Pharmacodynamic profiling of continuously infused piperacillin/tazobactam against Pseudomonas aeruginosa using Monte Carlo analysis

Kuti, Joseph L.; Nightingale, Charles H.; Quintiliani, Richard; Nicolau, David P.

doi:10.1016/s0732-8893(02)00416-9

Cited by 41 publications

(33 citation statements)

References 25 publications

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“…Monte Carlo simulation has been integrated with accepted pharmacodynamic models to compare antimicrobials and determine their abilities to achieve critical dynamic endpoints (1,12,13,15,(20)(21)(22)32). It is a mathematical technique in which parameter values are randomly drawn from a multivariate distribution.…”

Section: Discussionmentioning

confidence: 99%

“…Frequently, Monte Carlo simulations rely on PK data from healthy subjects because of the dearth of data on the population of interest (1,(20)(21)(22). Even the NCCLS frequently relies on healthy-subject data to assess the viability of MIC breakpoints.…”

Section: Discussionmentioning

confidence: 99%

“…Even the NCCLS frequently relies on healthy-subject data to assess the viability of MIC breakpoints. When possible, PK data should be derived from the population of interest (1,12,22,30,32,33). In summary, 3.375 g of piperacillin-tazobactam given intravenously every 6 h performed well, achieving excellent target attainment rates for MICs of Յ8 (piperacillin) and 4 (tazobactam) mg/liter.…”

Section: Discussionmentioning

confidence: 99%

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Pharmacodynamic Profiling of Piperacillin in the Presence of Tazobactam in Patients through the Use of Population Pharmacokinetic Models and Monte Carlo Simulation

Lodise

Lomaestro

Rodvold

et al. 2004

Antimicrob Agents Chemother

112

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The primary objectives of this analysis were to determine which pharmacokinetic model most accurately describes the elimination pathways for piperacillin in the presence of tazobactam through population pharmacokinetic modeling and to characterize its pharmacodynamic profile. Once the optimal pharmacokinetic model was identified, Monte Carlo simulation of 10,000 subjects with ADAPT II was performed to estimate the probability of attaining a target free-piperacillin concentration greater than the MIC for 50% of the dosing interval for 3.375 g every 6 h or every 4 h given as a 0.5-h infusion at each MIC between 0.25 and 32 g/ml.In the population pharmacokinetic analysis, measurements of bias and precision, observed-predicted plots, and r 2 values were highly acceptable for all three models and all three models were appropriate candidates for the Monte Carlo simulation evaluation. Visual comparison of the distribution of the piperacillin concentrations at the pharmacodynamic endpoint-h 3 concentrations of a 6-h dosing interval-between the simulated populations and raw data revealed that the linear model was most reflective of the raw data at the pharmacodynamic endpoint, and the linear model was therefore selected for the target attainment analysis. In the target attainment analysis, administration of 3 g of piperacillin every 6 h resulted in a robust target attainment rate that exceeded 95% for MICs of <8 mg/liter. The 4-h piperacillin administration interval had a superior pharmacodynamic profile and provided target attainment rates exceeding 95% for MICs of <16 mg/liter. This study indicates that piperacillin-tazobactam should have utility for empirical therapy of hospital-onset infections.Antimicrobial pharmacodynamics is a term used to describe the relationship between drug exposure and antimicrobial activity. In recent years there have been tremendous strides in understanding the relationship between the pharmacodynamics of beta-lactams and treatment outcomes. Beta-lactams, in contrast to aminoglycosides and fluoroquinolones, exhibit little concentration-dependent bacterial killing (7-9, 14, 24, 25, 29, 30). This phenomenon was observed in early Staphylococcus aureus time-kill curve studies, which demonstrated that the rate of bacterial killing was not improved by increasing the concentration of penicillin (19). For beta-lactams, the time during which the free (unbound) serum drug concentration exceeds the MIC of the drug for the organism (T Ͼ MIC) appears to be the best predictor of outcomes (7-9, 24, 25). The serum free-beta-lactam concentration does not have to remain above the MIC for the entire dosing interval, and the fraction of the dosing interval during which it is required to remain above the MIC for the maximal antimicrobial effect varies for the different types of beta-lactams (7-9). Although the T Ͼ MIC varies for different drug-bacteria combinations, satisfactory outcomes (near-maximal bactericidal effect) are achieved when the free (unbound)-antibiotic concentration remains above the MIC for t...

