimicrobials, the time of exposure may not be as important as its intensity. Options here are limited to the maximum tolerated level. Another therapeutic option is the strategic combination of two antimicrobials in an attempt to generate a synergic effect. While this is often attempted, antibiotic synergy is a very specific situation that must be proven for each particular pathogen and the two selected antimicrobial agents. Even in vitro testing in the laboratory sometimes provides conflicting data when different measures of synergy are used.12 Although there are limited data defining optimal antibiotic combinations with fluoroquinolones, some general guidelines might be considered when attempting to produce synergy. Using antibiotics of the same chemical class should probably be avoided, as should use of two concentration-dependent antibiotics or two concentration-independent antibiotics.13 The quinolone antibiotics The quinolones are a group of synthetic antimicrobials characterized by a broad spectrum of activity, favourable pharmacokinetic profiles, a unique mechanism of action and (for some) availability in both oral and parenteral dosage forms.14 The first quinolone antibiotics, nalidixic acid, cinoxacin and oxolinic acid, were introduced in the 1960s for treating urinary tract infections caused by Gram-negative bacilli. The addition of a fluorine substituent to the main quinolone ring substantially widened their spectrum of antibacterial activity. Numerous new fluoroquinolones have been introduced in the past 5 years, e.g. moxifloxacin and gatifloxacin, and other compounds are on the horizon (gemifloxacin, sitafloxacin). Although not all-inclusive, Table I provides a summary of fluoroquinolones commonly used in the USA and Europe. As a class, the fluoroquinolones are broad-spectrum agents; they are uniformly active against the Enterobacteriaceae as well as many strains of Listeria spp., Chlamydia spp. and mycobacteria. The newer quinolone agents have enhanced activity against staphylococci, streptococci and anaerobes.15–17 Bacterial susceptibility to the quinolones remains generally good, although concerns about emerging resistance have recently surfaced.18–20 Table II summarizes the pharmacokinetic profiles of several quinolone agents. The majority of quinolones are cleared by the kidney, consequently achieving high urinary tract concentrations but requiring dosing adjustments in patients with renal insufficiency (trovafloxacin and moxifloxacin are exceptions). Apart from norfloxacin, the quinolones are characterized by very high bioavailability (generally 70–100%) and excellent tissue penetration into tissues such as skin, lung, bone and prostate. The newer quinolone agents are characterized by extended serum half-lives, which, combined with their concentration-dependent activity, allows for once-daily dosing.14,21 As a result of their favourable pharmacology, the quinolones have become primary agents for a wide range of indications, including respiratory, genitourinary, skin and soft-tissue infections.14,21–24 Fluoroquinolone pharmacodynamic investigations Many of the assumptions made about fluoroquinolone pharmacodynamics have been extrapolated from pharmacodynamic principles developed for the aminoglycosides (which also have concentration-dependent activity).1,21 From these investigations, researchers have identified peak/ MIC and AUC/MIC ratios as potential predictors of outcome for concentration-dependent agents.25–27 Recently, several, predominantly retrospective, studies have attempted to define optimal dosing regimens for fluoroquinolones and to determine whether there is a generic pharmacodynamic predictor of clinical response for the fluoroquinolones, regardless of the pathogen or disease state. Table III is a listing of pivotal studies conducted specifically to characterize fluoroquinolone pharmacodynamics. The studies are listed in chronological order to provide an appreciation of the progression of pharmacodynamic research over the past decade. These studies can be analysed according to whether they were in vitro models, animal infection models or human clinical trials. Typically, in vitro evaluations generate a hypothesis, which is in turn confirmed or disproved by studies in animals and clinical trials. There appears to be general agreement between the pharmacodynamic data generated in vitro and in animals, and the limited human data available. In vitro model investigations In vitro studies allow the researcher to examine the direct relationship between dosing regimens and bacteriological effect. These systems allow independent modification of drug concentration, dosing schedules, bacterial inoculum, simulated drug half-life and environmental conditions (e.g. aerobic compared with anaerobic). These in vitro modelling systems can provide detailed pharmacodynamic information on the direct quinolone–organism interaction and assist in designing more effective animal models and clinical trials. However, caution should be used in extrapolating data from in vitro models to in vivo situations, as the former lack a functional immune system and other variables found in vivo, and generally are studied for only limited periods. In 1987, Blaser and colleagues27 suggested that peak/ MIC ratios were important parameters in predicting the clinical use of quinolone antibiotics. Using an in vitro pharmacodynamic model, they examined netilmicin and enoxacin activity against Pseudomonas aeruginosa, Klebsiella pneumoniae, Escherichia coli and Staphylococcus aureus. Bacterial regrowth was observed within 24 h unless the peak/MIC ratio exceeded 8. Furthermore, the regrowing bacteria had four- to eight-fold higher MICs, and little or no bactericidal effect occurred after subsequent antimicrobial dosing. The authors concluded that peak/MIC ratios may be an important indicator of both clinical success and the development of bacterial resistance.27 Similarly, the selection of resistant pathogens after quinolone dosing that produced peak/MIC ratios of <8 has also been noted in an in vitro investigation of ciprofloxacin against P. aeruginosa by Dudley and colleagues.28 Madaras-Kelly et al.29 investigated the utility of AUC/ MIC ratios to describe the antimicrobial activity of ciprofloxacin and ofloxacin against three strains of P. aeruginosa in vitro. Changing peak antibiotic concentrations and half-lives but maintaining equivalent AUC values allowed the investigators to determine whether AUC/MIC or peak/ MIC was more important in antibiotic performance. Both ciprofloxacin and ofloxacin demonstrated equivalent antibacterial activity at AUC/MIC ratios of ≥100, with ratios below this breakpoint resulting in poorer outcome. These data suggested that AUC/MIC may be the most useful measure of fluoroquinolone antibacterial activity against P. aeruginosa.29 Investigating further, Firsov and colleagues30 examined ciprofloxacin and trovafloxacin activity against E. coli, P. aeruginosa and K. pneumoniae in vitro. Individual pharmacodynamic parameters (AUC/MIC, peak/MIC and t > MIC) correlated equally well with antimicrobial effect for both ciprofloxacin and trovafloxacin; no advantage of one parameter over the others was supported by the data. The authors concluded that predictors of fluoroquinolone antimicrobial effects were of two types: intraquinolone (within regimens) and interquinolone (between regimens). AUC/MIC, peak/MIC and t > MIC were suggested as intraquinolone predictors, while t > MIC was suggested to be the only interquinolone predictor that might predict accurately the antimicrobial effect of one fluoroquinolone on the basis of data obtained from another.30 The role of t > MIC as an interquinolone predictor, however, was contradicted by further work from the same laboratory studying ciprofloxacin, gatifloxacin and trovafloxacin against S. aureus.31 The authors suggested that AUC/MIC was the best predictor of fluroquinolone effect based on their work with two strains of S. aureus, adding further confusion to the picture. As an extension of these findings, Firsov and colleagues32–35 have suggested a new approach to the comparison of quinolones based on the intensity of the antimicrobial effect (IE); this is defined as the difference between the areas under the control growth and bacterial killing/ regrowth curves. To measure IE accurately, experiments must be conducted until the bacterial regrowth curve reaches the control growth curve, which can easily take 48–72 h for many of the newer quinolone agents. Each quinolone is then evaluated by the relationship between IE and the AUC/MIC ratio generated.32–35 The utility of IE appears to be quinolone specific and independent of bacterial strain.35 The IE concept relies on bacterial regrowth regardless of clinical dosing schedules and, therefore, does not conform well to in vivo situations, limiting its clinical utility. The applicability of using generic pharmacodynamic ratios as predictors of microbiological eradication of Gram-positive organisms and anaerobes was further examined in in vitro studies of levofloxacin, trovafloxacin and ciprofloxacin against strains of penicillin-resistant S. pneumoniae (PRSP), S. aureus, Bacteroides fragilis and Bacteroides thetaiotaomicron.36–39 Data from these investigations indicated that, at clinically relevant concentrations, fluoroquinolones eradicate these Gram-positive aerobes and Gram-negative anaerobes in a concentration-independent fashion and an AUC/MIC breakpoint of ≤40 appears to be most appropriate for Gram-positive organisms and anaerobes.36–39 Lacy and colleagues40 found that AUC/MIC ratios of 30–55 were effective for ciprofloxacin and levofloxacin against four strains of PRSP. These were significantly lower than the suggested breakpoint of 100–125 for P. aeruginosa,29 and suggests that fluoroquinolone pharmacodynamics are likely to be organism specific. Lister & Sanders41 examined the pharmacodynamics of ciprofloxacin, ofloxacin and trovafloxacin against eight strains of S. pneumoniae using an in vitro model. In this investigation, an AUC/MIC ratio of 49 was sufficient for ofloxacin to eradicate all eight strains. With an AUC/MIC ratio of 44 and a peak/MIC ratio of 5, ciprofloxacin eradicated five of the strains.41 The authors suggested that the inability to eradicate three of the S. pneumoniae isolates with ciprofloxacin was a result of adaptive resistance or a reversible decrease in susceptibility after initial exposure to the antibiotic. Hershberger & Rybak42 examined the bactericidal activities of six quinolones in an in vitro pharmacodynamic model of fibrin clots infected with PRSP.42 They found that