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Pharmacodynamic modeling of antibiotics on cystic fibrosis P. aeruginosa biofilms

Pharmacodynamic modeling of antibiotics on cystic fibrosis P. aeruginosa biofilms
抗生素对囊性纤维化铜绿假单胞菌生物膜的药效学模型
批准号:
8471052
负责人:
Katherine Y. Yang
金额:
$36.58万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-05-22 至 2017-04-30

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项目成果

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中文摘要
翻译
描述(申请人提供):关于抗生素和生物膜的药代动力学(PK)和药效学(PD)知之甚少,但细菌生物膜占所有重要人类感染的80%以上,包括囊性纤维化(CF)。开发有效的治疗方法来对抗生物被膜感染被NIH称为抗菌药物开发中最紧迫的挑战之一。随着时间的推移,铜绿假单胞菌在CF肺中经历了广泛的遗传适应,使其能够持续存在,尽管进行了密集、重复的抗菌治疗。因此,目前抗菌治疗的目标是抑制感染,而不是治愈。铜绿假单胞菌呼吸道感染的治疗指南是基于对浮游(例如液体)培养中生长的细菌的PD分析,这些细菌不能推断为生物膜。此外,已知不同类别的抗生素针对生物膜中不同的亚群。这项研究的长期目标是确定通过在细菌生物膜上应用PD来根除CF患者铜绿假单胞菌生物膜所需的抗生素组合、剂量和时间表。传统的PK/PD研究根据“活的”或“死的”的简单计数来量化抗菌效果。这项研究中提出的独特的PD建模的时空方法将允许实时可视化和量化抗生素对生物膜内不同亚群的暴露反应关系以及对耐药性演变的相关影响。目标1的目的是优化设计一种创新的动态体外生物膜PK/PD模型,该模型可以模拟连续培养条件下铜绿假单胞菌生物膜上的体内抗生素浓度-时间分布。在目标2中,该模型将被用来确定美罗培南和妥布霉素的生物膜PD靶点,单独和联合使用,在一组独特的遗传相同的铜绿假单胞菌分离株上,纵向收集自CF患者,历时35年,从而允许比较导致早期与晚期疾病以及急性与慢性感染的菌株之间的PD靶点。在目标3中,将建立描述抗生素活性和生物被膜杀灭之间关系的数学模型。我们已经组建了一支国际化的多学科研究团队,在PK/PD、微生物生物膜、CF和数学建模方面具有专业知识。这项研究的结果将被用于研究新的抗生素方案,以最大限度地杀灭生物膜。这项翻译研究将为抗菌素PD的研究提供一个创新的新框架,解释在铜绿假单胞菌生物膜中观察到的遗传适应和表型多样性,并将能够发现针对CF中铜绿假单胞菌生物膜的替代抗菌剂剂量策略和药物组合,最终目标是改善临床护理。这项研究的结果将广泛应用于其他生物被膜形成生物(例如金黄色葡萄球菌),这些生物是人类感染的重要原因,如心内膜炎、骨科-植入物感染和导管相关感染。
英文摘要
DESCRIPTION (provided by applicant): Little is known regarding the pharmacokinetics (PK) and pharmacodynamics (PD) of antibiotics and biofilms yet bacterial biofilms account for over 80% of all important human infections, including cystic fibrosis (CF). The development of effective therapies to counter biofilm infections has been called one of the most pressing challenges in anti-bacterial drug development by the NIH. P. aeruginosa undergoes extensive genetic adaptation in the CF lung over time, allowing it to persist despite intense, repeated courses of antimicrobial treatment. Thus the current goal of antimicrobial therapy is to suppress infection and not cure. Guidelines for the treatment of P. aeruginosa airway infection are based upon PD analyses of bacteria grown in planktonic (e.g. liquid) culture which cannot be extrapolated to biofilms. Additionally, different classes of antibiotics are known to target differnt subpopulations within the biofilm. The long-term goal of this study is to identify the antibiotic combinations, doses, and schedules needed to eradicate P. aeruginosa biofilms in patients with CF through the application of PD on bacterial biofilms. Traditional PK/PD studies quantify antimicrobial effect based upon simple counts of "live" or "dead." The unique spatial and temporal approach to PD modeling proposed in this study will allow simultaneous visualization and quantification of the exposure response relationship of antibiotics on heterogeneous subpopulations within the biofilm in real-time and the associated effect on resistance evolution. The goal of Aim 1 is to optimize the design of an innovative dynamic in vitro biofilm PK/PD model that can simulate in vivo antibiotic concentration-time profiles on P. aeruginosa biofilms under continuous culture conditions. In Aim 2, this model will be used to determine the biofilm PD targets of meropenem and tobramycin, administered alone and in combination, on a unique collection of genetically identical P. aeruginosa isolates longitudinally-collected from CF patient over a period of 35 years thus allowing for comparisons in PD targets between isolates causing early vs. late disease and acute vs. chronic infection. In Aim 3, mathematical models describing the relationship between antibiotic activity and biofilm killing will be developed. We have assembled an international, multi-disciplinary research team with expertise in PK/PD, microbial biofilms, CF, and mathematical modeling. Results from this study will be used to investigate new antibiotic regimens for maximal bio- film killing. This translational study will provide an innovatve new framework for the investigation of antimicrobial PD that accounts for the genetic adaptations and phenotypic diversity observed in P. aeruginosa biofilms and will enable the discovery of alternative antimicrobial dosing strategies and drug combinations specifically targeting P. aeruginosa biofilms in CF with the ultimate goal of improving clinical care. Results of this study will have broad applications toward other biofilm-forming organisms (e.g., Staphyloccocus aureus) which are important causes of human infections such as endocarditis, orthopedic-implant infections, and catheter-related infections.
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Pharmacodynamic modeling of antibiotics on cystic fibrosis P. aeruginosa biofilms
Pharmacodynamic modeling of antibiotics on cystic fibrosis P. aeruginosa biofilms
Pharmacodynamic modeling of antibiotics on cystic fibrosis P. aeruginosa biofilms
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