Rapid Identification of Optimal Combination Regimens for Pseudomonas aeruginosa

快速鉴定铜绿假单胞菌的最佳组合方案

基本信息

  • 批准号:
    9186485
  • 负责人:
  • 金额:
    $ 72.99万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-12-01 至 2020-11-30
  • 项目状态:
    已结题

项目摘要

 DESCRIPTION (provided by applicant): Ventilator-Requiring Hospital Acquired Bacterial pneumonia is a disease process with substantial mortality and morbidity. Resistance emergence, particularly with P. aeruginosa is common with monotherapy and is on the order of 33-50% in patients treated with monotherapy. It has been recently demonstrated that granulocytes are saturable for bacterial cell kill. Rapid lowering of the bacterial burden to less than the half-saturation point results in a return of granulocyte-mediated bacterial kill. Combination therapy is prudent for both the ability to obtain maximal kill rate and to suppress amplification of resistant subpopulations. Identifying optimal combination regimens is difficult and time consuming. It is the overarching aim of this proposal to develop a new method to rapidly and robustly identify optimal combination therapy that will provide maximal cell kill along with resistance suppression. The rapid cell kill will help reduce the bacterial burden below the half saturation point and bring the granulocytes "back on line". it is our intent to: 1) Develop a new rapid method to identify optimal combination chemotherapy regimens employing flow cytometry 2) Test regimens resulting from this method in the HFIM; we will look at 3 isogenic strains to ascertain the impact of different resistance mechanisms on cell kill and resistance emergence; we will employ state-of-the art mathematical models to analyze these experiments; we will then validate these findings in the murine PA pneumonia models 3) Quantitate the interaction of granulocytes and combination therapy on cell kill and resistance suppression. The use of flow cytometry, linked with the Greco mathematical model will allow statistically robust determination of synergy/ additivity/ antagonism. Exploration of these combinations in our Hollow Fiber Infection Model and murine P. aeruginosa pneumonia models will provide the validation that the regimens identified by the flow assay as optimal or non-optimal behave in the fashion predicted. The impact of regimen on granulocyte recruitment will be ascertained. All these experiments will be linked by state-of-the-art mathematical models. Optimal regimens will improve outcomes, suppress resistance amplification and speed recovery because of granulyte function return. Defining optimal antimicrobial combination regimens will generate several salutary outcomes: 1] resistance emergence will be suppressed 2] rapid bacterial kill will unsaturate granulocytes, adding 1.0-1.5 extra Logs of bacterial kill per day 3] clinical outcomes and (hopefully) time to extubation will be shortened because of the improved rate of kill. Taken together overall clinical outcomes will be improved.
 描述(由申请人提供):需要呼吸机的医院获得性细菌性肺炎是一种具有显著死亡率和发病率的疾病过程。耐药的出现,特别是铜绿假单胞菌,在单药治疗中很常见,在单药治疗的患者中约为33-50%。最近已经证明,粒细胞对于细菌细胞杀伤是可饱和的。细菌负荷快速降低至低于半饱和点导致粒细胞介导的细菌杀灭恢复。联合治疗对于获得最大杀灭率和抑制耐药亚群扩增的能力都是谨慎的。确定最佳组合方案是困难和耗时的。该提案的首要目标是开发一种新方法来快速、稳健地确定最佳组合疗法,从而沿着提供最大的细胞杀伤 有阻力抑制。快速细胞杀灭将有助于将细菌负荷降低到半饱和点以下,并使粒细胞“恢复正常”。我们打算:1)开发一种新的快速方法,采用流式细胞术鉴定最佳的联合化疗方案2)在HPLC 1中测试由该方法产生的方案;我们将观察3种同基因菌株,以确定不同的耐药机制对细胞杀伤和耐药出现的影响;我们将采用最先进的数学模型来分析这些实验;然后,我们将在鼠PA肺炎模型中验证这些发现。3)定量粒细胞和联合治疗对细胞杀伤和抗性抑制的相互作用。使用流式细胞术,与Greco数学模型相结合,将允许统计学上稳健地确定协同作用/加和性/拮抗作用。在我们的中空纤维感染模型和鼠铜绿假单胞菌肺炎模型中探索这些组合将提供验证,即通过流动测定法鉴定为最佳或非最佳的方案以预测的方式表现。将确定方案对粒细胞募集的影响。所有这些实验都将通过最先进的数学模型联系起来。最佳方案将改善预后,抑制耐药扩增,并因粒细胞功能恢复而加速恢复。确定最佳的抗菌剂组合方案将产生几个有益的结果:1)耐药性的出现将被抑制2)快速的细菌杀灭将使粒细胞减少,每天增加1.0-1.5倍的额外细菌杀灭3)由于杀灭率的提高,临床结果和(希望)拔管时间将缩短。总的来说,总体临床结果将得到改善。