trovafloxacin, gatifloxacin, clinafloxacin, sparfloxacin and levofloxacin had better activity than ciprofloxacin. Although no clear association between pharmacodynamic parameters and bacterial killing was identified, an AUC/MIC of ≤40 or a t > MIC of ≤55% was associated with decreased killing and significant bacterial regrowth.42 Coyle & Rybak43 came to similar conclusions when trovafloxacin, gatifloxacin, levofloxacin and ciprofloxacin were evaluated against two laboratory-derived ciprofloxacin-resistant S. pneumoniae isolates. During the experiment, MICs of ciprofloxacin increased from 4 and 8 mg/L to >32 mg/L, while trovafloxacin, gatifloxacin and levofloxacin MICs did not change. Bacterial regrowth and/ or resistance was associated with AUC/MIC ratios of ≤20 and peak/MIC ratios of ≤2.2.43 Further in vitro work was conducted with S. pneumoniae and levofloxacin by Ibrahim and colleagues.44 After infusing levofloxacin at a constant rate of 1, 2 or 10 × MIC for 15, 40, 65 and 100% of the dosing interval, the authors found no concentration-dependent killing and equal rates of kill with all dosing regimens. Regrowth was generally prevented, however, with AUC/MIC ratios of >30.44 Animal infection models Animal studies are effective means of examining the relationship between pharmacodynamic parameters and in vivo efficacy. They can provide confusing results, however, owing to the effects of protein binding, variable pharmacokinetics and the animal’s immune system. Additionally, in vivo data tend to be analysed in terms of discrete endpoints (success or failure, death or survival, sensitive or resistant) that do not allow specific quantitative examination of antimicrobial activity. Furthermore, experimental models, such as S. pneumoniae thigh infections, may not be representative of typical human infections. An examination of the relationship between results from in vitro and in vivo studies, however, can lead to significant conclusions because of the complementary nature of the two experimental methods. In the late 1980s, the 24 h AUC/MIC (AUC24/MIC) ratio was shown to be the pharmacodynamic parameter that best correlates with efficacy for the aminoglycosides in animal models of infection.45,46 Much of the animal data regarding fluoroquinolone pharmacodynamics have been extrapolated from these aminoglycoside data, owing to their similar concentration-dependent activity. A brief examination of the landmark trials is warranted to give a better appreciation of the correlation between in vitro, animal and human pharmacodynamic data. Craig and colleagues45,46 conducted studies of pneumonia, peritonitis and sepsis, caused by P. aeruginosa, E. coli, S. aureus and S. pneumoniae, in mice, rats and guinea pigs. The data from these investigations suggested that an AUC/ MIC ratio of c. 35 was necessary to achieve a bacteriostatic effect. This value appeared to be independent of the dosing interval or site of infection. Generally, AUC/MIC ratios of <30 were associated with >50% mortality and AUC/MIC ratios of ≥100 approached 100% survival.46 The authors suggested that fluoroquinolone serum concentrations need to average c. 4 × MIC for 24 h to result in 100% survival in experimental animal models.1,46 Craig and colleagues47 continued their investigations with tobramycin and pefloxacin against 15 Gram-negative bacilli from five different species in a murine thigh infection model. They demonstrated that the AUC/MIC ratio necessary to achieve a bacteriostatic effect in the animal models was not significantly different for pefloxacin and tobramycin, and that there was a strong linear relationship between the ratio and the results of in vitro susceptibility tests. The authors suggested that variations in antimicrobial potency could be explained by differences in pharmacokinetic and pharmacodynamic properties. Drusano and colleagues48 investigated the in vivo utility of peak/MIC ratios with lomefloxacin in a neutropenic rat model of pseudomonal sepsis. Outcome was most likely to be successful when lomefloxacin was administered at a dose sufficient to achieve peak/MIC ratios of >10. At lower doses, producing peak/MIC ratios of <10, however, the AUC/MIC ratio appeared to be linked most closely to outcome. In 1996, Vesga & Craig49 evaluated levofloxacin against six strains of PRSP in normal and neutropenic mice. Static-dose AUC/MIC ratios ranged from 22 to 59 in the animal models.50 A similar evaluation50 by Vesga and colleagues with sparfloxacin against multiple bacterial pathogens, including nine strains of S. pneumoniae, indicated that a mean AUC/MIC ratio of 29 was necessary to produce a net static effect. Further investigations with murine thigh and lung infection models have been conducted with gatifloxacin, sitafloxacin and gemifloxacin.51–53 Mean AUC/MIC ratios needed to achieve clinical efficacy were <100 for Enterobacteriaceae, S. pneumoniae and S. aureus. Specifically, for S. pneumoniae mean AUC/MIC ratios of 37, 52 and 35 were necessary to achieve a net bacteriostatic effect for sitafloxacin, gatifloxacin and gemifloxacin, respectively.51–53 Human clinical trials Relatively few human trials have been conducted to confirm the hypotheses generated from the in vitro and animal investigations. One of the first reported studies, by Peloquin et al.,10 involved iv ciprofloxacin in patients with nosocomial pneumonia. The study involved 50 patients with Gram-negative lower respiratory tract infections, half of whom had failed previous antimicrobial therapy. Elevated peak/MIC ratios and AUC/MIC ratios and extended t > MIC were associated with successful bacterial eradication from the lower respiratory tract. Additionally, patients with trough concentrations exceeding the pathogen MIC were significantly more likely to show bacterial eradication.10 As a follow-up to the above work, Forrest et al.54 examined retrospectively the pharmacodynamics of iv ciprofloxacin in human patients with moderate to severe infections, chiefly of the lower respiratory tract. An AUC24/ MIC) of 125 was considered to be the minimally effective value, with values of 250 and 500 exhibiting an increased in vivo bactericidal rate and a shorter time to bactericidal eradication. Of the 74 patients evaluated, 82% had infections attributed to Gram-negative aerobic pathogens. Approximately 15% of the patients had S. aureus infections, with nearly half of those receiving concomitant rifampicin therapy.54 A year later, Hyatt and colleagues55 attempted to confirm the utility of AUC/MIC as a generic fluoroquinolone pharmacodynamic outcome parameter by assessing the bactericidal activity of ciprofloxacin serum ultrafiltrates from five healthy volunteers against strains of S. pneumoniae, S. aureus and P. aeruginosa. The killing rates were found to be considerably more rapid for P. aeruginosa than for the Gram-positive organisms at clinically achievable concentrations. The maximal effect of ciprofloxacin, however, was seen at 15–40 × MIC for the tested Gram-positive organisms and 20–50 × MIC for P. aeruginosa. These data appear to support the premise that MIC is a useful indicator of relative ciprofloxacin susceptibility for these three bacterial species, giving credence to the utility of AUC/MIC ratios as a generic predictor.55 A very small clinical study (n = 8) evaluated the pharmacodynamics of oral grepafloxacin in treatment of acute exacerbations of chronic bronchitis,56 and found an 87.5% bacteriological cure with AUC/MIC ratios ranging from 0 to 92 for S. pneumoniae isolates. The data suggest that the minimum AUC/MIC required for the treatment of pneumococcal infections may indeed be lower than the 125 suggested for Gram-negative bacteria.54,56 In the only prospective human study conducted to date, Preston and colleagues5 suggested peak/MIC as the optimal predictive parameter for successful clinical and microbiological outcome. The authors of this study reported that a peak/MIC ratio of 12.2 correlated with a successful clinical outcome and microbiological cure in patients treated with levofloxacin for urinary tract infections, pulmonary infections and skin and soft tissue infections. They noted that the AUC/MIC ratio was highly correlated with the peak/MIC ratio (r = 0.942), but concluded from previous animal studies48 that the peak/MIC ratio was linked more closely to clinical outcome. In total, these studies evaluated 313 adult patients, 134 of whom had clinical outcome determinations and an identified microorganism with a measured MIC of levofloxacin. Five species accounted for 58% of the isolates recovered in the study: 15.7% of the patients had S. pneumoniae infections and 11.2% had S. aureus as the predominant pathogen.5 When the S. pneumoniae infections alone were examined, 19/20 were classified as clinically successful and all 20 were considered microbiologically cured. The single clinical failure was an anomaly since the MIC of levofloxacin for this pathogen was 0.15 mg/L, resulting in AUC/ MIC and peak/MIC ratios of 249 and 23, respectively. Overall, the AUC/MIC ratios were ≥50 in 17 of the 20 patients infected with pneumococci, ≥75 in 11 patients and >100 in nine patients. Therefore, even though only 45% of the cases had AUC/MIC ratios of >100, 95% clinical cure and 100% microbiological eradication rates were observed (G. L. Drusano, personal communication). As this was not a controlled in vitro investigation, the investigators were unable to take into account any effects of the host immune system, nor were they able to alter the serum concentration and half-life of levofloxacin for a rigorous evaluation of the individual contributions of peak/MIC and AUC/MIC. For these reasons, the authors’ chosen parameter, peak/MIC, may not be the optimal pharmacodynamic predictor for both Gram-positive and Gram-negative bacteria, especially when there is such covariance between AUC/MIC, peak/ MIC and t > MIC. Rather than relying on pharmacodynamic parameters to predict bacteriological or clinical response, Thomas and colleagues57 analysed the relationship of AUC/MIC and the development of bacterial resistance, similar to an earlier study.27 In a retrospective review of 107 acutely ill patients from four nosocomial lower respiratory tract infection clinical trials, the probability of developing bacterial resistance increased significantly when the AUC/MIC ratio was <100. Antimicrobials included in this analysis were cefmenoxime, imipenem, ceftazidime and ciprofloxacin. Approximately 86% of the isolates included in this analysis, however, were Gram-negative organisms. The authors note that the strongest relationship between AUC/MIC ratio and the development of bacterial resistance existed