a Department of Pharmacokinetics, Centre for Science & Technology LekBioTech, and b Department of Pharmacokinetics and Pharmacodynamics, Gause Institute of New Antibiotics, Russian Academy of Medical Sciences, Moscow, Russia; c Mount Auburn Hospital, Harvard Medical School, Cambridge, MA, USA
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Abstract |
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Introduction |
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Similarities or differences in efficacy between these two macrolides might better correlate with their tissue concentrations than their plasma concentrations. Furthermore, a true understanding of comparative macrolide pharmacodynamics should be based on appropriate in vitro simulations of tissue rather than plasma pharmacokinetics, as reported in experiments with clarithromycin6 or erythromycin7 compared with azithromycin. The present study compares the antimicrobial effects of azithromycin and roxithromycin using an in vitro model simulating their pharmacokinetics in a specific peripheral tissue, human tonsils.
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Materials and methods |
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Azithromycin and roxithromycin powders were kindly provided by Roerig, a division of Pfizer Pharmaceuticals, (Groton, CT, USA) and Hoechst-Marion-Roussel (Bridgewater, NJ, USA), respectively. Clinical isolates of Streptococcus pyogenes and Streptococcus pneumoniae with similar susceptibility to both macrolides were used in the study. MICs determined by multiple serial dilutions were 0.12 and 0.47 mg/L of azithromycin and 0.15 and 0.60 mg/L of roxithromycin, respectively.
Simulated pharmacokinetic profiles
The simulated pharmacokinetic profiles reflected steady-state tonsillar concentrations of the macrolides expected after a third dose of azithromycin 500 mg od and after a sixth dose of roxithromycin 150 mg bd.
Azithromycin.
To calculate the steady-state concentrations of azithromycin in human tonsils, pharmacokinetic data from a 500 mg single dose study2 and a study that used two 250 mg doses administered 12 hourly8 were combined. The first study measured azithromycin concentrations in homogenized tonsils from 1 to 12 h post-dose, whereas the second study used data obtained between 13 and 178 h, without reference to the ascending limb of the concentrationtime curve (Figure 1a). The combined data set was fitted by the Bateman function:
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Roxithromycin.
Steady-state concentrations of roxithromycin in homogenized tonsils have been reported in humans after twice daily administration of 150 mg for 3 days3 (Figure 1c). The concentrationtime data were fitted by equation 1
, taking into account the residual antibiotic concentration after its preceding dose, i.e. the fifth dose. This steady-state pharmacokinetic profile is presented as the sum of mono- and bi-exponential (Bateman) functions. The estimated parameters of equation 1
are shown in the Table.
In vitro dynamic model
A slightly modified version of a previously described dynamic model9 was used. Pharmacokinetically, the model consists of two compartments: subcompartment 0, which mimics mono-exponential drug efflux from the systemic circulation to tonsillar tissue; and compartment 1, which mimics drug pharmacokinetics in tonsils, obeying the Bateman function. Mono-exponential efflux of antibiotic is provided by continuous dilution of antibiotic solution of volume in subcompartment 0 (V0) with fresh nutrient medium with a flow rate F. Bi-exponentially changing concentrations of antibiotic in compartment 1 of volume V1 are provided by continuous influx of antibiotic solution in nutrient medium from subcompartment 0 and by efflux of antibiotic solution from compartment 1 to the waste with the same flow rate F. Based on azithromycin and roxithromycin pharmacokinetic parameters, F, V0 and V1 were calculated as described elsewhere.10 The respective values of F, V0 and V1 are presented in the Table. To simulate the mono-exponential decay of residual antibiotic concentrations from the preceding dose, azithromycin or roxithromycin was administered into compartment 1 to achieve the desired level (8.4 and 1.0 mg/L, respectively). To simulate the lag-time in tonsillar drug appearance, antibiotics were administered into subcompartment 0 1 h after their administration into compartment 1.
