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Exploration of optimal dosing regimens of vancomycin in patients infected with methicillin-resistant Staphylococcus aureus by modeling and simulation

加药 耐甲氧西林金黄色葡萄球菌 万古霉素 金黄色葡萄球菌 微生物学 医学 抗生素 葡萄球菌感染 药理学 生物 细菌 遗传学
作者
Hyun‐Sook Lim,Yong Pil Chong,Yun Hee Noh,Jin Ah Jung,Y. S. Kim
出处
期刊:Journal of Clinical Pharmacy and Therapeutics [Wiley]
卷期号:39 (2): 196-203 被引量:23
标识
DOI:10.1111/jcpt.12123
摘要

What is known and objective Vancomycin is the drug of choice for methicillin-resistant Staphylococcus aureus (MRSA) infection and shows time-dependent bacterial killing. The current study evaluated the pharmacokinetics (PK) and pharmacodynamics (PD) of vancomycin and explored its optimal dosing regimens by modeling and simulation. Methods Pharmacokinetics study was performed for 20 patients who were treated with vancomycin intravenously, 1000 mg, every 12 h, and blood for PK was randomly drawn within prespecified time windows. PD study was in vitro time-kill experiment for vancomycin against 20 MRSA strains independent of the PK study, where bacterial titre was measured at 0, 2, 4, 8, 24 h after the beginning of vancomycin exposure at 0, 1, 2, 4, 8, 16, 32× minimum inhibitory concentrations. PK and PD models were built from each data set, and simulation for MRSA titre changes over time in human body was performed for various vancomycin dosing regimens using NONMEM®. Results Vancomycin followed a two-compartment PK model, and creatinine clearance was the significant covariate affecting the clearance of vancomycin. PD model described the in vitro time-kill data well. The PK/PD model predicted clear dose–response relationships of vancomycin. The therapeutic dosing regimens of vancomycin, suggested by the simulation studies, showed good agreement with the current clinical practice guidance, which indicates that this PK/PD modeling and simulation approach could prove useful for identifying optimal dosing regimens of other antibiotics and expediting novel antibiotic development. Using PD model from in vitro time-kill study and human PK model from phase 1 study, we could predict whether the drug is going to be efficacious or obtain insight into the optimal dosing regimens for a novel antibiotic agent in the early phases of drug development process.
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