for P. aeruginosa treated with ciprofloxacin.57 These data indicate the utility of pharmacodynamic parameters in predicting the emergence of bacterial resistance rather than bacteriological or clinical cure. Limitations in the application of pharmacodynamic data There is significant agreement between pharmacodynamic data generated in vitro and those found through in vivo investigations; this correlation validates the clinical application of results obtained from in vitro pharmacodynamic models.58,59 Clearly, AUC/MIC and peak/MIC ratios are applicable for the fluoroquinolones against Gram-negative bacteria, especially P. aeruginosa. There are limited and conflicting data, however, regarding the generic predictability of these pharmacodynamic parameters for fluoroquinolones. Gram-negative bacteria are characterized by a complex outer cell wall of lipopolysaccharide, lipoprotein and phospholipid, whereas Gram-positive bacteria are relatively lipid-poor and possess a thick peptidoglycan cell wall with a layer of teichoic acid lying outside the peptidoglycan.60 Atypical pathogens have no formal cell wall structure and certain strains of bacteria can protect themselves by encapsulation, spore formation or glycocalyx production.60 When a fluoroquinolone enters a bacterial cell, various efflux proteins may be present and these can alter the amount of antibiotic that reaches the site of activity.60 Owing to these compositional and structural differences, as well as varying porin channel protein distribution, cellular uptake and affinity for DNA gyrase of fluoroquinolone antibiotics may vary considerably between species. Even with the newer fluoroquinolones, there are intrinsic differences in potency, based on MICs, between Gram-positive and Gram-negative bacteria. Accordingly, because of the large diversity among organisms, the lack of a universal pharmacodynamic predictor of antimicrobial efficacy among fluoroquinolones is unremarkable. Environmental conditions at the site of infection may also affect the intrinsic activity of an antibiotic against various pathogens. The bactericidal activity of fluoroquinolones against S. aureus, for instance, differs in aerobic and anaerobic conditions,61 and clinical staphylococcal infections may occur in an anaerobic or microaerophilic environment. The bactericidal activity of five fluoroquinolones (ciprofloxacin, ofloxacin, temafloxacin, sparfloxacin and clinafloxacin) was delayed by anaerobiosis in an in vitro pharmacodynamic system. Data from these experiments indicated differing AUC/MIC ratios for staphylococci, despite similar kill curves.61 Another complication in the application of current pharmacodynamic data is the lack of consistent methods of analysis of in vitro pharmacodynamic studies. Investigators have employed different reductions in bacterial inoculum as endpoints to assess fluoroquinolone pharmacodynamic parameters. Craig and colleagues suggest that a 1 log10 reduction in the bacterial inoculum is sufficient (equating to a net bacteriostatic effect),49–53 while others prefer a 3 log10, or 99.9%, reduction in bacterial inoculum, which equates to a bactericidal effect.36–38 The role of bacterial regrowth remains unclear, as some investigators merely make passing commentary on the presence or absence of regrowth while Firsov and colleagues use the IE concept, which is highly dependent on the time taken for bacterial regrowth.31–35 Universal consensus on methodology (e.g. in terms of log reduction endpoints, role of regrowth, length of experiments, number of pathogens necessary, inoculum size, lower counting limits, prevention of antibiotic carryover) would be beneficial. By creating consistent standards of operation and analysis, data from various studies might be pooled, enhancing their utility. The relationship between data from in vitro studies, animal models and clinical trials could also be defined more accurately. Assuming that a pharmacodynamic ratio does prove to be a generic outcome parameter for all bacteria, the quantitative value of such a parameter might differ depending upon the organism, the intrinsic properties of the quinolone used and/or the environmental conditions at the site of infection. Defining values for pharmacodynamic outcome parameters based on the site of infection may necessary. Presently, however, the application of fluoroquinolone pharmacodynamics appears to be pathogen- and quinolone-specific. Clinical application of fluoroquinolone pharmacodynamics Pharmacokinetic variability As is evident from Table II, quinolones typically have low protein binding (trovafloxacin is the exception) and excellent bioavailability (>70%). However, AUC and Cmax in healthy individuals are significantly different from those in sick patients, for both levofloxacin and gatifloxacin.5,62 Most investigators calculate pharmacodynamic ratios from pharmacokinetic data obtained in healthy volunteers. As AUCs for levofloxacin and gatifloxacin in patients with bacterial infections may be 33% higher than those seen in healthy individuals,5,62 this methodology may lead to an underestimation of the calculated AUC/MIC ratio. The increased AUCs observed in infected patients may result from diminished quinolone excretion, decreased protein binding or a heightened immune response. When available, pharmacokinetic data derived from patients with a bacterial infection should be used to calculate pharmacodynamic ratios. The difference in protein binding between healthy volunteers and infected patients should also be considered when calculating pharmacodynamic ratios. In order to assess the AUC/MIC or peak/MIC ratio accurately, the free or unbound drug concentration, which represents the true antibiotic concentration available to cross biological membranes and interact with the bacterium, should be used. Otherwise the pharmacodynamic ratio may be overestimated. Tissue penetration is another factor that might need to be considered when calculating pharmacodynamic ratios, since the AUC and maximum concentration at the site of infection are the relevant pharmacokinetic parameters needed to determine pharmacodynamic ratios. The ultimate role of tissue penetration in pharmacodynamic calculations, however, remains to be defined fully. Tables IV and V illustrate the AUC/MIC and peak/MIC ratios generated with conventional single dose regimens for some of the newer quinolone agents. The AUCfree and Cmax,free values represent the values corrected for protein binding. Included in these tables are pharmacokinetic data for levofloxacin and gatifloxacin from patients with bacterial infections. These tables can assist the clinician in estimating AUC/MIC or peak/MIC ratios based on the MIC for a pathogen. Pathogen variability The MIC represents the pathogen-specific variable in pharmacodynamic ratios. MICs can vary significantly depending on methodology and specimen source. The way in which MICs are measured (Etest, broth microdilution or disc diffusion) can affect the interpretation of the MIC,63–65 and the type of broth, incubation time, incubation temperature and method of determining turbidity can all vary.66 The site of infection may also affect the ‘true’ MIC for a given pathogen owing to the effects of pH on MIC.67 MIC errors of a single tube dilution can alter the corresponding pharmacodynamic ratio significantly. For example, if the AUC of levofloxacin is 72 and the MIC for an S. pneumoniae isolate is 0.5 mg/L, the corresponding AUC/MIC ratio is 144 (72/0.5). If the MIC is later found (perhaps by Etest) to be 1 mg/L, the AUC/MIC would then be 72 (72/1). We would suggest that, whenever possible, MICs of blood isolates, measured using NCCLS-approved methodology,68 should be used. The clinician should be aware that both patient- and pathogen-specific variation exists and the resulting pharmacodynamic ratio remains an estimate. Gram-negative pathogens Initial fluoroquinolone pharmacodynamic evaluations dealt primarily with P. aeruginosa.27–29,48,54,55 As outlined above, breakpoint values of AUC/MIC for quinolones and pseudomonal sepsis have ranged from c. 10029 to 125.54 Similarly, peak/MIC ratios of 105,48 or 125 have been suggested for optimal bacteriological and clinical outcomes, respectively, in pseudomonal sepsis. Furthermore, peak/MIC ratios in excess of 8–12 have been associated with diminished development of bacterial resistance.5,27,28,57 Studies of ciprofloxacin in ventilator-dependent patients with lower respiratory tract infections10 did not identify a specific pharmacodynamic ratio, but development of bacterial resistance was associated with MICs > 0.25 mg/L. Retrospective analysis of these data suggest a peak/MIC ratio of c. 12. Assuming that an AUC/MIC ratio of ≥100 and peak/ MIC ratio of ≥10 are necessary for clinical and microbiological cure, an MIC ≤ 0.25 mg/L would be a necessary breakpoint for most fluoroquinolones, including ciprofloxacin. Most Gram-negative pathogens remain highly susceptible to the fluoroquinolones,69–73 although a notable exception is P. aeruginosa, with MIC90s ranging from 0.25 to 8 mg/L.16 The pharmacokinetic data for the fluoroquinolones (Tables IV and V) suggest that, given the low MICs for Gram-negative bacilli, existing dosage regimens are sufficient to achieve AUC/MIC ratios of 100 and peak/MIC ratios of 10. With the exception of P. aeruginosa, the fluoroquinolones appear to have a high probability of clinical and microbiological efficacy against Gram-negative bacteria while minimizing the development of bacterial resistance. Importantly, the clinical experience with ciprofloxacin and levofloxacin correlates well with these pharmacodynamic predictions. Streptococcus pneumoniae As stated previously, the natural inclination is to extrapolate the data from Gram-negative organisms to other pathogens, such as Gram-positive pathogens, atypical pathogens and anaerobes. Within the past 3 years, however, a significant amount of data has emerged describing fluoroquinolone pharmacodynamics with the pneumococci. These data suggest that the breakpoint AUC/MIC ratio necessary to ensure successful outcome is c. 40.36,40–44 Levofloxacin is the predominant fluoroquinolone evaluated, although these data correlate with conclusions from animal models by Andes & Craig for sitafloxacin, gatifloxacin and gemifloxacin,51–53 as well as human clinical data by Preston and colleagues.5 Assuming that a minimal AUC/MIC ratio of 40 is necessary to achieve clinical and microbiological success in S. pneumoniae infections, the newer quinolone agents will generate an AUC/MIC ≥ 40 with isolates whose MICs are ≤1 mg/L. Such MICs are observed typically for most S. pneumoniae isolates