有哪些信誉好的足球投注网站a novel approach to pharmacodynamic assessment of antimicrobial agents new insights to dosing regimen design一种新型抗菌药物的药效学评价方法新见解给药方案设计.pdfVIP
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a novel approach to pharmacodynamic assessment of antimicrobial agents new insights to dosing regimen design一种新型抗菌药物的药效学评价方法新见解给药方案设计
A Novel Approach to Pharmacodynamic Assessment of Antimicrobial Agents: New Insights to Dosing Regimen Design Vincent H. Tam1,2*, Michael Nikolaou2 1 Department of Clinical Sciences and Administration, College of Pharmacy, University of Houston, Houston, Texas, United States of America, 2 Department of Chemical and Biomolecular Engineering, Cullen College of Engineering, University of Houston, Houston, Texas, United States of America Abstract Pharmacodynamic modeling has been increasingly used as a decision support tool to guide dosing regimen selection, both in the drug development and clinical settings. Killing by antimicrobial agents has been traditionally classified categorically as concentration-dependent (which would favor less fractionating regimens) or time-dependent (for which more frequent dosing is preferred). While intuitive and useful to explain empiric data, a more informative approach is necessary to provide a robust assessment of pharmacodynamic profiles in situations other than the extremes of the spectrum (e.g., agents which exhibit partial concentration-dependent killing). A quantitative approach to describe the interaction of an antimicrobial agent and a pathogen is proposed to fill this unmet need. A hypothetic antimicrobial agent with linear pharmacokinetics is used for illustrative purposes. A non-linear functional form (sigmoid Emax) of killing consisted of 3 parameters is used. Using different parameter values in conjunction with the relative growth rate of the pathogen and antimicrobial agent concentration ranges, various conventional pharmacodynamic surrogate indices (e.g., AUC/MIC, Cmax/MIC, %T.MIC) could be satisfactorily linked to outcomes. In addition, the dosing intensity represented by the average kill rate of a dosing regimen can be derived, which could be used for quantit
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