Physically, the model was represented by three connected flasks: one containing fresh trypticase soy broth with 10% pooled horse serum; the second, subcompartment 0, containing the same broth; and the third, compartment 1, containing the broth plus a bacterial culture (Figure 2). The third flask had a magnetic stirrer and was incubated at 37°C. The system was filled with sterile broth. The medium in the third flask was inoculated with a 24 h culture of S. pyogenes or S. pneumoniae, and after a further 2 h incubation, when exponentially growing cultures approached c. 106 cfu/mL, azithromycin or roxithromycin was injected into the third flask and 1 h later into the second flask. Peristaltic pumps circulated fresh nutrient medium from the first flask to the second flask and then to the third flask, as well as from the third flask to the waste chamber. The volumes of fluids in the second and third flasks were maintained constant during the experiment.
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The ability of the dynamic model to simulate the required pharmacokinetic profiles of azithromycin and roxithromycin was tested using ciprofloxacin, because levels of this drug can be measured easily with good reliability and sensitivity. The pharmacokinetic parameters of azithromycin and roxithromycin were produced in the model in triplicate using ciprofloxacin. To verify the suitability of the use of ciprofloxacin as a marker for the macrolides, parallel determinations of ciprofloxacin and roxithromycin were also performed when 10-fold greater concentrations of roxithromycin and ciprofloxacin with pharmacokinetic parameters of roxithromycin were simulated simultaneously.
Assays
Ciprofloxacin concentrations were assayed by highperformance liquid chromatography (HPLC) with a precolumn (50 x 4.6 mm) and on a column (250 x 4.6 mm) of Silasorb 5 C8 (Lachema, Czech Republic). The mobile phase was 0.02 M KH2PO4, ethanol and acetonitrile (70:20:10 v/v), pumped at a flow rate of 1.3 mL/min. Fluorometric detection (274 nm excitation, 418 nm emission) was used. The detection limit was 0.05 mg/L. The calibration curve was linear within the range 0.120 mg/L, and the coefficients of variation at ciprofloxacin 10 and 1 mg/L were 2.2% and 3.4%, respectively.
Roxithromycin concentrations were also determined by HPLC using a precolumn (50 x 4.6 mm) and on a column (250 x 4 mm) with Nucleosil 10 C18 (Macherey-Nagel, Germany). The mobile phase consisted of acetonitrile and 0.067 M phosphate buffer pH 4 (45:55 v/v), pumped at a flow rate of 1.1 mL/min. Detection was by UV absorption at 210 nm. The calibration curve was linear for roxithromycin concentrations ranging from 1 to 20 mg/L, the limit of detection was 0.5 mg/L and the coefficient of variation at roxithromycin 10 mg/L was 2.4%.
Quantification of bacterial growth and killing
In each experiment, 0.1 mL samples were withdrawn from bacteria-containing media in the central compartment (the third flask) throughout the observation period, initially every hour, then every 3 h, and again hourly during the last 67 h. These samples were subjected to serial 10-fold dilutions with chilled, sterile 0.9% NaCl and were plated in duplicate on trypticase soy agar supplemented with 10% pooled horse serum. After overnight incubation at 37°C in a 5% CO2 atmosphere, the resulting bacterial colonies were counted, and the numbers of cfu/mL were calculated. The limit of accurate quantification was 2 x 102 cfu/mL. A level of 10 cfu/mL was considered a theoretically achievable limit of detection.
The bacterial elimination rate constant (kelb) as a measure of the rate of initial killing was determined as described elsewhere.11 The area between the control growth curve and the timekill curve of antibiotic-exposed bacteria (ABBC)12 as an integral measure of the antimicrobial effect was determined over the first 12 h (Figure 3).