and the newer quinolone agents.64–68 The post-marketing clinical experience with levofloxacin in community-acquired pneumonia confirms these pharmacodynamic predictions. Recent data from the TRUST surveillance system indicate that the S. pneumoniae MIC90 of levofloxacin is 1 mg/L.17 According to the pharmacokinetic/pharmacodynamic data available for levofloxacin, typical AUC/MIC ratios generated by a 500 mg daily dose of levofloxacin range from 48 in healthy patients to 72 in patients with infections. As clinical treatment failures and reports of pneumococcal resistance remain rare for levofloxacin, a breakpoint AUC/MIC ratio of >40 correlates well with clinical experience. Interestingly, no apparent benefit is realized in terms of rate and extent of bactericidal activity with AUC/MIC ratios of >40. Further work characterizing the role of pharmacodynamics in the development of pneumococcal resistance is necessary. Anaerobes Trovafloxacin was the first fluoroquinolone with significant anaerobic activity and corresponding clinical indications. Moxifloxacin and gatifloxacin have demonstrated some activity against anaerobes although they are not approved for use in anaerobic infections.74,75 With more quinolone agents currently in development with enhanced anaerobic activity, the identification of pharmacodynamic parameters describing anaerobic activity is of importance. Initial data suggest that for B. fragilis and B. thetaiotaomicron, a breakpoint AUC/MIC ratio of between 10 and 50 appears to be appropriate and that AUC/MIC ratios of >50 and >15, respectively, were necessary to prevent the development of resistance in these two anaerobic species.37,39 Conclusion A basic understanding of fluoroquinolone pharmacodynamics is necessary for clinicians to evaluate the potential use and proper dosing of quinolone antimicrobials. The proper application of quinolone- and organism-specific pharmacodynamic principles may aid the clinician in ensuring clinical and bacteriological cure as well as minimizing the likelihood of the development of bacterial resistance. Given the recent evidence with Gram-positive bacteria and anaerobes, it seems unlikely that there will ever be a universal pharmacodynamic outcome parameter to predict clinical and microbiological success. It is possible that there is no single pharmacodynamic parameter that will be able to predict clinical and microbiological cure by extrapolation between quinolone agents or between bacterial species. Fluoroquinolone pharmacodynamics rather, appears to be both quinolone- and pathogen-specific. Currently, the suggested pharmacodynamic breakpoints for the development of resistance correspond to those identified with clinical and microbiological outcome. Further studies of this important application of fluoroquinolone pharmacodynamics are warranted. Table I. Selected quinolone antimicrobial compounds Generic name . Trade name(s) . Manufacturer(s) . aInvestigational. Norfloxacin Noroxin, Utinor, Fulgram, Chibroxol Merck, Roberts Enoxacin Penetrex, Gyramid, Enoxor, Bactidan, Aventis Enoxen, Flumark, Almitil, Comprecin Ciprofloxacin Cipro, Ciloxan Bayer Moxifloxacin Avelox Bayer Ofloxacin Floxin, Tarivid Ortho-McNeil, Aventis, Daiichi Levofloxacin Levaquin, Elequine Aventis Lomefloxacin Maxaquin, Uniquin, Chimono Unimed, Searle Sparfloxacin Zagam, Zegam Mylan, Aventis Trovafloxacin Trovan Pfizer Alatrofloxacin Trovan IV Pfizer Gatifloxacin Tequin Bristol-Myers Squibb, Grunenthal Gemifloxacina Factive SmithKline Beecham Sitafloxacina – Daiichi Generic name . Trade name(s) . Manufacturer(s) . aInvestigational. Norfloxacin Noroxin, Utinor, Fulgram, Chibroxol Merck, Roberts Enoxacin Penetrex, Gyramid, Enoxor, Bactidan, Aventis Enoxen, Flumark, Almitil, Comprecin Ciprofloxacin Cipro, Ciloxan Bayer Moxifloxacin Avelox Bayer Ofloxacin Floxin, Tarivid Ortho-McNeil, Aventis, Daiichi Levofloxacin Levaquin, Elequine Aventis Lomefloxacin Maxaquin, Uniquin, Chimono Unimed, Searle Sparfloxacin Zagam, Zegam Mylan, Aventis Trovafloxacin Trovan Pfizer Alatrofloxacin Trovan IV Pfizer Gatifloxacin Tequin Bristol-Myers Squibb, Grunenthal Gemifloxacina Factive SmithKline Beecham Sitafloxacina – Daiichi Open in new tab Table I. Selected quinolone antimicrobial compounds Generic name . Trade name(s) . Manufacturer(s) . aInvestigational. Norfloxacin Noroxin, Utinor, Fulgram, Chibroxol Merck, Roberts Enoxacin Penetrex, Gyramid, Enoxor, Bactidan, Aventis Enoxen, Flumark, Almitil, Comprecin Ciprofloxacin Cipro, Ciloxan Bayer Moxifloxacin Avelox Bayer Ofloxacin Floxin, Tarivid Ortho-McNeil, Aventis, Daiichi Levofloxacin Levaquin, Elequine Aventis Lomefloxacin Maxaquin, Uniquin, Chimono Unimed, Searle Sparfloxacin Zagam, Zegam Mylan, Aventis Trovafloxacin Trovan Pfizer Alatrofloxacin Trovan IV Pfizer Gatifloxacin Tequin Bristol-Myers Squibb, Grunenthal Gemifloxacina Factive SmithKline Beecham Sitafloxacina – Daiichi Generic name . Trade name(s) . Manufacturer(s) . aInvestigational. Norfloxacin Noroxin, Utinor, Fulgram, Chibroxol Merck, Roberts Enoxacin Penetrex, Gyramid, Enoxor, Bactidan, Aventis Enoxen, Flumark, Almitil, Comprecin Ciprofloxacin Cipro, Ciloxan Bayer Moxifloxacin Avelox Bayer Ofloxacin Floxin, Tarivid Ortho-McNeil, Aventis, Daiichi Levofloxacin Levaquin, Elequine Aventis Lomefloxacin Maxaquin, Uniquin, Chimono Unimed, Searle Sparfloxacin Zagam, Zegam Mylan, Aventis Trovafloxacin Trovan Pfizer Alatrofloxacin Trovan IV Pfizer Gatifloxacin Tequin Bristol-Myers Squibb, Grunenthal Gemifloxacina Factive SmithKline Beecham Sitafloxacina – Daiichi Open in new tab Table II. Summary of oral fluoroquinolone pharmacokinetic data after single doses (adapted from references 5, 62 and 74–78) Fluoroquinolone . Total daily dose (mg) . PB (%) . f (%) . F (%) . AUC24 (mg•h/L)a . Cmax (mg/L) . tH (h) . PB, protein binding; f, urinary fraction excreted unbound; F, bioavailability; Cmax, peak serum concentration; tH, half-life. aAUC24, multiple oral dosing (total daily dose over 24 h period). bAUC24 = AUC0–12 × 2. cPatients with bacterial infections. Ciprofloxacin74 750 20–40 40–50 70 31.6b 4.3 4 Levofloxacin75 500 24–38 87 99 47.5 6.2 6–7 Levofloxacin5,c 500 – – – 72.5 8.7 – Sparfloxacin76 200 45 10 92 18.7 1.1 20 Trovafloxacin77 200 76 6 88 34.4 2.1 9.6 Moxifloxacin78 400 50 20 90 48 4.5 12 Gatifloxacin62 400 20 72 96 34.4 3.8 7.8 Gatifloxacin62,c 400 – – – 51.3 4.2 – Fluoroquinolone . Total daily dose (mg) . PB (%) . f (%) . F (%) . AUC24 (mg•h/L)a . Cmax (mg/L) . tH (h) . PB, protein binding; f, urinary fraction excreted unbound; F, bioavailability; Cmax, peak serum concentration; tH, half-life. aAUC24, multiple oral dosing (total daily dose over 24 h period). bAUC24 = AUC0–12 × 2. cPatients with bacterial infections. Ciprofloxacin74 750 20–40 40–50 70 31.6b 4.3 4 Levofloxacin75 500 24–38 87 99 47.5 6.2 6–7 Levofloxacin5,c 500 – – – 72.5 8.7 – Sparfloxacin76 200 45 10 92 18.7 1.1 20 Trovafloxacin77 200 76 6 88 34.4 2.1 9.6 Moxifloxacin78 400 50 20 90 48 4.5 12 Gatifloxacin62 400 20 72 96 34.4 3.8 7.8 Gatifloxacin62,c 400 – – – 51.3 4.2 – Open in new tab Table II. Summary of oral fluoroquinolone pharmacokinetic data after single doses (adapted from references 5, 62 and 74–78) Fluoroquinolone . Total daily dose (mg) . PB (%) . f (%) . F (%) . AUC24 (mg•h/L)a . Cmax (mg/L) . tH (h) . PB, protein binding; f, urinary fraction excreted unbound; F, bioavailability; Cmax, peak serum concentration; tH, half-life. aAUC24, multiple oral dosing (total daily dose over 24 h period). bAUC24 = AUC0–12 × 2. cPatients with bacterial infections. Ciprofloxacin74 750 20–40 40–50 70 31.6b 4.3 4 Levofloxacin75 500 24–38 87 99 47.5 6.2 6–7 Levofloxacin5,c 500 – – – 72.5 8.7 – Sparfloxacin76 200 45 10 92 18.7 1.1 20 Trovafloxacin77 200 76 6 88 34.4 2.1 9.6 Moxifloxacin78 400 50 20 90 48 4.5 12 Gatifloxacin62 400 20 72 96 34.4 3.8 7.8 Gatifloxacin62,c 400 – – – 51.3 4.2 – Fluoroquinolone . Total daily dose (mg) . PB (%) . f (%) . F (%) . AUC24 (mg•h/L)a . Cmax (mg/L) . tH (h) . PB, protein binding; f, urinary fraction excreted unbound; F, bioavailability; Cmax, peak serum concentration; tH, half-life. aAUC24, multiple oral dosing (total daily dose over 24 h period). bAUC24 = AUC0–12 × 2. cPatients with bacterial infections. Ciprofloxacin74 750 20–40 40–50 70 31.6b 4.3 4 Levofloxacin75 500 24–38 87 99 47.5 6.2 6–7 Levofloxacin5,c 500 – – – 72.5 8.7 – Sparfloxacin76 200 45 10 92 18.7 1.1 20 Trovafloxacin77 200 76 6 88 34.4 2.1 9.6 Moxifloxacin78 400 50 20 90 48 4.5 12 Gatifloxacin62 400 20 72 96 34.4 3.8 7.8 Gatifloxacin62,c 400 – – – 51.3 4.2 – Open in new tab Table III. Chronological summary of select fluoroquinolone pharmacodynamic studies Investigator, year (ref. no.) . Organisms . Fluoroquinolones . Study population . Conclusions . Blaser et al., 1987 (27) P. aeruginosa, K. pneumoniae,E. coli and S. aureus enoxacin in vitro pharmacodynamic model peak/MIC > 8 to prevent development of resistance Peloquin et al., 1989 (10) 15 Enterobacter spp., 10 P. aeruginosa, six Klebsiella spp., three each of Proteus spp., Seratia spp. and E. coli ciprofloxacin ventilator-dependent nosocomial pneumonia patients MIC > 0.25 mg/L as marginally susceptible and peak/MIC ratio of 5 for P. aeruginosa led to 70% resistance rate Dudley et al., 1991 (28) P. aeruginosa ciprofloxacin in vitro pharmacodynamic model peak/MIC > 8 to prevent development of resistance Drusano et al., 1993 (48) P. aeruginosa lomefloxacin neutropenic rat sepsis peak/MIC > 10 Forrest et al., 1993 (54) 82% Gram-negative, 15% S. aureus ciprofloxacin retrospective human study of lower respiratory tract infections AUC/MIC > 125 SIT–1•h as generic outcome predictor Hyatt et al., 1994 (55) S. pneumoniae, S. aureus and P. aeruginosa ciprofloxacin in vitro analysis of serum ultrafiltrates from five healthy volunteers AUC/MIC > 125 SIT–1•h Vesga & Craig, 1996 (49) PRSP (n = 6) levofloxacin neutropenic and healthy mice AUC/MIC 22–59 for optimal outcome for S. pneumoniae Vesga et al., 1996 (50) Enterobacteriaceae, S. aureus and S. pneumoniae (n = 9) sparfloxacin neutropenic mice mean AUC/MIC ratio of 29 for Enterobacteriaceae, S. aureus and S. pneumoniae Madaras-Kelly et al., P. aeruginosa ciprofloxacin, in vitro pharmacodynamic model AUC/MIC > 100 SIT–1•h for 1996 (29) ofloxacin P. aeruginosa Forrest et al., 1997 (56) S. pneumoniae (n = 8) grepafloxacin po acute exacerbations of chronic AUC/MIC of 0–92 gave 87.5% bronchitis bacteriological cure for S. pneumoniae Preston et al., 1998 (5) 16% S. pneumoniae, levofloxacin prospective human trial with peak/MIC > 10 with peak/MIC 11% S. aureus urinary tract, pulmonary and skin and AUC/MIC correlation or skin structure infections (r = 