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

通过高灵敏度下一代测序实现慢性呼吸道疾病亚急性感染的全面诊断

• 批准号: 10325843
• 负责人: Roland Marcus
• 金额: $ 100万
• 依托单位: PEAK DIAGNOSTIC PARTNERS LLC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-17 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10325843
• 关键词: Acute; Algorithms; Asthma; Automobile Driving; Biological Assay; CLIA certified; Chronic; Chronic Obstructive Airway Disease; Chronic lung disease; Clinical; Clinical Research; Collaborations; Colorado; Computer Systems; Computer software; Computerized Medical Record; Data; Detection; Development; Diagnosis; Diagnostic; Diagnostic tests; Disease; Future; Goals; Gold; Health; Healthcare Systems; Hospitalization; Individual; Infection; Information Systems; Infrastructure; Institution; Knowledge; Laboratories; Lung; Lung diseases; Lung infections; Medical Care Costs; Metagenomics; Methodology; Methods; Microbe; Microbiology; Molecular; Online Systems; Outcome; Pathology; Patients; Pharmaceutical Preparations; Phase; Physicians; Population; Prognosis; Quality of life; Reporting; Research; Research Activity; Respiratory Tract Infections; Risk; Sampling; Secure; Sensitivity and Specificity; Series; Small Business Innovation Research Grant; Source; Symptoms; System; Systems Integration; Technology; Test Result; Testing; Time; Treatment Effectiveness; Validation; Viral; Visualization; Writing; acute infection; base; care costs; clinical database; clinically relevant; cloud based; cost; data integration; design; diagnostic assay; disease phenotype; disorder control; experience; health care service organization; improved; insight; learning algorithm; metagenomic sequencing; microbial; molecular sequence database; next generation sequencing; novel; novel diagnostics; pathogen; pathogenic microbe; personalized medicine; phase 1 study; productivity loss; provider adoption; relational database; research clinical testing; respiratory pathogen; scale up; software systems; statistical learning; targeted sequencing; technological innovation; tool; treatment strategy; web portal

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.

抽象的 亚急性肺部感染越来越被认为是导致部分人群症状控制不佳的原因 据估计，美国有超过 200 万患有慢性肺病的人患有哮喘和慢性阻塞性肺病 患者。当这些亚急性感染得到适当诊断和治疗时，慢性肺部疾病 患者可以从中度/重度转变为轻度疾病表型，需要较少的药物来实现 以显着降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数周才能完成，灵敏度有限，并且类型和类型也有限 通过一次测试可以筛选的微生物数量。因此，由于当前无法 全面、准确地检测低负荷临床样本中微生物病原体的诊断， 是改善慢性肺病临床结果的重大障碍。我们因此开发了一个 用于检测和鉴定微生物的综合下一代测序 (NGS) 组合。我们的阶段 研究证明了我们的诊断工具应用于亚临床呼吸系统疾病的可行性 感染及其相对于微生物学和分子诊断方法的优越性。我们的NGS 诊断（Dx）面板是对当前方法的重大技术创新； Dx 面板利用 直接从患者身上获取样本（而不是依赖于培养物），比 qPCR 或 宏基因组测序方法和筛选在一个环境中是否存在数以万计的其他微生物 单一测定。这些功能之所以成为可能，是因为我们的 Dx 面板设计以及专有实验室和 分析工作流程。该项目的长期目标是提供新的临床工具来检测低- 导致慢性肺病的病理学、症状学和恶化的微生物感染负担 人口。在第二阶段，我们将开发一个数据集成系统，以 1) 在 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 我们的检测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 系统融入我们临床合作伙伴的临床工作流程，以及 3) 开发一个基于网络的可视化门户用于测试 结果并构建使用高级统计学习算法的基础设施。这个集成系统将 推动个性化医疗诊断和治疗方法的开发和应用 目前慢性肺病缺乏指导。该诊断的总市场是慢性肺疾病的集合 症状不受控制的疾病患者，可以筛查亚急性感染。我们的竞争力 优点包括提高灵敏度、全面的微生物检测、简化的分析和处理 一次测定中的有效性见解。