Optimizing Combination Therapy to Accelerate Clinical Cure of Tuberculosis

 描述(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)的出现加剧了这一问题，并导致死亡率增加和发病率大幅上升。除了几年前获得批准但带有黑匣子警告的贝达奎兰外，最后一种“新”的结核分枝杆菌制剂是利福平。然而，最近一些新的药物，其中一些具有独特的作用机制，已经进入开发流水线。这最终将有助于MDR/XDR结核分枝杆菌的治疗。治疗结核分枝杆菌的很大一部分困难是治疗的持续时间。完全敏感的菌株需要6个月的治疗，而MDR/XDR菌株需要18-24个月或更长的治疗。如此长的治疗持续时间加剧了坚持治疗的问题，这是耐药性的主要驱动因素。此外，特别是对于MDR/XDR MTB，治疗有许多二线药物，它们比一线药物毒性更大。能够缩短治疗时间将带来巨大的公共健康红利。 虽然我们有新的药物进入治疗武器库，但很少有人考虑如何使用它们来提高细胞杀伤力，抑制耐药性，从而有可能缩短治疗时间。本计划的总体目标是确定满足缩短治疗要求的最佳方案：对结核分枝杆菌存在的不同代谢状态(对数生长阶段、酸性生长阶段和非复制持续表型阶段)进行最快的细胞杀伤、耐药性抑制和活性。 有三个项目和三个核心。这些项目包括在中空纤维感染模型(HFIM)、小鼠感染模型和食蟹猴非人类灵长类模型(NHP)中评估结核分枝杆菌药物的组合。核心是管理核心、药物分析核心和数学建模核心。所有项目和核心都将相互作用并相互支持。 HFIM可以灵活地研究所有的代谢状态，并可以用人类、小鼠和NHP的药物图谱进行研究。我们实验室的一份出版物指出，动物药物概况会改变药物对正在建模的病原体的活性。人们一直在猜测动物系统在设计人体试验时是否具有可靠性。我们将使用HFIM来生成关于每种代谢状态下的联合疗法杀伤率和耐药性抑制的数据，使用人类和动物的概况。数学建模将允许直接识别不同配置文件对端点的影响。然后，可以将这些HFIM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驾驶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实现最佳桥接 人类感染。 对方案进行排序，将后续方案针对第一方案后剩余的机体状态，并使两种方案的耐药机制独立，可能是缩短治疗时间的最佳方法。这可能是未来联合疗法发展的一个通用范例。

 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.