0.942) Firsov et al., 1998 (30) P. aeruginosa, E. coli ciprofloxacin, in vitro pharmacodynamic model t > MIC as interquinolone; and K. pneumoniae trovafloxacin AUC/MIC, peak/MIC and t > MIC as intraquinolone outcome predictors Vostrov et al., 1998 (31) S. aureus ciprofloxacin, in vitro pharmacodynamic model AUC/MIC optimal predictor gatifloxacin, for S. aureus trovafloxacin Thomas et al., 1998 (57) 86% Gram-negative bacilli ciprofloxacin retrospective human study of AUC/MIC as predictor of lower respiratory tract infections development of resistance Wright et al., 1998 (36) S. pneumoniae levofloxacin, in vitro pharmacodynamic model AUC/MIC > 35 as optimal ciprofloxacin, predictor for S. pneumoniae trovafloxacin Peterson et al., 1998 (37) B. fragilis levofloxacin, in vitro pharmacodynamic model AUC/MIC > 50 as optimal trovafloxacin predictor for B. fragilis Hoang et al., 1998 (38) S. aureus trovafloxacin, in vitro pharmacodynamic model AUC/MIC > 57 as optimal ciprofloxacin, predictor for S. aureus clinafloxacin, sparfloxacin, levofloxacin Firsov et al., 1999 (35) S. aureus ciprofloxacin, in vitro pharmacodynamic model IE – log AUC/MIC relationship trovafloxacin as predictor Lacy et al., 1999 (40) S. pneumoniae ciprofloxacin, in vitro pharmacodynamic model AUC/MIC of 30–55 as optimal levofloxacin predictor for S. pneumoniae Lister & Sanders, S. pneumoniae ciprofloxacin, in vitro pharmacodynamic model AUC/MIC of 44–49 for 1999 (41) ofloxacin, bacterial eradication with trovafloxacin S. pneumoniae Ibrahim et al., 1999 (44) fluoroquinolone-resistant levofloxacin in vitro pharmacodynamic model AUC/MIC of 26–36 as optimal S. pneumoniae predictor and t > MIC utility with fluoroquinolone-resistant S. pneumoniae Brown et al., 1999 (39) B. thetaiotamicron levofloxacin, in vitro pharmacodynamic model AUC/MIC of 10–50 as optimal sparfloxacin, predictor for trovafloxacin B. thetaiotamicron Andes & Craig, S. pneumoniae (n = 14), sitafloxacin murine thigh and lung infection mean AUC/MIC values of 43 1999 (51) S. aureus, Enterobacteriaceae models for Enterobacteriaciae, 37 for S. pneumoniae and 71 for S. aureus to achieve efficacy Andes & Craig, S. pneumoniae (n = 9), gatifloxacin murine thigh and lung infection mean AUC/MIC values of 48 1999 (52) S. aureus and models for Enterobacteriaciae, 52 for Enterobacteriaceae S. pneumoniae and 39 for S. aureus to achieve efficacy Andes & Craig, S. pneumoniae (n = 13), S. aureus gemifloxacin murine thigh and lung infection mean AUC/MIC values of 35 to 1999 (53) and Enterobacteriaceae models achieve efficacy Coyle & Rybak, fluoroquinolone-resistant levofloxacin, in vitro pharmacodynamic model AUC/MIC ≥ 20 or peak/MIC 1999 (43) S. pneumoniae (n = 2) trovafloxacin, ≥ 2.2 prevented regrowth and gatifloxacin, development of resistance ciprofloxacin Hershberger & Rybak, S. pneumoniae (n = 2) levofloxacin, in vitro fibrin clot AUC/MIC ≥ 40 or t > MIC ≥ 2000 (42) trovafloxacin, pharmacodynamic model 55% associated with increased gatifloxacin, killing and less regrowth clinafloxacin, sparfloxacin, ciprofloxacin Investigator, year (ref. no.) . Organisms . Fluoroquinolones . Study population . Conclusions . Blaser et al., 1987 (27) P. aeruginosa, K. pneumoniae,E. coli and S. aureus enoxacin in vitro pharmacodynamic model peak/MIC > 8 to prevent development of resistance Peloquin et al., 1989 (10) 15 Enterobacter spp., 10 P. aeruginosa, six Klebsiella spp., three each of Proteus spp., Seratia spp. and E. coli ciprofloxacin ventilator-dependent nosocomial pneumonia patients MIC > 0.25 mg/L as marginally susceptible and peak/MIC ratio of 5 for P. aeruginosa led to 70% resistance rate Dudley et al., 1991 (28) P. aeruginosa ciprofloxacin in vitro pharmacodynamic model peak/MIC > 8 to prevent development of resistance Drusano et al., 1993 (48) P. aeruginosa lomefloxacin neutropenic rat sepsis peak/MIC > 10 Forrest et al., 1993 (54) 82% Gram-negative, 15% S. aureus ciprofloxacin retrospective human study of lower respiratory tract infections AUC/MIC > 125 SIT–1•h as generic outcome predictor Hyatt et al., 1994 (55) S. pneumoniae, S. aureus and P. aeruginosa ciprofloxacin in vitro analysis of serum ultrafiltrates from five healthy volunteers AUC/MIC > 125 SIT–1•h Vesga & Craig, 1996 (49) PRSP (n = 6) levofloxacin neutropenic and healthy mice AUC/MIC 22–59 for optimal outcome for S. pneumoniae Vesga et al., 1996 (50) Enterobacteriaceae, S. aureus and S. pneumoniae (n = 9) sparfloxacin neutropenic mice mean AUC/MIC ratio of 29 for Enterobacteriaceae, S. aureus and S. pneumoniae Madaras-Kelly et al., P. aeruginosa ciprofloxacin, in vitro pharmacodynamic model AUC/MIC > 100 SIT–1•h for 1996 (29) ofloxacin P. aeruginosa Forrest et al., 1997 (56) S. pneumoniae (n = 8) grepafloxacin po acute exacerbations of chronic AUC/MIC of 0–92 gave 87.5% bronchitis bacteriological cure for S. pneumoniae Preston et al., 1998 (5) 16% S. pneumoniae, levofloxacin prospective human trial with peak/MIC > 10 with peak/MIC 11% S. aureus urinary tract, pulmonary and skin and AUC/MIC correlation or skin structure infections (r = 0.942) Firsov et al., 1998 (30) P. aeruginosa, E. coli ciprofloxacin, in vitro pharmacodynamic model t > MIC as interquinolone; and K. pneumoniae trovafloxacin AUC/MIC, peak/MIC and t > MIC as intraquinolone outcome predictors Vostrov et al., 1998 (31) S. aureus ciprofloxacin, in vitro pharmacodynamic model AUC/MIC optimal predictor gatifloxacin, for S. aureus trovafloxacin Thomas et al., 1998 (57) 86% Gram-negative bacilli ciprofloxacin retrospective human study of AUC/MIC as predictor of lower respiratory tract infections development of resistance Wright et al., 1998 (36) S. pneumoniae levofloxacin, in vitro pharmacodynamic model AUC/MIC > 35 as optimal ciprofloxacin, predictor for S. pneumoniae trovafloxacin Peterson et al., 1998 (37) B. fragilis levofloxacin, in vitro pharmacodynamic model AUC/MIC > 50 as optimal trovafloxacin predictor for B. fragilis Hoang et al., 1998 (38) S. aureus trovafloxacin, in vitro pharmacodynamic model AUC/MIC > 57 as optimal ciprofloxacin, predictor for S. aureus clinafloxacin, sparfloxacin, levofloxacin Firsov et al., 1999 (35) S. aureus ciprofloxacin, in vitro pharmacodynamic model IE – log AUC/MIC relationship trovafloxacin as predictor Lacy et al., 1999 (40) S. pneumoniae ciprofloxacin, in vitro pharmacodynamic model AUC/MIC of 30–55 as optimal levofloxacin predictor for S. pneumoniae Lister & Sanders, S. pneumoniae ciprofloxacin, in vitro pharmacodynamic model AUC/MIC of 44–49 for 1999 (41) ofloxacin, bacterial eradication with trovafloxacin S. pneumoniae Ibrahim et al., 1999 (44) fluoroquinolone-resistant levofloxacin in vitro pharmacodynamic model AUC/MIC of 26–36 as optimal S. pneumoniae predictor and t > MIC utility with fluoroquinolone-resistant S. pneumoniae Brown et al., 1999 (39) B. thetaiotamicron levofloxacin, in vitro pharmacodynamic model AUC/MIC of 10–50 as optimal sparfloxacin, predictor for trovafloxacin B. thetaiotamicron Andes & Craig, S. pneumoniae (n = 14), sitafloxacin murine thigh and lung infection mean AUC/MIC values of 43 1999 (51) S. aureus, Enterobacteriaceae models for Enterobacteriaciae, 37 for S. pneumoniae and 71 for S. aureus to achieve efficacy Andes & Craig, S. pneumoniae (n = 9), gatifloxacin murine thigh and lung infection mean AUC/MIC values of 48 1999 (52) S. aureus and models for Enterobacteriaciae, 52 for Enterobacteriaceae S. pneumoniae and 39 for S. aureus to achieve efficacy Andes & Craig, S. pneumoniae (n = 13), S. aureus gemifloxacin murine thigh and lung infection mean AUC/MIC values of 35 to 1999 (53) and Enterobacteriaceae models achieve efficacy Coyle & Rybak, fluoroquinolone-resistant levofloxacin, in vitro pharmacodynamic model AUC/MIC ≥ 20 or peak/MIC 1999 (43) S. pneumoniae (n = 2) trovafloxacin, ≥ 2.2 prevented regrowth and gatifloxacin, development of resistance ciprofloxacin Hershberger & Rybak, S. pneumoniae (n = 2) levofloxacin, in vitro fibrin clot AUC/MIC ≥ 40 or t > MIC ≥ 2000 (42) trovafloxacin, pharmacodynamic model 55% associated with increased gatifloxacin, killing and less regrowth clinafloxacin, sparfloxacin, ciprofloxacin Open in new tab Table III. Chronological summary of select fluoroquinolone pharmacodynamic studies Investigator, year (ref. no.) . Organisms . Fluoroquinolones . Study population . Conclusions . Blaser et al., 1987 (27) P. aeruginosa, K. pneumoniae,E. coli and S. aureus enoxacin in vitro pharmacodynamic model peak/MIC > 8 to prevent development of resistance Peloquin et al., 1989 (10) 15 Enterobacter spp., 10 P. aeruginosa, six Klebsiella spp., three each of Proteus spp., Seratia spp. and E. coli ciprofloxacin ventilator-dependent nosocomial pneumonia patients MIC > 0.25 mg/L as marginally susceptible and peak/MIC ratio of 5 for P. aeruginosa led to 70% resistance rate Dudley et al., 1991 (28) P. aeruginosa ciprofloxacin in vitro pharmacodynamic model peak/MIC > 8 to prevent development of resistance Drusano et al., 1993 (48) P. aeruginosa lomefloxacin neutropenic rat sepsis peak/MIC > 10 Forrest et al., 1993 (54) 82% Gram-negative, 15% S. aureus ciprofloxacin retrospective human study of lower respiratory tract infections AUC/MIC > 125 SIT–1•h as generic outcome predictor Hyatt et al., 1994 (55) S. pneumoniae, S. aureus and P. aeruginosa ciprofloxacin in vitro analysis of serum ultrafiltrates from five healthy volunteers AUC/MIC > 125 SIT–1•h Vesga & Craig, 1996 (49) PRSP (n = 6) levofloxacin neutropenic and healthy mice AUC/MIC 22–59 for optimal outcome for S. pneumoniae Vesga et al., 1996 (50) Enterobacteriaceae, S. aureus and S. pneumoniae (n = 9) sparfloxacin neutropenic mice mean AUC/MIC ratio of 29 for Enterobacteriaceae, S. aureus and S. pneumoniae Madaras-Kelly et al., P. aeruginosa ciprofloxacin, in vitro pharmacodynamic model AUC/MIC > 100 SIT–1•h for 1996 (29) ofloxacin P. aeruginosa Forrest et al., 1997 (56) S. pneumoniae (n = 8) grepafloxacin po acute exacerbations of chronic AUC/MIC of 0–92 gave 87.5% bronchitis bacteriological cure for S. pneumoniae Preston et al., 1998 (5) 16% S. pneumoniae, levofloxacin prospective human trial with peak/MIC > 10 with peak/MIC 11% S. aureus urinary tract, pulmonary and skin and AUC/MIC correlation or skin structure infections (r = 0.942) Firsov et al., 1998 (30) P. aeruginosa, E. coli ciprofloxacin, in vitro pharmacodynamic model t > MIC as interquinolone; and K. pneumoniae trovafloxacin AUC/MIC, peak/MIC and t > MIC as intraquinolone outcome predictors Vostrov et al., 1998 (31) S. aureus ciprofloxacin, in vitro pharmacodynamic model AUC/MIC optimal predictor gatifloxacin, for S. aureus trovafloxacin Thomas et al., 1998 (57) 86% Gram-negative bacilli