New pharmacodynamic parameters for antimicrobial agents

Li, Ronald C.

doi:10.1016/s0924-8579(99)00114-4

Cited by 17 publications

(17 citation statements)

References 46 publications

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“…The CFU for each incubation time point per milliliter is determined, and plotted as a function of time, resulting in "time-kill" curves for each drug combination tested. Time-kill methods have been commonly used for testing bactericidal activity of antimicrobial agents (5,9,25,92,102,131), and recent studies have focused on using this method to determine the efficacy of antifungal agents also, both singly and in combination (27,60,62,63,105,107,108,123,126,129). For antifungal interactions tested by time-kill methods (at 24 to 48 h), the following criteria are commonly followed: (i) synergy is defined as a Ն2 log 10 decrease in CFU per milliliter compared to the most active constituent, (ii) antagonism is defined as a Ն2 log 10 increase in CFU per milliliter compare to the least active agent, (iii) additivity is defined as a Ͻ2 but Ͼ1 log 10 decrease in CFU per milliliter compared to the most active agent, and (iv) indifference is defined as a Ͻ2 but Ͼ1 log 10 increase in CFU per milliliter compared to the least active agent (123,126,127), (Fig.…”

Section: Time-kill Methodsmentioning

confidence: 99%

Combination Treatment of Invasive Fungal Infections

et al. 2005

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The persistence of high morbidity and mortality from systemic fungal infections despite the availability of novel antifungals points to the need for effective treatment strategies. Treatment of invasive fungal infections is often hampered by drug toxicity, tolerability, and specificity issues, and added complications often arise due to the lack of diagnostic tests and to treatment complexities. Combination therapy has been suggested as a possible approach to improve treatment outcome. In this article, we undertake a historical review of studies of combination therapy and also focus on recent studies involving newly approved antifungal agents. The limitations surrounding antifungal combinations include nonuniform interpretation criteria, inability to predict the likelihood of clinical success, strain variability, and variations in pharmacodynamic/pharmacokinetic properties of antifungals used in combination. The issue of antagonism between polyenes and azoles is beginning to be addressed, but data regarding other drug combinations are not adequate for us to draw definite conclusions. However, recent data have identified potentially useful combinations. Standardization of assay methods and adoption of common interpretive criteria are essential to avoid discrepancies between different in vitro studies. Larger clinical trials are needed to assess whether combination therapy improves survival and treatment outcome in the most seriously debilitated patients afflicted with life-threatening fungal infections

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Section: Time-kill Methodsmentioning

confidence: 99%

Combination Treatment of Invasive Fungal Infections

et al. 2005

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“…It follows the patterns of random cell division, which has been confirmed by a mathematical modeling approach [20]. However, turbidity only reflects the total cell numbers, it cannot distinguish between dividing and resting cells, and the dividing cells are usually used to be the objective function [10][11][12][13]. In general, the existence of resting cells could be eliminated by determining the net increase in turbidity, because the net increase in optical density (A) (A net =(A i+1 −A i )/(t i+1 −t i )) cannot be influenced by the existence of resting cells.…”

Section: Employing Rc Changes For Growth Sequence Turbidity To Characmentioning

confidence: 85%

“…The inhibition of drugs should be analyzed by comparing the dynamic growth processes of bacteria under drug and drug-free conditions [10]. Research on pharmacokinetics (PK) and pharmacodynamics (PD) indicated that the effective action time was an important factor that closely corresponded with the effect of treatment [11][12][13]. The results of various dilution methods and disk diffusion were all obtained from overnight culture, which was based on "the judgment of terminal concentration", and was chosen to be the only basis for analyzing the action time [1][2][3][4].…”

mentioning

confidence: 99%

“…In order to obtain the results of quantitative analysis, the drug concentration should be logarithmically translated and then regressed to be a straight line; therefore, a formula of inhibition rate and concentration can be established by linear regression and the inhibition rate can be obtained from this formula [1][2][3][4]. However, this method not only altered the functional relationship between the drug concentration and inhibition rate, but also does not reflect the impact of the action time of the drug [3,6,7,11,12]. Recently, new methods proposed for testing the combined effect of drug concentration and action time, such as the "time-dose mortality model", "Time above MIC" and "Ratio of AUC/MIC" [14][15][16], have provided a basis of statistical analysis, but an operational method that can be commonly used is still needed.…”

mentioning

confidence: 99%

“…In addition, because proliferating cells have a certain life cycle, and the occurrence of division has a certain probability, there will always be a certain number of cells that cannot grow or proliferate. The toxin is usually derived from the gene expression of proliferating cells [10][11][12][13]17], indicating that AST should use proliferating cells, but the question of how to distinguish proliferating and non-proliferating cells remains unsolved.…”

mentioning

confidence: 99%

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A novel approach for assessing the susceptibility of Escherichia coli to antibiotics

Zhang

Zhao

XiuLi

et al. 2010

Sci. China Life Sci.

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The dynamic growth process of Escherichia coli CVCC249 under different concentrations of antibiotics was analyzed. The results suggested that the main reason that definitive results cannot be obtained by antibiotic susceptibility testing (AST) is that the ratio of drug concentration to the population of bacteria and the combined effect of drug concentration and action time cannot be completely determined with the methods used. Based on the analysis of the growth process with a series of concentrations of gentamicin acting for a certain time, and according to the forward difference method, a novel method for AST was proposed. The net increase in turbidity of the bacterial population was used to eliminate the existing effects of resting cells, and then the recurrent coefficient for a growing sequence was used to characterize the effect of antibiotics on bacterial division, and the contour plot was used to display and analyze the combined effect of drug concentration and action time. The inhibition rate of the antibiotics can be characterized as the dynamic change in the composite function of the antibiotic concentration and action time, which indicated that the inhibition rate was dependent on the combined effect of time and concentration of antibiotics. The effectiveness of this new method has been verified with different kinds of antibiotics, such as enrofloxacin, levofloxacin, and ceftriaxone, having different antibacterial mechanisms.

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A Stochastic Formulation of the Gompertzian Growth Model forin vitro Bactericidal Kinetics: Parameter Estimation and Extinction Probability

Ferrante¹,

Bompadre

Leone

et al. 2005

Biom. J.

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Time-kill curves have frequently been employed to study the antimicrobial effects of antibiotics. The relevance of pharmacodynamic modeling to these investigations has been emphasized in many studies of bactericidal kinetics. Stochastic models are needed that take into account the randomness of the mechanisms of both bacterial growth and bacteria-drug interactions. However, most of the models currently used to describe antibiotic activity against microorganisms are deterministic. In this paper we examine a stochastic differential equation representing a stochastic version of a pharmacodynamic model of bacterial growth undergoing random fluctuations, and derive its solution, mean value and covariance structure. An explicit likelihood function is obtained both when the process is observed continuously over a period of time and when data is sampled at time points, as is the custom in these experimental conditions. Some asymptotic properties of the maximum likelihood estimators for the model parameters are discussed. The model is applied to analyze in vitro time-kill data and to estimate model parameters; the probability of the bacterial population size dropping below some critical threshold is also evaluated. Finally, the relationship between bacterial extinction probability and the pharmacodynamic parameters estimated is discussed.

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New pharmacodynamic parameters for antimicrobial agents

Cited by 17 publications

References 46 publications

Combination Treatment of Invasive Fungal Infections

Combination Treatment of Invasive Fungal Infections

A novel approach for assessing the susceptibility of Escherichia coli to antibiotics

A Stochastic Formulation of the Gompertzian Growth Model forin vitro Bactericidal Kinetics: Parameter Estimation and Extinction Probability

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