FAIR VISION for TOP-NT

TOP-NT 的公平愿景

• 批准号: 10407811
• 负责人: JACQUELINE C BRESNAHAN
• 金额: $ 23.69万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10407811
• 关键词: Address; Affect; Anatomy; Animal Model; Area; Award; Behavioral; Big Data; Big Data Methods; Brain; Certification; Collaborations; Communities; Complex; Data; Data Commons; Data Pooling; Data Science; Data Sources; Documentation; Educational workshop; Elements; Ensure; FAIR principles; Functional disorder; Funding; Funding Agency; Generations; Goals; Healthcare; Heterogeneity; Housing; Human; Individual; Injury; Intellectual Property; Journals; Knowledge; Language; Medical; Metadata; Modeling; Modernization; Molecular; Multiple Trauma; Nervous System Trauma; Neuraxis; Outcome; Outcome Assessment; Pattern; Phase; Physiological; Positioning Attribute; Preparation; Prevalence; Process; Publications; Recovery; Recovery of Function; Reproducibility; Research Personnel; Resources; Services; Severities; Site; Spinal Cord; Spinal cord injury; Standardization; Syndrome; System; TRUST principles; Testing; Therapeutic; Translations; Trauma; Traumatic Brain Injury; Traumatic CNS injury; Treatment Efficacy; Trust; U-Series Cooperative Agreements; United States National Institutes of Health; Update; Work; bench to bedside; biomarker discovery; body system; clinically relevant; cost; data access; data format; data preservation; data resource; diverse data; economic cost; economic impact; experimental study; heterogenous data; improved; indexing; information organization; innovation; insight; large scale data; novel; open data; pre-clinical; precision medicine; preservation; productivity loss; repository; seal; spinal cord and brain injury; therapeutic development; therapeutic evaluation; trustworthiness

PROJECT SUMMARY: Trauma to the spinal cord and brain (neurotrauma) together impact over 2.5 million people per year in the US, with economic costs of $80 billion in healthcare and loss-of-productivity. Yet precise pathophysiological processes impacting recovery remain poorly understood. This lack of knowledge limits the reliability of therapeutic development in animal models and limits translation across species and into humans. Part of the problem is that neurotrauma is intrinsically complex, involving heterogeneous damage to the central nervous system (CNS), the most complex organ system in the body. This results in a multifarious CNS syndrome spanning across heterogeneous data sources and multiple scales of analysis. Multi-scale heterogeneity makes spinal cord injury (SCI) and traumatic brain injury (TBI) difficult to understand using traditional analytical approaches that focus on a single endpoint for testing therapeutic efficacy. Single endpoint-testing provides a narrow window into the complex system of changes that describe the holistic syndromes of SCI and TBI. In this sense, complex neurotrauma is fundamentally a problem that requires big- data analytics to evaluate reproducibility in basic discovery and cross-species translation. For the proposed TOP-VISION cooperative agreement we will: 1) integrate preclinical neurotrauma data on a large-scale; 2) develop novel applications of cutting-edge multidimensional analytics to make sense of complex neurotrauma data; and 3) validate bio-functional patterns in targeted big-data-to-bench experiments in multi-PI single center (UG3 phase), and multicenter (UH3 phase) studies. The goal of the proposed project is to develop an integrated workflow for preclinical discovery, reproducibility testing, and translational discovery both within and across neurotrauma types. Our team is well-positioned to execute this project given that with prior NIH funding we built one of the largest multicenter, multispecies repositories of neurotrauma data to-date, housing detailed multidimensional outcome data on nearly N=5000 preclinical subjects and over 20,000 curated variables. We will leverage these existing data resources and apply recent innovations from data science to render complex multidimensional endpoint data into robust syndromic patterns that can be visualized and explored by researchers and clinicians for discovery, hypothesis-generation and ultimately translational outcome testing.

项目摘要：对脊髓和大脑（神经特征）的创伤共同影响超过250万 在美国，每年人民的经济成本为800亿美元的医疗保健和生产力丧失。又精确 影响恢复的病理生理过程仍然很少了解。缺乏知识限制了 动物模型中治疗发展的可靠性，并限制了整个物种和人类的翻译。 问题的一部分是，神经曲霉本质上是复杂的，涉及中央的异质损害 神经系统（CNS），体内最复杂的器官系统。这导致了多种中枢神经系统 综合征跨越异质数据源和多个分析量表。多尺度 异质性使脊髓损伤（SCI）和创伤性脑损伤（TBI）难以理解 传统的分析方法着眼于测试治疗功效的单个终点。单身的 端点测试为复杂的变化系统提供了一个狭窄的窗口，以描述整体 SCI和TBI综合征。从这个意义上讲，复杂的神经瘤从根本上是一个需要大的问题 数据分析以评估基本发现和跨物种翻译中的可重复性。对于拟议的 顶级合作协议，我们将：1）在大规模上整合临床前神经曲子数据； 2） 开发尖端多维分析的新颖应用，以使复杂的神经特征有意义 数据; 3）验证在多PI单中心的目标大数据对基础实验中验证生物功能模式 （UG3期）和多中心（UH3期）研究。拟议项目的目标是开发 临床前发现，可重复性测试和翻译发现的集成工作流程以及内部和转化发现 跨神经瘤类型。鉴于先前的NIH资助 我们建造了待办事项的最大多中心，多种产品的存储库之一 几乎n = 5000名临床前受试者和超过20,000多个策划变量的多维结果数据。我们 将利用这些现有的数据资源并将数据科学的最新创新应用于渲染复杂 多维终点数据中的鲁棒综合征模式可以可视化和探索 研究人员和临床医生发现，假设生成和最终转化结果测试。