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：
George Louis Drusano
金额：
$ 72.99万
依托单位：
UNIVERSITY OF FLORIDA
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

来源：
https://reporter.nih.gov/project-details/9186485
关键词：
Back Bacteria Bacterial Pneumonia Biological Assay Chemotherapy-Oncologic Procedure Clinical Clinical Trials Combination Drug Therapy Combined Modality Therapy Data Disease Dose Dose Fractionation Drug Combinations Drug Interactions Evaluation Fiber Flow Cytometry Hospitals Hour Infection Investigation Link Literature Lung Mediating Methods Modeling Morbidity - disease rate Mus Nature Nosocomial pneumonia Organism Outcome Patient-Focused Outcomes Patients Pharmaceutical Preparations Pneumonia Process Pseudomonas aeruginosa Pseudomonas aeruginosa pneumonia Recovery Recruitment Activity Regimen Resistance Schedule Site Speed Testing Time Validation Ventilator Work antimicrobial cell killing experimental study granulocyte improved improved outcome in vivo insight killings mathematical model mortality mouse model novel pathogen public health relevance rapid technique resistance mechanism survivorship synergism virtual

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着死亡率和发病率的疾病过程，尤其是铜绿假单胞菌，在单一疗法中很常见，并且在接受治疗的患者中约为 33-50%。最近已经证明，粒细胞对于细菌细胞杀灭来说是饱和的，将细菌负荷快速降低到低于半饱和点会导致细菌细胞死亡。粒细胞介导的细菌杀灭的回归对于获得最大杀灭率和抑制耐药亚群扩增的能力是谨慎的。本提案的总体目标是开发一种新的方法。快速、可靠地确定最佳联合疗法的新方法，该联合疗法将提供最大程度的细胞杀伤快速杀死细胞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”。我们的目的是：1）开发一种新的快速方法来确定采用流量的最佳联合化疗方案。 2) 在 HFIM 中采用该方法进行的测试方案；我们将研究 3 个同基因菌株，以确定不同耐药机制对细胞杀伤和耐药性出现的影响；我们将采用最先进的数学模型来分析这些实验;然后，我们将在小鼠 PA 肺炎模型中验证这些发现。 3) 定量粒细胞和联合疗法对细胞杀伤和耐药抑制的相互作用。流式细胞术的使用与 Greco 数学模型相结合，将能够特别稳健地确定协同作用/相加性。 / 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验证流式测定确定的方案是最佳还是非最佳。治疗方案对粒细胞募集的影响将通过最先进的数学模型来确定，最佳治疗方案将改善结果，抑制阻力放大并加速恢复。确定最佳的抗菌药物组合方案将产生几个有益的结果：1] 耐药性的出现将受到抑制 2] 快速杀死细菌将使粒细胞不饱和，额外增加 1.0-1.5 个细菌。每天的细菌杀灭日志 3] 临床结果和（希望）拔管时间将会缩短，因为杀灭率有所提高，总体临床结果将会得到改善。