Enabling comprehensive diagnosis of sub-acute infection in chronic respiratory disease via high sensitivity next generation sequencing

摘要 亚急性肺部感染越来越多地被认为是导致症状控制不佳的原因 慢性肺病患者，据估计，美国有200多万人患有哮喘和慢性阻塞性肺病 病人。当这些亚急性感染得到适当的诊断和治疗时，慢性肺部疾病 患者可以从中度/重度转化为较轻的疾病表型，需要较低的药物治疗才能实现 以显著较低的成本改善健康状况。目前亚急性感染的金标准诊断依赖于 几十年前的技术，可能需要几周时间才能完成，灵敏度有限，类型和 可通过一次测试筛选的微生物数量。因此，由于不能提供电流，因此存在临界间隙 全面准确地检测低负担临床标本中的微生物病原体的诊断学， 是改善慢性肺部疾病临床结果的一个重要障碍。因此，我们开发了一种 全面的下一代测序(NGS)面板，用于检测和鉴定微生物。我们的阶段 研究表明，我们的诊断工具应用于亚临床呼吸系统是可行的。 感染及其诊断方法相对于微生物学和分子方法的优越性。我们的NGS 诊断(Dx)面板是当前方法的重大技术创新；Dx面板利用 直接来自患者的样本(而不是依赖于培养)提供了比qPCR或 元基因组测序方法和筛选数以万计的其他微生物的存在 单项检测。这些功能是可能的，因为我们的Dx面板设计，以及专有实验室和 分析工作流。该项目的长期目标是为检测低密度脂蛋白提供新的临床工具。 慢性肺部疾病中引起疾病病理、症状和恶化的微生物感染负担 人口。在此阶段II中，我们将开发数据集成系统以1)将我们的诊断测试部署到 医疗保健组织推动医生采用，2)构建数据并应用扩展所需的算法 我们化验的影响和基于价值的报销。我们的目标是1)开发基于云的商业 用于大规模数据接收、存储、分析和临床报告的软件系统，2)集成我们的软件 系统集成到我们的临床合作伙伴的临床工作流程中，以及3)开发用于测试的基于Web的可视化门户 并为使用先进的统计学习算法建立基础设施。这一集成系统将 推动个性化诊疗手段的发展和应用 指南目前在慢性肺部疾病中缺失。这种诊断的总市场是一套慢性肺病 症状不受控制的疾病患者，可以进行亚急性感染筛查。我们的竞争力 优势包括改进的灵敏度、全面的微生物检测、简化的分析和治疗 一次化验中的有效性洞察。

ABSTRACT Sub-acute lung infections are increasingly recognized as drivers of poor symptom control among a subset of individuals with chronic lung disease, estimated to be more than 2 million in the US for Asthma and COPD patients. When these sub-acute infections are diagnosed and treated appropriately, chronic lung disease patients can convert from moderate/severe to a milder disease phenotype, requiring lower medication to achieve better health at a significantly lower cost. Current gold-standard diagnostics for sub-acute infection rely on decades-old technology that can take weeks to complete, have limited sensitivity, and are limited in the type and number of microbes that can be screened by a single test. Thus, a critical gap exists due to the inability of current diagnostics to comprehensively and accurately detect microbial pathogens in low-burden clinical samples, which is a significant barrier to improved clinical outcomes in chronic lung disease. We have thus developed a comprehensive next generation sequencing (NGS) panel for detection and identification of microbes. Our Phase I studies have demonstrated the feasibility of our diagnostic tool for application to subclinical respiratory infections and its superiority to both microbiological and molecular approaches to diagnosis. Our NGS diagnostics (Dx) panel is a significant technological innovation over current methodology; the Dx panel utilizes samples directly from the patient (rather than relying on cultures), provides greater sensitivity than qPCR or meta-genomic sequencing approaches and screens for the presence of tens of thousands other microbes in a single assay. These features are possible due to our Dx panel design in addition to proprietary laboratory and analysis workflows. The long-term goal of this project is to provide novel clinical tools for the detection of low- burden microbial infections driving disease pathology, symptomology, and exacerbations in chronic lung disease populations. In this Phase II, we will develop a data integration system to 1) deploy our diagnostic test in healthcare organizations to drive physician adoption, 2) build data and apply algorithms necessary to expand the impact and value-based reimbursement of our assay. Our Aims are to 1) develop a cloud-based commercial software system for data receipt, storage, analysis and clinical reporting at scale, 2) integrate our software system into the clinical workflow at our clinical partners, and 3) develop a web-based visualization portal for test results and build the infrastructure for use of advanced statistical learning algorithms. This integrated system will drive the development and application of personalized medicine approaches for diagnosis and treatment guidance currently missing in chronic lung disease. The total market for this diagnostic is the set of chronic lung disease patients with uncontrolled symptoms who could be screened for sub-acute infections. Our competitive advantages include improved sensitivity, comprehensive microbe detection, streamlined analysis, and treatment effectiveness insights within a single assay.