Kinetics and Mechanisms of Drug Action on Microorganisms XVII: Bactericidal Effects of Penicillin, Kanamycin, and Rifampin with and without Organism Pretreatment with Bacteriostatic Chloramphenicol, Tetracycline, and Novobiocin

Garrett, Edward R.; Won, Chong Min

doi:10.1002/jps.2600621018

Cited by 31 publications

(10 citation statements)

References 21 publications

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“…4E). At threshold densities of 10 5 and lower, emergence of resistance occurs at equivalent rates that are lower than for the corresponding thresholds under PDD immune dynamics (Fig. 4F).…”

Section: Resultsmentioning

confidence: 90%

“…Although there have been efforts to develop more comprehensive measures of the relationship between the concentration of antibiotics and rate of bacterial growth (e.g., see refs. [3][4][5], in practice the lowest antibiotic concentration required to prevent the in vitro growth of the bacteria [the minimum inhibitory concentration (MIC)] is the sole pharmacodynamic parameter used for these indices (6). Depending on the drug, one of three PK parameters that quantify drug availability is combined with the MIC to generate these PK/PD indices: (i) the ratio of the peak antibiotic concentration achieved in vivo to the MIC, C MAX /MIC, (ii) the ratio of the area under the concentration-time curve to the MIC, AUC/MIC, and (iii) the amount of time the antibiotic concentration exceeds the MIC, T > MIC.…”

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confidence: 99%

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Exploring the collaboration between antibiotics and the immune response in the treatment of acute, self-limiting infections

Ankomah

Levin

2014

Proc. Natl. Acad. Sci. U.S.A.

128

139

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The successful treatment of bacterial infections is the product of a collaboration between antibiotics and the host's immune defenses. Nevertheless, in the design of antibiotic treatment regimens, few studies have explored the combined action of antibiotics and the immune response to clearing infections. Here, we use mathematical models to examine the collective contribution of antibiotics and the immune response to the treatment of acute, self-limiting bacterial infections. Our models incorporate the pharmacokinetics and pharmacodynamics of the antibiotics, the innate and adaptive immune responses, and the population and evolutionary dynamics of the target bacteria. We consider two extremes for the antibiotic-immune relationship: one in which the efficacy of the immune response in clearing infections is directly proportional to the density of the pathogen; the other in which its action is largely independent of this density. We explore the effect of antibiotic dose, dosing frequency, and term of treatment on the time before clearance of the infection and the likelihood of antibiotic-resistant bacteria emerging and ascending. Our results suggest that, under most conditions, high dose, full-term therapy is more effective than more moderate dosing in promoting the clearance of the infection and decreasing the likelihood of emergence of antibiotic resistance. Our results also indicate that the clinical and evolutionary benefits of increasing antibiotic dose are not indefinite. We discuss the current status of data in support of and in opposition to the predictions of this study, consider those elements that require additional testing, and suggest how they can be tested.population dynamics | immunology T he goals of antibiotic treatment of bacterial infections are straightforward and interrelated: to maximize the likelihood and rate of cure, to minimize the toxic and other deleterious side effects of treatment, and to minimize the likelihood of resistance emerging during the course of therapy. How does one choose the most effective antibiotic(s) for a given infection and determine its optimum dose, frequency, and term of administration to achieve these goals?One answer has been to combine in vitro studies of the pharmacodynamics (PD) of the antibiotics and bacteria and the in vivo pharmacokinetics (PK) of the antibiotics in treated patients or model organisms (1, 2). Central to this "rational" (as opposed to purely empirical) approach to antibiotic treatment are PK/PD indices. Although there have been efforts to develop more comprehensive measures of the relationship between the concentration of antibiotics and rate of bacterial growth (e.g., see refs. 3-5), in practice the lowest antibiotic concentration required to prevent the in vitro growth of the bacteria [the minimum inhibitory concentration (MIC)] is the sole pharmacodynamic parameter used for these indices (6). Depending on the drug, one of three PK parameters that quantify drug availability is combined with the MIC to generate these PK/PD indices: (i) the r...