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Results |
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The suitability of ciprofloxacin as a marker for the macrolides was verified by simultaneous simulation of roxithromycin and ciprofloxacin with the pharmacokinetic parameters of roxithromycin. As seen in Figure 4a, the concentrations of ciprofloxacin in compartment 1 of the dynamic model matched those of roxithromycin. This validated the use of ciprofloxacin alone in the further model validation experiments. As seen in Figure 4 (b and c
), the concentrations of ciprofloxacin determined with the pharmacokinetic parameters of azithromycin and roxithromycicn were close to the expected pharmacokinetic profiles.
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The timekill kinetics of S. pyogenes and S. pneumoniae exposed to the macrolides and the respective control growth curves are presented in Figure 5. Azithromycin produced rapid killing of S. pyogenes and S. pneumoniae, with no regrowth for at least 48 h; the viable counts reached the theoretical limit of detection 810 h after drug administration. In contrast to azithromycin, S. pyogenes and S. pneumoniae exposed to roxithromycin regrew 26 or 6 h, respectively, after initial rapid reduction of the starting inoculum. The differences between the antimicrobial effects of azithromycin and roxithromycin can be seen over the first 12 h, i.e. within the dosing interval of roxithromycin. Using ABBC as an endpoint of the antimicrobial effect, azithromycin is 22% more efficient against S. pyogenes and 36% more efficient against S. pneumoniae than roxithromycin (ABBC of 78 versus 64, and 72 versus 53 log cfu/mLh, respectively). However, the rates of azithromycin- and roxithromycin-induced killing were similarwith S. pyogenes the respective kelbs were 1.4/h and 1.3/h, and with S. pneumoniae the kelbs were 1.3/h and 1.5/h, respectively.
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Discussion |
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Unfortunately, the realities of in vitro simulations of specific tissue pharmacokinetics are limited by the availability of in vivo data: all too often, reported tissue concentrations are too sparse to allow appropriate model fitting. Paradoxically, this applies to the new macrolides, although their excellent tissue penetration was a major driving force in their development. Moreover, most in vivostudies, including those used as a basis for our in vitrosimulations, report macrolide concentrations in homogenized tissues, i.e. the sum of relatively high interstitial and relatively low extracellular concentrations, which are in a dynamic equilibrium with plasma concentrations of free (i.e. non-protein-bound) drug.13 Although extracellular concentrations of macrolides are considered more predictive of their antimicrobial effect on most common respiratory tract pathogens,14 this may not explain reported similar efficacies of azithromycin, roxithromycin and clarithromycin in upper respiratory tract infections,5,15 and azithromycin and clarithromycin in streptococcal tonsillitis,15 despite the markedly lower extracellular concentrations of azithromycin.
This study demonstrated the more pronounced antimicrobial effects of simulated tonsillar concentrations of azithromycin compared with those of roxithromycin against S. pyogenes and S. pneumoniae. Despite similar rates of initial killing, the antibacterial effects as expressed by the ABBC determined over the first 12 h of antibiotic exposure were 22% and 36% greater with azithromycin than with roxithromycin, respectively. Moreover, no regrowth occurred with S. pyogenes and S. pneumoniae exposed to azithromycin, but bacterial regrowth was observed 26 or 6 h, respectively, after administration of roxithromycin.
Clearly, these differences would not have been seen with an in vitro simulation of plasma concentrations of these macrolides, which are much higher with roxithromycin than azithromycin. In this light, the more pronounced killing of bacteria exposed to plasma concentrations of clarithromycin compared with azithromycin reported by Bauernfeind et al.6 is quite predictable, because the simulated peak concentration-to-MIC ratios were 520 times higher for clarithromycin with four of the five organisms studied. Other conclusions might have been drawn if peripheral tissue pharmacokinetics of clarithromycin and azithromycin were simulated.
Overall, the results of pharmacodynamic comparisons among the tissue-selective macrolides might be highly dependent on whether systemic or peripheral pharmacokinetics are simulated. Care must be taken in deciding which model is most relevant to the clinical situation.
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Acknowledgements |
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Notes |
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References |
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Received 23 November 2000; returned 4 July 2001; revised 6 September 2001; accepted 17 September 2001