Antibiotic pharmacokinetic/pharmacodynamic modelling: MIC pharmacodynamic indices and beyond

被引:22
作者
Rao, Gauri G. [1 ]
Landersdorfer, Cornelia B. [2 ]
机构
[1] Univ N Carolina, UNC Eshelman Sch Pharm, Chapel Hill, NC 27599 USA
[2] Monash Univ, Monash Inst Pharmaceut Sci, Ctr Med Use & Safety, Parkville, Vic 3053, Australia
基金
英国医学研究理事会;
关键词
MIC; AUC; PD; PK; Modelling; Bacteria; POLYMYXIN-B; DRUG EXPOSURE; COMBINATION; DORIPENEM; SELECTION;
D O I
10.1016/j.ijantimicag.2021.106368
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
The dramatic increase in antimicrobial resistance and the limited pharmacological treatment options highlight the urgent need to optimize therapeutic regimens of new and available anti-infectives. Several in-vitro and in-vivo infection models are employed to understand the relationship between drug exposure profiles in plasma or at the site of infection (pharmacokinetics) and the time course of therapeutic response (pharmacodynamics) to select and optimize dosage regimens for new and approved drugs. Well-designed preclinical studies, combined with mathematical-model-based pharmacokinetic/pharmacodynamic analysis and in-silico simulations, are critical for the effective translation of preclinical data and design of appropriate and successful clinical trials. Integration with population pharmacokinetic modelling and simulations allows for the incorporation of interindividual variability that occurs in both pharmacokinetics and pharmacodynamics, and helps to predict the probability of target attainment and treatment outcome in patients. This article reviews the role of pharmacokinetic/pharmacodynamic approaches in the optimization of dosage regimens to maximize antibacterial efficacy while minimizing toxicity and emergence of resistance, and to achieve a high likelihood of therapeutic success. Polymyxin B, an approved drug with a narrow therapeutic window, serves as an illustrative example to highlight the importance of pharmacokinetic/pharmacodynamic modelling in conjunction with experimentation, employing static time-kill studies followed by dynamic in-vitro or in-vivo models, or both, to learn and confirm mechanistic insights necessary for translation to the bedside. (c) 2021 Elsevier Ltd and International Society of Antimicrobial Chemotherapy. All rights reserved.
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页数:5
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