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“…4E). At threshold densities of 10 5 and lower, emergence of resistance occurs at equivalent rates that are lower than for the corresponding thresholds under PDD immune dynamics (Fig. 4F).…”

Section: Resultsmentioning

confidence: 90%

mentioning

confidence: 99%

Exploring the collaboration between antibiotics and the immune response in the treatment of acute, self-limiting infections

Ankomah

Levin

2014

Proc. Natl. Acad. Sci. U.S.A.

128

139

View full text Add to dashboard Cite

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“…where k 0 is the growth rate constant in absence of drug, k i is the kill rate constant, C is the drug concentration, and C i is the minimum drug concentration that will produce an effect (50). Using a different mathematical approach, the growth curves for bacteria exposed to different antibiotic concentrations were described taking into account the effect lag time after initial drug exposure.…”

Section: Models With Constant Antibiotic Concentrationmentioning

confidence: 99%

Issues in Pharmacokinetics and Pharmacodynamics of Anti-Infective Agents: Kill Curves versus MIC

Mueller

Peña

Derendorf

2004

Antimicrob Agents Chemother

269

233

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“…The MIC and the MBC are conventional measurements of antibiotic activity in vitro. However, data obtained from timekill studies have also been frequently used to estimate the relative potencies between different antibiotics and to analyze antibiotic-receptor interactions or structure-activity relationships (4,7,8,11). A typical time-kill curve exhibited by most antibiotics consists of three distinctive phases: a lag phase, a log-linear killing phase, and a regrowth phase (6,9,17).…”

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confidence: 99%

“…Garrett and Won in their study of the antibacterial effects of penicillin-G, kanamycin, and rifampin against Escherichia coli have proposed that antibiotic permeation into bacterial cells may be responsible for this lag period (4). However, the existence of a rate-limiting step between antibiotic-receptor binding and the final expression of cell death as previously proposed (10,15) has not been addressed.…”

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confidence: 99%

Simultaneous pharmacodynamic analysis of the lag and bactericidal phases exhibited by beta-lactams against Escherichia coli

1996

Antimicrob Agents Chemother

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Antibiotic-bacterium interactions are complex in nature. In many cases, bacterial killing does not commence immediately after the addition of an antibiotic, and a lag period is observed. Antibiotic permeation and/or the intermediate steps that exist between antibiotic-receptor binding and expression of cell death are two major possible causes for such lag period. This study was primarily designed to determine the relationship, if any, between antibiotic concentrations and the lag periods by a modeling approach. Short-term time-kill studies were conducted for amoxicillin, ampicillin, penicillin-G, oxacillin, and dicloxacillin against Escherichia coli. In conjunction with the use of a saturable rate model to describe the concentration-dependent killing process, a first-order induction (initiation) rate constant was used to characterize the delay in bacterial killing during the lag period. For all of the beta-lactams tested, parameters describing the bactericidal effect suggest that amoxicillin and ampicillin were much more potent than oxacillin and dicloxacillin. The induction rate constant estimates for both ampicillin and amoxicillin were found to relate linearly to concentrations. Nevertheless, these induction rate constant estimates were lower for penicillin-G, oxacillin, and dicloxacillin and increased nonlinearly with concentrations until an apparent plateau was observed. These findings support the hypothesis that the permeation process is potentially a rate-limiting step for the rapid bactericidal beta-lactams such as ampicillin and amoxicillin. However, as suggested by previous observations of the various morphological changes induced by beta-lactams, the contribution of the steps following antibiotic-receptor complex formation to the lag period might be significant for the less bactericidal antibiotics such as oxacillin and dicloxacillin. Findings from the present modeling approach can potentially be used to guide future bench experimentation.

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Kinetics and Mechanisms of Drug Action on Microorganisms XVII: Bactericidal Effects of Penicillin, Kanamycin, and Rifampin with and without Organism Pretreatment with Bacteriostatic Chloramphenicol, Tetracycline, and Novobiocin

Cited by 31 publications

References 21 publications

Exploring the collaboration between antibiotics and the immune response in the treatment of acute, self-limiting infections

Exploring the collaboration between antibiotics and the immune response in the treatment of acute, self-limiting infections

Issues in Pharmacokinetics and Pharmacodynamics of Anti-Infective Agents: Kill Curves versus MIC

Simultaneous pharmacodynamic analysis of the lag and bactericidal phases exhibited by beta-lactams against Escherichia coli

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