title: Pharmacodynamic profiling of piperacillin in the presence of tazobactam in patients through the use of population pharmacokinetic models and Monte Carlo simulation.
abstract: 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 microg/ml. In the population pharmacokinetic analysis, measurements of bias and precision, observed-predicted plots, and r2 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 < or =8 mg/liter. The 4-h piperacillin administration interval had a superior pharmacodynamic profile and provided target attainment rates exceeding 95% for MICs of < or =16 mg/liter. This study indicates that piperacillin-tazobactam should have utility for empirical therapy of hospital-onset infections.
authors.affiliation: Albany College, Albany, New York, USA.
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Lodise
authors.forename: Ben
authors.initials: B
authors.lastname: Lomaestro
authors.forename: Keith A
authors.initials: KA
authors.lastname: Rodvold
authors.forename: Larry H
authors.initials: LH
authors.lastname: Danziger
authors.forename: George L
authors.initials: GL
authors.lastname: Drusano
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003428:Cross Infection / Q000188:drug therapy / Q000378:metabolism / Q000382:microbiology; D004347:Drug Interactions; D004791:Enzyme Inhibitors / Q000494:pharmacology*; D006207:Half-Life; D006801:Humans; D008954:Models, Biological; D009010:Monte Carlo Method; D010397:Penicillanic Acid / Q000031:analogs & derivatives* / Q000494:pharmacology*; D010406:Penicillins / Q000493:pharmacokinetics*; D010878:Piperacillin / Q000493:pharmacokinetics*; D011153:Population; D000078142:Tazobactam
chemical_list: D004791:Enzyme Inhibitors; D010406:Penicillins; D010397:Penicillanic Acid; D000078142:Tazobactam; D010878:Piperacillin