Pharmacokinetic/pharmacodynamic modeling of in vitro activity of azithromycin against four different bacterial strains
Introduction
The parameter most commonly used to quantify the antimicrobial activity of antibiotics against a certain bacterium is usually the minimum inhibitory concentration (MIC). It is defined as the lowest concentration of drug that prevents visible growth of the organism as detected by the unaided eye [1]. Although the MIC is a well-established pharmacodynamic (PD) parameter routinely determined in microbiology, this parameter has several disadvantages. For instance, the MIC does not provide information on the rate of bacterial kill. Since the MIC determination depends on the number of bacteria at a single time-point, many different combinations of growth and kill rates can result in the same MIC. Antibacterial activity is a dynamic process whereas MIC is only a threshold value, a one-point measurement with poor precision determined in two-fold dilution steps [2]. An alternative PD approach, bacterial time–kill curves, has been proposed to offer detailed information about the antibacterial efficacy as a function of both time and antibiotic concentration [3]. Time–kill curves of many antibacterial agents have been studied in both in vitro kinetic models and animal infection models.
To date, pharmacokinetic/pharmacodynamic (PK/PD) modeling has become a powerful tool to evaluate the antimicrobial effect of antibiotics. An Emax model has been successfully applied to describe the relationship between concentration and effect in many drug classes [4], [5]. There have been some attempts to evaluate antimicrobial activity with an adapted Emax model [6]. Some parameters such as the maximum number of bacteria (Nmax) at the end of the growth phase, adaptation rate terms (x, y, z) and Hill factor (h) have been included in a PK/PD model to optimize these models [7].
Previously, several β-lactam and fluoroquinolone antibiotics have been evaluated in our group for their antibacterial activities at different dosing regimens: piperacillin [2], piperacillin–tazobactam [4], cefaclor [5], faropenem [8] and ciprofloxacin [9]. In all cases the Emax model allowed good characterization of the observed antimicrobial effects.
Azithromycin, a 15-membered macrolide, is a commonly prescribed antibacterial agent used to treat respiratory tract infections [10]. The American Thoracic Society and the Infectious Diseases Society of America have recommended a macrolide as a viable first-line option for treating community-acquired pneumonia [11]. In the present study, four bacterial strains, S. pneumoniae (penicillin-intermediate), S. pneumoniae (penicillin-sensitive), H. influenzae and M. catarrhalis, the most common causes of community-acquired pneumonia, were tested.
The purpose of this study was to investigate the PD effect of azithromycin by evaluating in vitro time–kill curves against four common bacterial strains and to establish a mathematical model to describe the PK/PD relationship of azithromycin.
Section snippets
Drugs and bacteria
Azithromycin was provided by Pfizer Inc., Groton, CT, USA. Four different bacterial strains: S. pneumoniae (penicillin-intermediate) ATCC® 49619, S. pneumoniae (penicillin-sensitive) ATCC® 6303, H. influenzae ATCC® 10211 and M. catarrhalis ATCC® 8176 were obtained from the microbiology laboratory in Shands Hospital at the University of Florida, Gainesville, FL, USA.
Broth preparation
Mueller–Hinton broth (MHB; Becton Dickinson, Franklin Lakes, NJ, USA) and Todd–Hewitt broth (THB; Difco, Detroit, USA) were both
MIC values and azithromycin time–kill curve concentrations
The determined MIC values and azithromycin concentrations used in the time–kill curve experiments against the four bacterial strains are summarized in Table 1. Overall, the results obtained in this study were consistent with the reported MIC values [12], [13], [14].
Comparison of the investigated models
Simulated effects of the different parameters, incorporated in the modified Emax models, are shown in Fig. 1. Fig. 1A shows a simple Emax model (model 1) without any delay or saturation terms. In Fig. 1B (model 2) the onset of growth
Discussion
In this study we have used two different PK/PD approaches (MIC and time–kill curve) to evaluate the antimicrobial efficacy of the second generation macrolide azithromycin [15] against four different bacterial strains. Although widely used, MICs do not provide a very detailed characterization of antimicrobial activity [16]. Therefore, the more sophisticated time–kill curve approach was used. Compared to the MIC, one of the main advantages of the kill curve approach is the PD effect can be
References (29)
- et al.
Rational dosing of antibiotics: the use of plasma concentrations versus tissue concentrations
Int J Antimicrob Agents
(2002) - et al.
In vitro activity of telithromycin compared with macrolides and fluoroquinolones against Streptococcus pneumoniae, Haemophilus influenzae and Moraxella catarrhalis
Int J Antimicrob Agents
(2003) - et al.
Eradication of H. influenzae in AECB: a pooled analysis of moxifloxacin phase III trials compared with macrolide agents
Respir Med
(2006) - et al.
In vitro activity and pharmacodynamics of azithromycin and clarithromycin against Streptococcus pneumoniae based on serum and intrapulmonary pharmacokinetics
Clin Ther
(2001) - et al.
Characteristics and mechanisms of azithromycin accumulation and efflux in human polymorphonuclear leukocytes
Int J Antimicrob Agents
(2001) - et al.
Issues in pharmacokinetics and pharmacodynamics of anti-infective agents: kill curves versus MIC
Antimicrob Agents Chemother
(2004) - et al.
Pharmacokinetic-pharmacodynamic modeling of the antibiotic effect of piperacillin in vitro
Pharm Res
(1996) - et al.
Pharmacokinetic-pharmacodynamic modelling of the in vitro antiinfective effect of piperacillin-tazobactam combinations
Int J Clin Pharmacol Ther
(1997) - et al.
PK-PD modelling of the effect of cefaclor on four different bacterial strains
Int J Antimicrob Agents
(2004) - et al.
A combined in vivo pharmacokinetic-in vitro pharmacodynamic approach to simulate target site pharmacodynamics of antibiotics in humans
J Antimicrob Chemother
(2000)
Pharmacokinetic-pharmacodynamic modeling of activity of ceftazidime during continuous and intermittent infusion
Antimicrob Agents Chemother
The macrolide antibiotics: a pharmacokinetic and pharmacodynamic overview
Curr Pharm Des
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