ciprofloxacin retrospective human study of AUC/MIC as predictor of lower respiratory tract infections development of resistance Wright et al., 1998 (36) S. pneumoniae levofloxacin, in vitro pharmacodynamic model AUC/MIC > 35 as optimal ciprofloxacin, predictor for S. pneumoniae trovafloxacin Peterson et al., 1998 (37) B. fragilis levofloxacin, in vitro pharmacodynamic model AUC/MIC > 50 as optimal trovafloxacin predictor for B. fragilis Hoang et al., 1998 (38) S. aureus trovafloxacin, in vitro pharmacodynamic model AUC/MIC > 57 as optimal ciprofloxacin, predictor for S. aureus clinafloxacin, sparfloxacin, levofloxacin Firsov et al., 1999 (35) S. aureus ciprofloxacin, in vitro pharmacodynamic model IE – log AUC/MIC relationship trovafloxacin as predictor Lacy et al., 1999 (40) S. pneumoniae ciprofloxacin, in vitro pharmacodynamic model AUC/MIC of 30–55 as optimal levofloxacin predictor for S. pneumoniae Lister & Sanders, S. pneumoniae ciprofloxacin, in vitro pharmacodynamic model AUC/MIC of 44–49 for 1999 (41) ofloxacin, bacterial eradication with trovafloxacin S. pneumoniae Ibrahim et al., 1999 (44) fluoroquinolone-resistant levofloxacin in vitro pharmacodynamic model AUC/MIC of 26–36 as optimal S. pneumoniae predictor and t > MIC utility with fluoroquinolone-resistant S. pneumoniae Brown et al., 1999 (39) B. thetaiotamicron levofloxacin, in vitro pharmacodynamic model AUC/MIC of 10–50 as optimal sparfloxacin, predictor for trovafloxacin B. thetaiotamicron Andes & Craig, S. pneumoniae (n = 14), sitafloxacin murine thigh and lung infection mean AUC/MIC values of 43 1999 (51) S. aureus, Enterobacteriaceae models for Enterobacteriaciae, 37 for S. pneumoniae and 71 for S. aureus to achieve efficacy Andes & Craig, S. pneumoniae (n = 9), gatifloxacin murine thigh and lung infection mean AUC/MIC values of 48 1999 (52) S. aureus and models for Enterobacteriaciae, 52 for Enterobacteriaceae S. pneumoniae and 39 for S. aureus to achieve efficacy Andes & Craig, S. pneumoniae (n = 13), S. aureus gemifloxacin murine thigh and lung infection mean AUC/MIC values of 35 to 1999 (53) and Enterobacteriaceae models achieve efficacy Coyle & Rybak, fluoroquinolone-resistant levofloxacin, in vitro pharmacodynamic model AUC/MIC ≥ 20 or peak/MIC 1999 (43) S. pneumoniae (n = 2) trovafloxacin, ≥ 2.2 prevented regrowth and gatifloxacin, development of resistance ciprofloxacin Hershberger & Rybak, S. pneumoniae (n = 2) levofloxacin, in vitro fibrin clot AUC/MIC ≥ 40 or t > MIC ≥ 2000 (42) trovafloxacin, pharmacodynamic model 55% associated with increased gatifloxacin, killing and less regrowth clinafloxacin, sparfloxacin, ciprofloxacin Investigator, year (ref. no.) . Organisms . Fluoroquinolones . Study population . Conclusions . Blaser et al., 1987 (27) P. aeruginosa, K. pneumoniae,E. coli and S. aureus enoxacin in vitro pharmacodynamic model peak/MIC > 8 to prevent development of resistance Peloquin et al., 1989 (10) 15 Enterobacter spp., 10 P. aeruginosa, six Klebsiella spp., three each of Proteus spp., Seratia spp. and E. coli ciprofloxacin ventilator-dependent nosocomial pneumonia patients MIC > 0.25 mg/L as marginally susceptible and peak/MIC ratio of 5 for P. aeruginosa led to 70% resistance rate Dudley et al., 1991 (28) P. aeruginosa ciprofloxacin in vitro pharmacodynamic model peak/MIC > 8 to prevent development of resistance Drusano et al., 1993 (48) P. aeruginosa lomefloxacin neutropenic rat sepsis peak/MIC > 10 Forrest et al., 1993 (54) 82% Gram-negative, 15% S. aureus ciprofloxacin retrospective human study of lower respiratory tract infections AUC/MIC > 125 SIT–1•h as generic outcome predictor Hyatt et al., 1994 (55) S. pneumoniae, S. aureus and P. aeruginosa ciprofloxacin in vitro analysis of serum ultrafiltrates from five healthy volunteers AUC/MIC > 125 SIT–1•h Vesga & Craig, 1996 (49) PRSP (n = 6) levofloxacin neutropenic and healthy mice AUC/MIC 22–59 for optimal outcome for S. pneumoniae Vesga et al., 1996 (50) Enterobacteriaceae, S. aureus and S. pneumoniae (n = 9) sparfloxacin neutropenic mice mean AUC/MIC ratio of 29 for Enterobacteriaceae, S. aureus and S. pneumoniae Madaras-Kelly et al., P. aeruginosa ciprofloxacin, in vitro pharmacodynamic model AUC/MIC > 100 SIT–1•h for 1996 (29) ofloxacin P. aeruginosa Forrest et al., 1997 (56) S. pneumoniae (n = 8) grepafloxacin po acute exacerbations of chronic AUC/MIC of 0–92 gave 87.5% bronchitis bacteriological cure for S. pneumoniae Preston et al., 1998 (5) 16% S. pneumoniae, levofloxacin prospective human trial with peak/MIC > 10 with peak/MIC 11% S. aureus urinary tract, pulmonary and skin and AUC/MIC correlation or skin structure infections (r = 0.942) Firsov et al., 1998 (30) P. aeruginosa, E. coli ciprofloxacin, in vitro pharmacodynamic model t > MIC as interquinolone; and K. pneumoniae trovafloxacin AUC/MIC, peak/MIC and t > MIC as intraquinolone outcome predictors Vostrov et al., 1998 (31) S. aureus ciprofloxacin, in vitro pharmacodynamic model AUC/MIC optimal predictor gatifloxacin, for S. aureus trovafloxacin Thomas et al., 1998 (57) 86% Gram-negative bacilli ciprofloxacin retrospective human study of AUC/MIC as predictor of lower respiratory tract infections development of resistance Wright et al., 1998 (36) S. pneumoniae levofloxacin, in vitro pharmacodynamic model AUC/MIC > 35 as optimal ciprofloxacin, predictor for S. pneumoniae trovafloxacin Peterson et al., 1998 (37) B. fragilis levofloxacin, in vitro pharmacodynamic model AUC/MIC > 50 as optimal trovafloxacin predictor for B. fragilis Hoang et al., 1998 (38) S. aureus trovafloxacin, in vitro pharmacodynamic model AUC/MIC > 57 as optimal ciprofloxacin, predictor for S. aureus clinafloxacin, sparfloxacin, levofloxacin Firsov et al., 1999 (35) S. aureus ciprofloxacin, in vitro pharmacodynamic model IE – log AUC/MIC relationship trovafloxacin as predictor Lacy et al., 1999 (40) S. pneumoniae ciprofloxacin, in vitro pharmacodynamic model AUC/MIC of 30–55 as optimal levofloxacin predictor for S. pneumoniae Lister & Sanders, S. pneumoniae ciprofloxacin, in vitro pharmacodynamic model AUC/MIC of 44–49 for 1999 (41) ofloxacin, bacterial eradication with trovafloxacin S. pneumoniae Ibrahim et al., 1999 (44) fluoroquinolone-resistant levofloxacin in vitro pharmacodynamic model AUC/MIC of 26–36 as optimal S. pneumoniae predictor and t > MIC utility with fluoroquinolone-resistant S. pneumoniae Brown et al., 1999 (39) B. thetaiotamicron levofloxacin, in vitro pharmacodynamic model AUC/MIC of 10–50 as optimal sparfloxacin, predictor for trovafloxacin B. thetaiotamicron Andes & Craig, S. pneumoniae (n = 14), sitafloxacin murine thigh and lung infection mean AUC/MIC values of 43 1999 (51) S. aureus, Enterobacteriaceae models for Enterobacteriaciae, 37 for S. pneumoniae and 71 for S. aureus to achieve efficacy Andes & Craig, S. pneumoniae (n = 9), gatifloxacin murine thigh and lung infection mean AUC/MIC values of 48 1999 (52) S. aureus and models for Enterobacteriaciae, 52 for Enterobacteriaceae S. pneumoniae and 39 for S. aureus to achieve efficacy Andes & Craig, S. pneumoniae (n = 13), S. aureus gemifloxacin murine thigh and lung infection mean AUC/MIC values of 35 to 1999 (53) and Enterobacteriaceae models achieve efficacy Coyle & Rybak, fluoroquinolone-resistant levofloxacin, in vitro pharmacodynamic model AUC/MIC ≥ 20 or peak/MIC 1999 (43) S. pneumoniae (n = 2) trovafloxacin, ≥ 2.2 prevented regrowth and gatifloxacin, development of resistance ciprofloxacin Hershberger & Rybak, S. pneumoniae (n = 2) levofloxacin, in vitro fibrin clot AUC/MIC ≥ 40 or t > MIC ≥ 2000 (42) trovafloxacin, pharmacodynamic model 55% associated with increased gatifloxacin, killing and less regrowth clinafloxacin, sparfloxacin, ciprofloxacin Open in new tab Table IV. Predicted fluoroquinolone AUC/MIC ratios . . . . MIC (mg/L) . . AUC . PB (%) . Free AUC . 0.125 . 0.25 . 0.5 . 1 . 2 . AUC, multiple dose area under the curve values in healthy patients (single oral dose); PB, protein binding; free AUC, unbound AUC. aAUC value for patients with bacterial infection. Ciprofloxacin 31.6 30 22.1 177 88 44 22 11 Sparfloxacin 18.7 45 10.3 82 41 21 10 5 Trovafloxacin 34.4 76 8.3 66 33 17 8 4 Moxifloxacin 48 50 24 192 96 48 24 12 Levofloxacin 47.5 31 32.8 262 131 66 33 16 Levofloxacina 72.5 31 50 400 200 100 50 25 Gatifloxacin 34.4 20 27.5 220 110 55 28 14 Gatifloxacina 51.3 20 41 328 164 82 41 21 . . . . MIC (mg/L) . . AUC . PB (%) . Free AUC . 0.125 . 0.25 . 0.5 . 1 . 2 . AUC, multiple dose area under the curve values in healthy patients (single oral dose); PB, protein binding; free AUC, unbound AUC. aAUC value for patients with bacterial infection. Ciprofloxacin 31.6 30 22.1 177 88 44 22 11 Sparfloxacin 18.7 45 10.3 82 41 21 10 5 Trovafloxacin 34.4 76 8.3 66 33 17 8 4 Moxifloxacin 48 50 24 192 96 48 24 12 Levofloxacin 47.5 31 32.8 262 131 66 33 16 Levofloxacina 72.5 31 50 400 200 100 50 25 Gatifloxacin 34.4 20 27.5 220 110 55 28 14 Gatifloxacina 51.3 20 41 328 164 82 41 21 Open in new tab Table IV. Predicted fluoroquinolone AUC/MIC ratios . . . . MIC (mg/L) . . AUC . PB (%) . Free AUC . 0.125 . 0.25 . 0.5 . 1 . 2 . AUC, multiple dose area under the curve values in healthy patients (single oral dose); PB, protein binding; free AUC, unbound AUC. aAUC value for patients with bacterial infection. Ciprofloxacin 31.6 30 22.1 177 88 44 22 11 Sparfloxacin 18.7 45 10.3 82 41 21 10 5 Trovafloxacin 34.4 76 8.3 66 33 17 8 4 Moxifloxacin 48 50 24 192 96 48 24 12 Levofloxacin 47.5 31 32.8 262 131 66 33 16 Levofloxacina 72.5 31 50 400 200 100 50 25 Gatifloxacin 34.4 20 27.5 220 110 55 28 14 Gatifloxacina 51.3 20 41 328 164 82 41 21 . . . . MIC (mg/L) . . AUC . PB (%) . Free AUC . 0.125 . 0.25 . 0.5 . 1 . 2 . AUC, multiple dose area under the curve values in healthy patients (single oral dose); PB, protein binding; free AUC, unbound AUC. aAUC value for patients with bacterial infection. Ciprofloxacin 31.6 30 22.1 177 88 44 22 11 Sparfloxacin 18.7 45 10.3 82 41 21 10 5 Trovafloxacin 34.4 76 8.3 66 33 17 8 4 Moxifloxacin 48 50 24 192 96 48 24 12 Levofloxacin 47.5 31 32.8 262 131 66 33 16 Levofloxacina 72.5 31 50 400 200 100 50 25 Gatifloxacin 34.4 20 27.5 220 110 55 28 14 Gatifloxacina 51.3 20 41 328 164 82 41 21 Open in new tab Table V. Predicted fluoroquinolone peak/MIC ratios . . . . MIC (mg/L) . . Cmax . PB (%) . Free Cmax . 0.125 . 0.25 . 0.5 . 1 . 2 . Cmax, peak serum concentration values in healthy patients (single oral dose); PB, protein binding; free Cmax, unbound Cmax. aCmax values for patients with bacterial infection. Ciprofloxacin 4.3 30 3 24 12 6 3 1.5 Sparfloxacin 1.1 45 0.6 5 2 1.2 <1 <1 Trovafloxacin 2.1 76 0.5 4 2 1 <1 <1 Moxifloxacin 4.5 50 2.3 18 9 5 2 1 Levofloxacin 6.2 31 4.3 34 17 9 4 2 Levofloxacina 8.7 31 6 48 24 12 6 3 Gatifloxacin 3.8 20 3 24 12 6 3 1.5 Gatifloxacina 4.2 20 3.4 27 14 7 3 1.7 . . . . MIC (mg/L) . . Cmax . PB (%) . Free Cmax . 