The Advanced Analytics Research Core will support all four Research Projects at the University of Rochester Udall Center

高级分析研究核心将支持罗切斯特大学尤德尔中心的所有四个研究项目

• 批准号: 10242054
• 负责人: Michael P McDermott
• 金额: $ 30.37万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10242054
• 关键词: Algorithmic Analysis; Antiparkinson Agents; Biological Markers; Biometry; Caring; Cellular Phone; Clinic; Clinic Visits; Clinical; Clinical Trials; Collaborations; Communities; Computational Science; Computers; Data; Data Set; Development; Diagnosis; Disease Progression; Electrical Engineering; Enrollment; Evaluation; Faculty; Frequencies; Goals; Health Technology; Individual; Institution; LRRK2 gene; Measurement; Measures; Mentors; Observational Study; Outcome Measure; Pharmaceutical Preparations; Radio Waves; Research; Research Activity; Research Personnel; Research Project Grants; Research Support; Resources; Sample Size; Scientist; Severities; Standardization; Statistical Data Interpretation; Talents; Time; Universities; Visit; Work; advanced analytics; base; cohort; complex data; data management; data streams; digital; experience; improved; insight; interest; intervention effect; large datasets; machine learning algorithm; meetings; member; multidisciplinary; novel; novel therapeutics; organizational structure; predictive modeling; recruit; repository; response; sensor; signal processing; simulation; sound; synergism; tool; virtual; wearable sensor technology; webinar

SUMMARY The Advanced Analytics Research Core of the UR-Udall Center will unite deep biostatistical expertise and PD research experience at the University of Rochester with leading computational science talent from the University of Rochester, Johns Hopkins, Aston University, Sage Bionetworks, and MIT to support the UR-Udall Center's research projects and to conduct novel cross-project analyses. These projects will rely on large data sets, including the largest repository of PD clinical trial data (Project 1) and enormous data streams from smartphones (Project 3) and novel principally passive sensors (Project 4). The Advanced Analytics Research Core will rely on the talents of the Core's investigators, the resources of the individual institutions, and the data management expertise of the Center for Health + Technology to conduct its work. To enable cross-project analyses, we will enroll a group of “Super Users” (50 with PD and 20 without) that will undergo a standardized battery of in-clinic assessments over two years in addition to evaluation by at least three of the four sensors that are part of Research Projects 3 and 4, specifically smartphone, wearable sensor, video-based sensor, and radio wave-based sensor. This group will be one of the first to pair traditional clinical PD assessments with evaluations by multiple novel sensors in clinical and real-world settings. This highly characterized group will enable evaluation of the sensors' relative ability to differentiate those with PD from those without, to detect disease progression, to assess response to current medications, and to produce novel insights into PD that cannot be ascertained currently from in-clinic measurements. Beyond the work of the UR-Udall Center, the Advanced Analytics Research Core will be a resource for the Udall Center network and will also attract, develop, and mentor biostatistical and computational science talent for the greater PD community.

总结