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Optimizing Combination Therapy to Accelerate Clinical Cure of Tuberculosis

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
负责人:
George Louis Drusano
金额:
$233.63万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-08-20 至 2021-07-31

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项目成果

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中文摘要
翻译
 描述(由申请人提供):结核分枝杆菌(MTB)感染是一个巨大的世界性问题。多重耐药和广泛耐药菌株(MDR和XDR MTB)的出现加剧了该问题,并导致死亡率增加和大量发病。除了贝达喹啉,这是批准了几年前,但与黑框警告,最后一个“新的”结核病代理是利福平。然而,最近一些新的代理商,一些具有独特的作用机制已进入开发管道。这将最终有助于MDR/XDR MTB的治疗。治疗MTB的大部分困难是治疗的持续时间。完全敏感菌株需要6个月的治疗,而MDR/XDR菌株需要18-24个月或更长时间的治疗。如此长的治疗持续时间加剧了依从性问题,这是耐药性的主要驱动因素。此外,特别是对于MDR/XDR MTB,治疗具有许多比一线药物毒性更大的二线药物。如果能够缩短治疗时间,将带来巨大的公共卫生红利。 虽然我们有新的药物进入治疗设备,但很少考虑如何使用它们来提高细胞杀伤力,抑制耐药性,从而缩短治疗时间。本计划的总体目标是确定满足缩短治疗要求的最佳方案:最快速的细胞杀伤、耐药性抑制和针对MTB存在的不同代谢状态(对数期生长、酸期生长和非复制持续表型期)的活性。 有三个项目和三个核心。该项目涉及在中空纤维感染模型(HALF)、鼠感染模型和食蟹猴非人灵长类动物模型(NHP)中评估MTB药物的组合。核心是管理核心、药物检测核心和数学建模核心。所有项目和核心将相互作用和交叉支持。 Hestival具有研究所有代谢状态的灵活性,并可用于研究人、鼠和NHP药物特征。我们实验室的一份出版物指出,动物药物谱改变了药物对所模拟病原体的活性。人们一直在猜测动物系统是否可以可靠地设计人体试验。我们将使用人类和动物的资料,使用HALGOR生成关于每种代谢状态下联合治疗杀灭率和耐药性抑制的数据。数学建模将允许直接识别不同特征对终点的影响。然后可以将这些障碍估计值与动物系统中的建模数据进行比较。具有不同配置文件的驱动效果参数将允许进一步深入了解可以可靠地提取哪些信息以允许最佳桥接, 人类感染 方案的顺序,后续方案针对第一方案后剩余的生物体状态,并且两个方案的耐药机制是独立的,可能是缩短治疗的最佳方式。这可以成为未来联合方案开发的一般范例。
英文摘要
 DESCRIPTION (provided by applicant): Infection with Mycobacterium tuberculosis (MTB) is a massive worldwide problem. The advent of Multiply Drug- Resistant and eXtensively Drug-Resistant strains (MDR and XDR MTB) has exacerbated the problem and has resulted in increased mortality and substantial morbidity. Other than bedaquiline, which was approved several years ago but with a black box warning, the last "new" MTB agent was rifampin. However, lately a number of new agents, some with unique mechanisms of action have entered the developmental pipeline. This will ultimately help with the therapy of MDR/XDR MTB. A large part of the difficulty in treating MTB is the duration of therapy. Fully susceptible strains requir 6 months of therapy while MDR/XDR strains require 18-24 months of therapy or longer. Such long therapeutic durations exacerbate problems with adherence, which is a major driver of resistance. Further, particularly with MDR/XDR MTB, therapy has many second line agents which are more toxic than first line drugs. It would pay massive public health dividends to be able to shorten therapy. While we have new agents entering the therapeutic armamentarium, little thought has been given to how to use them to improve cell kill, suppress resistance and, hence, have the possibility of shortening therapy. It is the overall goal of this Program to identify optimal regimens that fulfill the requirements of shortening therapy: most rapid cell kill, resistance suppression and activity against different metabolic states in which MTB exists (log-phase growth, acid-phase growth and Non-Replicative Persistent Phenotype-phase). There are three Projects and three Cores. The Projects involve evaluating combinations of MTB drugs in the Hollow Fiber Infection Model (HFIM), in murine models of infection and in the Cynomolgus macaque Non- Human Primate model (NHP). The Cores are the Administrative Core, Drug Assay Core and Mathematical Modeling Core. All Projects and Cores will interact and cross support. The HFIM has the flexibility to study all the metabolic states and to do so with human, murine and NHP drug profiles. A publication from our lab noted that animal drug profiles alter the activity of drugs on the pathogens being modeled. There has been speculation regarding the utility of animal system for reliability to design human trials. We will use the HFIM to generate data on combination therapy kill rates and resistance suppression in each metabolic state, using human and animal profiles. The mathematical modeling will allow direct identification of the impact of the different profiles on endpoints. These HFIM estimates can then be compared to the modeled data in the animal systems. Driving effect parameters with different profiles will allow further insight into what information can be reliably extracted to allow the best bridging to human infection. Sequencing of regimens, with the follow-on regimen being targeted at the organism states remaining after the first regimen and with resistance mechanisms of the two regimens being independent may be the best way to shorten therapy. This can be a general paradigm for future combination regimen development.
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Optimizing Multi-drug Mycobacterium tuberculosis Therapy for Rapid Sterilization and Resistance Suppression
  • 批准号:
    10567327
  • 项目类别:
  • 资助金额:
    $131.43万
  • 财政年份:
    2023
  • 负责人:
    George Louis Drusano
  • 依托单位:
Optimizing Combination Therapy to Accelerate Clinical Cure of Tuberculosis
  • 批准号:
    9529494
  • 项目类别:
  • 资助金额:
    $233.3万
  • 财政年份:
    2016
  • 负责人:
    George Louis Drusano
  • 依托单位:
Optimizing Combination Therapy to Accelerate Clinical Cure of Tuberculosis
  • 批准号:
    9750603
  • 项目类别:
  • 资助金额:
    $271.05万
  • 财政年份:
    2016
  • 负责人:
    George Louis Drusano
  • 依托单位:
Rapid Identification of Optimal Combination Regimens for Pseudomonas aeruginosa
  • 批准号:
    9186485
  • 项目类别:
  • 资助金额:
    $72.99万
  • 财政年份:
    2015
  • 负责人:
    George Louis Drusano
  • 依托单位:
海外基金