项目成果

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George Louis Drusano其他文献

George Louis Drusano的其他文献

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{{ truncateString('George Louis Drusano', 18)}}的其他基金

Optimizing Multi-drug Mycobacterium tuberculosis Therapy for Rapid Sterilization and Resistance Suppression
优化结核分枝杆菌多药治疗以实现快速灭菌和耐药性抑制
  • 批准号:
    10567327
  • 财政年份:
    2023
  • 资助金额:
    $ 72.99万
  • 项目类别:
Optimizing Combination Therapy to Accelerate Clinical Cure of Tuberculosis
优化联合治疗加速结核病临床治愈
  • 批准号:
    9529494
  • 财政年份:
    2016
  • 资助金额:
    $ 72.99万
  • 项目类别:
Optimizing Combination Therapy to Accelerate Clinical Cure of Tuberculosis
优化联合治疗加速结核病临床治愈
  • 批准号:
    9750603
  • 财政年份:
    2016
  • 资助金额:
    $ 72.99万
  • 项目类别:
Optimizing Combination Therapy to Accelerate Clinical Cure of Tuberculosis
优化联合治疗加速结核病临床治愈
  • 批准号:
    9069215
  • 财政年份:
    2016
  • 资助金额:
    $ 72.99万
  • 项目类别:
Rapid Identification of Optimal Combination Regimens for Pseudomonas aeruginosa
快速鉴定铜绿假单胞菌的最佳组合方案
  • 批准号:
    9009651
  • 财政年份:
    2015
  • 资助金额:
    $ 72.99万
  • 项目类别:
Combination Therapy Modeling for M tuberculosis Resistance Suppression and Kill
结核分枝杆菌耐药性抑制和杀灭的联合治疗建模
  • 批准号:
    8878433
  • 财政年份:
    2014
  • 资助金额:
    $ 72.99万
  • 项目类别:
2010 New Antimicrobial Drug Discovery and Development Gordon Research Conference
2010新型抗菌药物发现与开发戈登研究会议
  • 批准号:
    7906349
  • 财政年份:
    2010
  • 资助金额:
    $ 72.99万
  • 项目类别:
Optimization of Neoglycoside Antibiotics for Nosocomial Pathogens and Select Agen
新糖苷类抗生素治疗院内病原体的优化及药物选择
  • 批准号:
    8465173
  • 财政年份:
    2010
  • 资助金额:
    $ 72.99万
  • 项目类别:
Optimization of Neoglycoside Antibiotics for Nosocomial Pathogens and Select Agen
新糖苷类抗生素治疗院内病原体的优化及药物选择
  • 批准号:
    7989055
  • 财政年份:
    2010
  • 资助金额:
    $ 72.99万
  • 项目类别:
Optimization of Neoglycoside Antibiotics for Nosocomial Pathogens and Select Agen
新糖苷类抗生素治疗院内病原体的优化及药物选择
  • 批准号:
    8075079
  • 财政年份:
    2010
  • 资助金额:
    $ 72.99万
  • 项目类别:

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Segmented Filamentous Bacteria激活宿主免疫系统抑制其拮抗菌 Enterobacteriaceae维持菌群平衡及其机制研究
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