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Pharmacodynamic Profiling of Piperacillin in the Presence of Tazobactam in Patients through the Use of Population Pharmacokinetic Models and Monte Carlo Simulation

Lodise

Lomaestro

Rodvold

et al. 2004

Antimicrob Agents Chemother

112

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“…Ideally, the use of hospital-or unit-specific MIC distributions in these Monte Carlo simulations would provide the most reliable data for designing empirical dosing regimens. This approach has been done at some centers to justify the use of novel dosing regimens, such as continuous infusion (20). Additionally, we chose to employ a one-compartment i.v.…”

Section: Discussionmentioning

confidence: 99%

Optimizing Pharmacodynamic Target Attainment Using the MYSTIC Antibiogram: Data Collected in North America in 2002

Kuti

Nightingale

Nicolau

2004

Antimicrob Agents Chemother

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The OPTAMA Program is intended to examine typical antimicrobial regimens used in the treatment of common nosocomial pathogens and the likelihood of these regimens attaining appropriate pharmacodynamic exposure in different parts of the world. A 5,000-subject Monte Carlo simulation was used to estimate pharmacodynamic target attainment for meropenem, imipenem, ceftazidime, cefepime, piperacillin-tazobactam, and ciprofloxacin against Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa. Standard dosing regimens from North America were used. Pharmacokinetic parameter variability was derived from existing healthy volunteer data, and MIC data came from the 2002 MYSTIC Program. Ciprofloxacin displayed the lowest target attainment against all bacterial species (41 to 46% for A. baumannii, 53 to 59% for P. aeruginosa, and 80 to 85% for the Enterobacteriaceae). Increasing the dose to 400 mg every 8 h did not significantly increase target attainment against nonfermenters. Piperacillin-tazobactam target attainments were similar to that of ceftazidime against all pathogens. Higher doses of both compounds were needed to achieve better target attainments against P. aeruginosa. Overall, meropenem, imipenem, and cefepime attained the highest probabilities of attainment against the Enterobacteriaceae (99 to 100%). The carbapenems appear to be the most useful agents against A. baumannii (88 to 92%), and these agents, along with higher doses of any of the ␤-lactams, would be the most appropriate choices for empirical therapy for P. aeruginosa infection. Given the lack of agreement between percent susceptibility and probability of target attainment for certain antimicrobial regimens, a methodology employing stochastic pharmacodynamic analyses may be a more useful tool for differentiating the most-optimal compounds and dosing regimens in the clinical setting of initial empirical therapy.

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“…A MCS approach has seldom been used for antimicrobial agents showing time-dependent (T ϾMIC ) activity (2,17), mainly because the calculations needed are less straightforward than for AUC-dependent drugs. The objectives of the present study were to propose a dosage regimen for future therapeutic studies with BAL9141, to show that MCS can be used to determine T ϾMIC activity, and to illustrate the limitations of this approach for ␤-lactams.…”

mentioning

confidence: 99%

Use of Monte Carlo Simulations To Select Therapeutic Doses and Provisional Breakpoints of BAL9141

Mouton

Schmitt‐Hoffmann

Shapiro

et al. 2004

Antimicrob Agents Chemother

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Pharmacodynamic profiling of continuously infused piperacillin/tazobactam against Pseudomonas aeruginosa using Monte Carlo analysis

Cited by 41 publications

References 25 publications

Pharmacodynamic Profiling of Piperacillin in the Presence of Tazobactam in Patients through the Use of Population Pharmacokinetic Models and Monte Carlo Simulation

Pharmacodynamic Profiling of Piperacillin in the Presence of Tazobactam in Patients through the Use of Population Pharmacokinetic Models and Monte Carlo Simulation

Optimizing Pharmacodynamic Target Attainment Using the MYSTIC Antibiogram: Data Collected in North America in 2002

Use of Monte Carlo Simulations To Select Therapeutic Doses and Provisional Breakpoints of BAL9141

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