Lesion-centric optimization of multidrug therapies for tuberculosis

修改后的项目摘要/摘要部分 结核病(TB)需要同时使用多种抗生素来根除异质细菌种群。对于药物敏感的结核病，疗程从6个月到24个月不等，对于广泛耐药的结核病，疗程更长。随着最近一些药物的批准和有希望的临床开发候选药物，有希望缩短急需的治疗。然而，我们需要高通量的方法来对非常大量的可能药物组合进行排序，并将它们减少到一个可行的数字，以便在临床试验中进行测试。目前，药物方案的优先顺序是基于小鼠模型的疗效，尽管它易于使用，但只适用于所有可能的组合中的一小部分。此外，在人类肺部病变中发现的不同的药物敏感细菌亚群在小鼠肺中不能很好地概括。结核病的一个特点是形成病变，同时结核分枝杆菌在药物治疗期间能够在各种病变类型中持续存在。这些难以治疗的细菌亚群会导致疾病复发。因此，确定新方案的优先顺序的关键是系统、高质量的多药方案效力的体外测量，以及将体外测量与不同类型的类人皮损的疗效联系起来的框架。要做到这一点，我们需要开发体外模型，捕捉关键的病变特异性应激源，并利用联合治疗的潜力来确定协同作用的药物。我们建议通过开发一种数据驱动的管道来弥合这一差距，通过将药物作用的体外和体内测量与数学建模相结合来快速确定药物方案的优先顺序。(1)我们将利用各种生长条件下的药物组合的有效测量来直接比较联合药物在皮损中的效果。(2)我们将利用非人类灵长类动物类似人类的病理学特性来质疑不同病变分区的药物疗效。(3)我们将应用多尺度(分子、细胞、肉芽肿和器官尺度)数学建模的力量来识别最能预测体内疗效的应激源。为了建立管道，我们将利用一种新的药物方案，该方案在临床试验中表现得出人意料地好，但其成分在体外标准效力分析中具有拮抗作用：NIX-TB方案，包括贝达奎兰-前托马尼德-利奈唑胺。一旦NIX-TB相对于标准护理得到验证，该管道将被用于使用数据驱动的计算模拟合理地优化和重新发明NIX方案。

Modified Project Summary/Abstract Section Tuberculosis (TB) requires the simultaneous administration of multiple antibiotics to eradicate heterogeneous bacterial populations. Treatment duration ranges from 6 months for drug susceptible TB to 24 months and longer for extensively resistant TB. With a number of recent drug approvals and promising clinical development candidates, there is hope for much needed treatment shortening. However, we need high-throughput methods to rank the very large number of possible drug combinations and reduce them to a feasible number for testing in clinical trials. Currently, drug regimens are prioritized based on efficacy in the mouse model, which despite its ease of use, is available for only a small subset of all possible combinations. In addition, differentially drug-susceptible bacterial subpopulations that are found in human pulmonary lesions are not well recapitulated in murine lungs. A hallmark of TB is the formation of lesions and the coincident remarkable ability of Mycobacterium tuberculosis to persist in a variety of lesion types during drug treatment. These hard-to-treat bacterial subpopulations cause disease relapse. Therefore, key to prioritizing new regimens is systematic, high-quality in vitro measurement of multidrug regimen potencies and a framework that links in vitro measurements to efficacy in different types of human-like lesions. To do so requires that we develop in vitro models that capture key lesion-specific stressors and harness the potential of combination therapies to identify drugs that act synergistically. We propose to bridge this gap by developing a data-driven pipeline to rapidly prioritize drug regimens by combining in vitro and in vivo measurements of drug action with mathematical modeling. (1) We will utilize efficient measurement of drug combinations in a variety of growth conditions for direct comparison of combination drug effects in lesions. (2) We will leverage the human-like properties of pathology in non-human primates to query drug efficacy in distinct lesion compartments. (3) We will apply the power of multiscale (molecular, cellular, granuloma and organ scales) mathematical modeling to identify the stressors that are most predictive of in vivo efficacy. To build the pipeline, we will leverage a new drug regimen that has performed surprisingly well in clinical trials but the components of which antagonize in standard potency assays in vitro: the NiX-TB regimen comprising bedaquiline-pretomanid-linezolid. Once validated for NiX-TB versus standard of care, the pipeline will be used to rationally optimize and re-invent the NiX regimen using data-driven computational simulation.