0.125 . 0.25 . 0.5 . 1 . 2 . Cmax, peak serum concentration values in healthy patients (single oral dose); PB, protein binding; free Cmax, unbound Cmax. aCmax values for patients with bacterial infection. Ciprofloxacin 4.3 30 3 24 12 6 3 1.5 Sparfloxacin 1.1 45 0.6 5 2 1.2 <1 <1 Trovafloxacin 2.1 76 0.5 4 2 1 <1 <1 Moxifloxacin 4.5 50 2.3 18 9 5 2 1 Levofloxacin 6.2 31 4.3 34 17 9 4 2 Levofloxacina 8.7 31 6 48 24 12 6 3 Gatifloxacin 3.8 20 3 24 12 6 3 1.5 Gatifloxacina 4.2 20 3.4 27 14 7 3 1.7 Open in new tab Table V. Predicted fluoroquinolone peak/MIC ratios . . . . MIC (mg/L) . . Cmax . PB (%) . Free Cmax . 0.125 . 0.25 . 0.5 . 1 . 2 . Cmax, peak serum concentration values in healthy patients (single oral dose); PB, protein binding; free Cmax, unbound Cmax. aCmax values for patients with bacterial infection. Ciprofloxacin 4.3 30 3 24 12 6 3 1.5 Sparfloxacin 1.1 45 0.6 5 2 1.2 <1 <1 Trovafloxacin 2.1 76 0.5 4 2 1 <1 <1 Moxifloxacin 4.5 50 2.3 18 9 5 2 1 Levofloxacin 6.2 31 4.3 34 17 9 4 2 Levofloxacina 8.7 31 6 48 24 12 6 3 Gatifloxacin 3.8 20 3 24 12 6 3 1.5 Gatifloxacina 4.2 20 3.4 27 14 7 3 1.7 . . . . MIC (mg/L) . . Cmax . PB (%) . Free Cmax . 0.125 . 0.25 . 0.5 . 1 . 2 . Cmax, peak serum concentration values in healthy patients (single oral dose); PB, protein binding; free Cmax, unbound Cmax. aCmax values for patients with bacterial infection. Ciprofloxacin 4.3 30 3 24 12 6 3 1.5 Sparfloxacin 1.1 45 0.6 5 2 1.2 <1 <1 Trovafloxacin 2.1 76 0.5 4 2 1 <1 <1 Moxifloxacin 4.5 50 2.3 18 9 5 2 1 Levofloxacin 6.2 31 4.3 34 17 9 4 2 Levofloxacina 8.7 31 6 48 24 12 6 3 Gatifloxacin 3.8 20 3 24 12 6 3 1.5 Gatifloxacina 4.2 20 3.4 27 14 7 3 1.7 Open in new tab * Corresponding author. Tel: +1-651-221-3896; Fax: +1-651-292-4031; E-mail: rotsc001@tc.umn.edu References 1 Craig, W. A. ( 1998 ). Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clinical Infectious Diseases 26 , 1 –12. 2 Vogelman, B. & Craig, W. A. ( 1986 ). Kinetics of antimicrobial activity. Journal of Pediatrics 108 , 835 –40. 3 Ebert, S. C. & Craig, W. A. ( 1990 ). Pharmacodynamic properties of antibiotics: application to drug monitoring and dosage regimen design. Infection Control and Hospital Epidemiology 11 , 319 –26. 4 Shah, P. M., Junghanns, W. & Stille, W. ( 1976 ). Dosis-Wirkungs-Beziehung der Bakterizidie bei E. coli, K. pneumoniae und Staphylococcus aureus. Deutsche Medizinische Wochenschrift 101 , 325 –8. 5 Preston, S. L., Drusano, G. L., Berman, A. L., Fowler, C. L., Chow, A. T., Dornseif, B. et al. ( 1998 ). Pharmacodynamics of levofloxacin: a new paradigm for early clinical trials. Journal of the American Medical Association 279 , 125 –9. 6 Schentag, J. J., Nix, D. E. & Adelman, M. H. ( 1991 ). Mathematical examination of dual individualization principles: I. Relationships between AUC above MIC and area under the inhibitory curve for cefmenoxime, ciprofloxacin, and tobramycin. DICP Annals of Pharmacotherapy 25 , 1050 –7. 7 Schumacher, G. E. ( 1983 ). Pharmacokinetic and microbiologic evaluation of dosage regimens for newer cephalosporins and penicillins. Clinical Pharmacy 2 , 448 –57. 8 Moore, R. D., Leitman, P. S. & Smith, C. R. ( 1987 ). Clinical response to aminoglycoside therapy: importance of the ratio of peak concentration to minimal inhibitory concentration. Journal of Infectious Diseases 155 , 93 –9. 9 Gerber, A. U., Feller, C. & Brugger, H. P. ( 1989 ). Time course of the pharmacological response to β-lactam antibiotics in vitro and in vivo. European Journal of Clinical Microbiology 3 , 592 –7. 10 Peloquin, C. A., Cumbo, T. J., Nix, D. E., Sands, M. F. & Schentag, J. J. ( 1989 ). Evaluation of intravenous ciprofloxacin in patients with nosocomial lower respiratory tract infections. Impact of plasma concentrations, organism, minimum inhibitory concentration, and clinical condition on bacterial eradication. Archives of Internal Medicine 149 , 2269 –73. 11 Beyer, K. H., Russo, H. F., Tillson, E. K., Miller, A. K., Verwey, W. F. & Gass, S. R. ( 1951 ). Benemid, p-(di-n-propylsulfamyl)- benzoic acid: its renal affinity and its elimination. American Journal of Physiology 166 , 625 –40. 12 Krogstad, D. J. & Moellering, R. C. (1986). Antimicrobial combinations. In Antibiotics in Laboratory Medicine, 2nd edn, (Lorian, V., Ed.), pp. 537–95. Williams & Wilkins, Baltimore, MD. 13 Schentag, J. J., Strenkoski-Nix, L. C., Nix, D. E. & Forrest, A. ( 1998 ). Pharmacodynamic interactions of antibiotics alone and in combination. Clinical Infectious Diseases 27 , 40 –6. 14 Andriole, V. T. (1998). The Quinolones, 2nd edn. Academic Press, San Diego, CA. 15 Piddock, L. J. V., Johnson, M., Ricci, V. & Hill, S. L. ( 1998 ). Activities of new fluoroquinolones against fluoroquinolone-resistant pathogens of the lower respiratory tract. Antimicrobial Agents and Chemotherapy 42 , 2956 –60. 16 Blondeau, J. M. ( 1999 ). A review of the comparative in-vitro activities of 12 antimicrobial agents, with a focus on five new ‘respiratory quinolones’. Journal of Antimicrobial Chemotherapy 43 , Suppl. B, 1 –11. 17 Thornsberry, C., Jones, M. E., Hickey, M. L., Mauriz, Y. L., Kahn, J. & Sahm, D. F. ( 1999 ). Resistance surveillance of Streptococcus pnuemoniae, Haemophilus influenzae and Moraxella catarrhalis isolated in the United States, 1997–1998. Journal of Antimicrobial Chemotherapy 44 , 749 –59. 18 Ho, P. L., Que, T. K., Tsang, D. N. C., Ng, T. K., Chow, K. H. & Seto, W. H. ( 1999 ). Emergence of fluoroquinolone resistance among multiply resistant strains of Streptococcus pneumoniae in Hong Kong. Antimicrobial Agents and Chemotherapy 43 , 1310 –3. 19 Hooper, D. C. ( 2000 ). New uses for new and old quinolones and the challenge of resistance. Clinical Infectious Diseases 30 , 243 –54. 20 Chen, D. K., McGeer, A., de Azavedo, J. C. & Low, D. E. ( 1999 ). Decreased susceptibility of Streptococcus pneumoniae to fluoroquinolones in Canada. New England Journal of Medicine 341 , 233 –9. 21 Lode, H., Borner, K. & Koeppe, P. ( 1998 ). Pharmacodynamics of fluoroquinolones. Clinical Infectious Diseases 27 , 33 –9. 22 Bartlett, J. G., Brieman, R. F., Mandell, L. A. & File, T. M. ( 1998 ). Community-acquired pneumonia in adults: guidelines for management. Clinical Infectious Diseases 26 , 811 –38. 23 Campbell, G. D. ( 1999 ). Commentary on the 1993 American Thoracic Society guidelines for the treatment of community-acquired pneumonia. Chest 115 , Suppl., 14S –18S. 24 Brown, P. D. & Lerner, S. A. ( 1998 ). Community-acquired pneumonia. Lancet 352 , 1295 –302. 25 Schentag, J. J. ( 1991 ). Correlation of pharmacokinetic parameters to efficacy of antibiotics: relationships between serum concentrations, MIC values, and bacterial eradication in patients with gram-negative pneumonia. Scandinavian Journal of Infectious Diseases 74 , Suppl., 218 –34. 26 Schentag, J. J., Nix, D. E. & Forrest, A. (1993). Pharmacodynamics of the fluoroquinolones. In Quinolone Antimicrobial Agents, 2nd edn, (Hooper, D. C. & Wolfson, J. S., Eds), pp. 259–71. American Society for Microbiology, Washington, DC. 27 Blaser, J., Stone, B. B., Groner, M. C. & Zinner, S. H. ( 1987 ). Comparative study with enoxacin and netilmicin in a pharmacodynamic model to determine importance of ratio of antibiotic peak concentration to MIC for bactericidal activity and emergence of resistance. Antimicrobial Agents and Chemotherapy 31 , 1054 –60. 28 Dudley, M. N., Blaser, J., Gilbert, D., Mayer, K. H. & Zinner, S. H. ( 1991 ). Combination therapy with ciprofloxacin plus azlocillin against Pseudomonas aeruginosa: effect of simultaneous versus staggered administration in an in vitro model of infection. Journal of Infectious Diseases 164 , 499 –506. 29 Madaras-Kelly, K. J., Ostergaard, B. E., Hovde, L. B. & Rotschafer, J. C. ( 1996 ). Twenty-four hour area under the concentration–time curve/MIC ratio as a generic predictor of fluoroquinolone antimicrobial effect using three strains of Pseudomonas aeruginosa and an in vitro pharmacodynamic model. Antimicrobial Agents and Chemotherapy 40 , 627 –32. 30 Firsov, A. A., Shevchenko, A. A., Vostrov, S. N. & Zinner, S. H. ( 1998 ). Inter- and intraquinlone predictors of antimicrobial effect in an in vitro dynamic model: new insight into a widely used concept. Antimicrobial Agents and Chemotherapy 42 , 659 –65. 31 Vostrov, S., Firsov, A., Lubenko, I., Kononenko, O., Zinner, S. H. & Portnoy, Y. (1998). Predictors of quinolone antimicrobial effects in an in vitro dynamic model: the pharmacodynamics of ciprofloxacin and gatifloxacin and trovafloxacin with Staphylococcus aureus. In Program and Abstracts of the Thirty-Eighth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA, 1998. Abstract A41a, p. 13. American Society for Microbiology, Washington, DC. 32 Firsov, A. A., Vostrov, S. N., Shevchenko, A. A., Zinner, S. H., Cornaglia, G. & Portnoy, Y. A. ( 1998 ). MIC-based interspecies prediction of the antimicrobial effects of ciprofloxacin on bacteria of different susceptibilities in an in vitro dynamic model. Antimicrobial Agents and Chemotherapy 42 , 2848 –52. 33 Firsov, A. A., Vostrov, S. N., Shevchenko, A. A. & Cornaglia, G. ( 1997 ). 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. Antimicrobial Agents and Chemotherapy 41 , 1281 –7. 34 Firsov, A. A., Vostrov, S. N., Shevchenko, A. A., Zinner, S. H. & Portnoy, Y. A. ( 1998 ). A new approach to in-vitro comparisons of antibiotics in dynamic models: equivalent AUC/MIC breakpoints and equiefficient doses of trovafloxacin and ciprofloxacin against bacteria of similar susceptibility. Antimicrobial Agents and Chemotherapy 42 , 3481 –7. 35 Firsov, A. A., Vasilov, R. G., Vostrov, S. N., Kononenko, O. V., Lubenko, I. Y. & Zinner, S. H. ( 1999 ). Prediction of the antimicrobial effects of trovafloxacin and ciprofloxacin on staphylococci using an in-vitro dynamic model. Journal of Antimicrobial Chemotherapy 43 , 483 –90. 36 Wright, D. H., Hovde, L. B., Peterson, M. L., Hoang, A. D. & Rotschafer, J. C. (1998). In vitro evaluation of pharmacodynamic outcome parameters for three fluoroquinolones against Streptococcus pneumoniae. In Program and Abstracts of the Ninety-Eighth General Meeting, Atlanta, GA, 1998. Abstract A86, p. 53. American Society for Microbiology, Washington, DC. 37 Peterson, M. L., Hovde, L. B., Wright, D. H., Hoang, A. D. & Rotschafer, J. C. (1998). Pharmacodynamic outcome parameters as predictors for fluoroquinolones in the treatment of anaerobic infections. In Program and Abstracts of the Ninety-Eighth General Meeting, Atlanta, GA, 1998. Abstract A85, p. 52. American Society for Microbiology, Washington, DC. 38 Hoang, A. D., Peterson, M., Hovde, L. B., Wright, D. & Rotschafer, J. C. (1998). Investigation of AUC/MIC ratio as a generic predictor of fluoroquinolone activity against Staphylococcus aureus using trovafloxacin, ciprofloxacin, sparfloxacin, and levofloxacin and an in vitro pharmacodynamic model. In Program and Abstracts of the Ninety-Eighth General Meeting, Atlanta, GA, 1998. Abstract A71, p. 50. American Society for Microbiology, Washington, DC. 39 Brown, G. H., Hovde, L. B., Wright, D. H., Peterson, M. L. & Rotschafer, J. C. (1999). Fluoroquinolone pharmacodynamics in Bacteroides thetaiotamicron. In Program and Abstracts of the Thirty-Ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 25, p. 8. American Society for Microbiology, Washington, DC. 40 Lacy, M. K., Lu, W., Xu, X., Tessier, P. R., Nicolau, D. P., Quintiliani, R. et al. ( 1999 ). Pharmacodynamic comparisons of levofloxacin, ciprofloxacin, and ampicillin against Streptococcus pneumoniae in an in vitro model of infection. Antimicrobial Agents and Chemotherapy 43 , 672 –77. 41 Lister, P. D. & Sanders, C. C. ( 1999 ). Pharmacodynamics of trovafloxacin, ofloxacin, and ciprofloxacin against Streptococcus pneumoniae in an in vitro pharmacokinetic model. Antimicrobial Agents and Chemotherapy 43 , 1118 –23. 42 Hershberger, E. & Rybak, M. J. ( 2000 ). Activities of trovafloxacin, gatifloxacin, clinafloxacin, sparfloxacin, levofloxacin, and ciprofloxacin against penicillin-resistant Streptococcus pneumoniae in an in vitro infection model. Antimicrobial Agents and Chemotherapy 44 , 598 –601. 43 Coyle, E. A. & Rybak, M. A. (1999). Evaluation of the activity of the newer fluroquinolones against ciprofloxacin-resistant Streptococcus pneumoniae. In Program and Abstracts of the Thirty-Ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 18, p. 5. American Society for Microbiology, Washington, DC. 44 Ibrahim, K. H., Hovde, L. B., Brown, G. H. & Rotschafer, J. C. (1999). Levofloxacin pharamacodynamics vs. Streptococcus pneumoniae. In Program and Abstracts of the Thirty-Ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 2033, p. 50. American Society for Microbiology, Washington, DC. 45 Vogelman, B., Gudmundsson, S., Leggett, J., Turnidge, J., Ebert, S. & Craig, W. A. ( 1988 ). Correlation of antimicrobial pharmacokinetic parameters with therapeutic efficacy in an animal model. Journal of Infectious Diseases 158 , 831 –47. 46 Leggett, J. E., Fantin, B., Ebert, S., Totsuka, K., Vogelman, B., Calame, W. et al. ( 1989 ). Comparative antibiotic dose-effect relations at several dosing intervals in murine pneumonitis and thigh-infection models. Journal of Infectious Diseases 159 , 281 –92. 47 Fantin, B., Leggett, J., Ebert, S. & Craig, W. A. ( 1991 ). Correlation between in vitro and in vivo activity of antimicrobial agents against gram-negative bacilli in a murine infection model. Antimicrobial Agents and Chemotherapy 35 , 1413 –22. 48 Drusano, G. L., Johnson, D. E., Rosen, M. & Standiford, H. C. ( 1993 ). Pharmacodynamics of a fluoroquinolone antimicrobial agent in a neutropenic rat model of Pseudomonas sepsis. Antimicrobial Agents and Chemotherapy 37 , 483 –90. 49 Vesga, O. & Craig, W. A. (1996). Activity of levofloxacin against penicillin-resistant Streptococcus pneumoniae in normal and neutropenic mice. In Program and Abstracts of the Thirty-Sixth Interscience Conference on Antimicrobial Agents and Chemotherapy, New Orleans, LA, 1999. Abstract A59, p. 12. American Society for Microbiology, Washington, DC. 50 Vesga, O., Conklin, R., Stamstad, T. & Craig, W. A. (1996). In-vivo pharmacodynamic activity of sparfloxacin against mulitiple bacterial pathogens. In Program and Abstracts of the Thirty-Sixth Interscience Conference on Antimicrobial Agents and Chemotherapy, New Orleans, LA, 1999. Abstract A65, p. 13. American Society for Microbiology, Washington, DC. 51 Andes, D. R. & Craig, W. A. (1999). In vivo pharmacodynamic activity of gatifloxacin against multiple bacterial pathogens. In Program and Abstracts of the Thirty-Ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 191, p. 10. American Society for Microbiology, Washington, DC. 52 Andes, D. R. & Craig, W. A. (1999). In vivo pharmacodynamic activity of sitafloxacin against multiple bacterial pathogens. In Program and Abstracts of the Thirty-Ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 28, p. 9. American Society for Microbiology, Washington, DC. 53 Andes, D. R. & Craig, W. A. (1999). In vivo pharmacodynamic activity of gemifloxacin against multiple bacterial pathogens. In Program and Abstracts of the Thirty-Ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 27, p. 8. American Society for Microbiology, Washington, DC. 54 Forrest, A., Nix, D. E., Ballow, C. H., Goss, T. F., Birmingham, M. C. & Schentag, J. J. ( 1993 ). Pharmacodynamics of intravenous ciprofloxacin in seriously ill patients. Antimicrobial Agents and Chemotherapy 37 , 1073 –81. 55 Hyatt, J. M., Nix, D. E. & Schentag, J. J. ( 1994 ). Pharmacokinetic and pharmacodynamic activities of ciprofloxacin against strains of Streptococcus pneumoniae, Staphylococcus aureus, and Pseudomonas aeruginosa for which MICs are similar. Antimicrobial Agents and Chemotherapy 38 , 2730 –7. 56 Forrest, A., Chodosh, S., Amantea, M. A., Collins, D. A. & Schentag, J. J. ( 1997 ). Pharmacokinetics and pharmacodynamics of oral grepafloxacin in patients with acute bacterial exacerbations of chronic bronchitis. Journal of Antimicrobial Chemotherapy 40 , Suppl. A, 45 –57. 57 Thomas, J. K., Forrest, A., Bhavnani, S. M., Hyatt, J. M., Cheng, A., Ballow, C. H. et al. ( 1998 ). Pharmacodynamic evaluation of factors associated with the development of bacterial resistance in acutely ill patient during therapy. Antimicrobial Agents and Chemotherapy 42 , 521 –7. 58 Hershberger, E., Coyle, E. A., Kaatz, G. W., Zervos, M. J. & Rybak, M. J. (1999). In vitro fibrin-clot infection model versus rabbit model of bacterial endocarditis. In Program and Abstracts of the Thirty-Ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 23, p. 7. American Society for Microbiology, Washington, DC. 59 Firsov, A., Zinner, S., Lubenko, I., Portnoy, Y. & Vostrov, S. (1999). Prediction of the equivalent fluoroquinolone AUC/MIC breakpoints based on pharmacodynamic studies with in vitro dynamic models: in vitro–in vivo correlation. In Program and Abstracts of the Thirty-Ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 24, p. 7. American Society for Microbiology, Washington, DC. 60 Forbes, B. A., Sahm, D. F. & Weissfeld, A. S. (1998). Bailey and Scott’s Diagnostic Microbiology, 10th edn. Mosby, St Louis, MO. 61 Zabinski, R. A., Walker, K. J., Larsson, A. J., Moody, J. A., Kaatz, G. W. & Rotschafer, J. C. ( 1995 ). Effect of aerobic and anaerobic environments on antistaphylococcal activities of five fluoroquinolones. Antimicrobial Agents and Chemotherapy 39 , 507 –12. 62 FDA website. CDER. New and generic drug approvals 1998–2000. Tequin. [Online.] http://www.fda.gov/cder/approval/index.htm [6 July 2000, last date accessed.] 63 Kelly, L. M., Jacobs, M. R. & Appelbaum, P. C. ( 1999 ). Comparison of agar dilution, microdilution, E-test, and disk diffusion methods for testing activity of cefditoren against Streptococcus pneumoniae. Journal of Clinical Microbiology 37 , 3296 –9. 64 Clark, C. L., Jacobs, M. R. & Appelbaum, P. C. ( 1998 ). Antipneumococcal activities of levofloxacin and clarithromycin as determined by agar dilution, microdilution, E-test, and disk diffusion methodologies. Journal of Clinical Microbiology 36 , 3579 –84. 65 Jenks, P. J., Akalin, E., Bergan, T., Dornbusch, K., Howard, A. J., Hryniewicz, W. et al. ( 1998 ). Susceptibility testing of Klebsiella spp.—an international collaborative study in quality assessment. Journal of Antimicrobial Chemotherapy 42 , 29 –48. 66 Traub, W. H., Geipel, U. & Leonhard, B. ( 1998 ). Antibiotic susceptibility testing (agar disk diffusion and agar dilution) of clinical isolates of Enterococcus faecalis and E. faecium: comparison of Mueller–Hinton, Iso-Sensitest, and Wilkins–Chalgren agar media. Chemotherapy 44 , 217 –29. 67 Cunha, B. A. ( 1997 ). Problems arising in antimicrobial therapy due to false susceptibility testing. Journal of Chemotherapy 9 , Suppl. 1, 25 –35. 68 National Committee for Clinical Laboratory Standards. (1997). Methods for Dilution Antimicrobial Susceptibility Tests for Bacteria that Grow Aerobically—Fourth Edition: Approved Standard M7-A4. NCCLS, Villanova, PA. 69 Fuchs, P. C., Barry, A. L., Pfaller, M. A., Allen, S. D. & Gerlach, E. H. ( 1991 ). Muliticenter evaluations of the in vitro activities of three new quinolones, sparfloxacin, CI-960, and PD 131,628, compared with the activity of ciprofloxacin against 5,252 clinical bacterial isolates. Antimicrobial Agents and Chemotherapy 35 , 764 –6. 70 Jones, M. E., Visser, M. R., Klootwijk, M., Heisig, P., Verhoef, J. & Schmitz, F.-J. ( 1999 ). Comparative activities of clinafloxacin, grepafloxacin, levofloxacin, moxifloxacin, ofloxacin, sparfloxacin, and trovafloxacin and nonquinolones linozelid, quinupristin–dalfopristin, gentamicin, and vancomycin against clinical isolates of ciprofloxacin-resistant and -susceptible Staphylococcus aureus strains. Antimicrobial Agents and Chemotherapy 43 , 421 –3. 71 Jorgensen, J. H., Weigel, L. M., Ferraro, M. J., Swenson, J. M. & Tenover, F. C. ( 1999 ). Activities of newer fluoroquinolones against Streptococcus pneumoniae clinical isolates including those with mutations in the gyrA, parC, and parE loci. Antimicrobial Agents and Chemotherapy 42 , 329 –34. 72 Goldstein, E. J. C., Citron, D. M., Merriam, C. V., Tyrrell, K. & Warren, Y. ( 1999 ). Activity of gatifloxacin compared to those of five other quinolones versus aerobic and anaerobic isolates from skin and soft tissue samples of human and animal bite wound infections. Antimicrobial Agents and Chemotherapy 43 , 1475 –9. 73 Wise, R. & Andrews, J. M. ( 1997 ). The activity of grepafloxacin against respiratory pathogens in the UK. Journal of Antimicrobial Chemotherapy 40 , Suppl. A, 27 –30. 74 Bertek Pharmaceuticals. (1998). Zagam prescribing information. Sugarland, TX, October 1998. 75 Bayer Corporation. (1999). Avelox prescribing information. West Haven, CT, December 1999. © 2000 The British Society for Antimicrobial Chemotherapy
TI - Application of fluoroquinolone pharmacodynamics
JF - Journal of Antimicrobial Chemotherapy
DO - 10.1093/jac/46.5.669
DA - 2000-11-01
UR - https://www.deepdyve.com/lp/oxford-university-press/application-of-fluoroquinolone-pharmacodynamics-2xekHLiIN4
SP - 669
VL - 46
IS - 5
DP - DeepDyve
ER -