DETECT-AD: Digital Evaluations and Technologies Enabling Clinical Translation for Alzheimer's Disease

DETECT-AD:数字评估和技术支持阿尔茨海默病的临床转化

基本信息

  • 批准号:
    10459706
  • 负责人:
  • 金额:
    $ 147.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-15 至 2023-06-30
  • 项目状态:
    已结题

项目摘要

Project Summary This study (DETECT-AD or Digital Evaluations and Technologies Enabling Clinical Translation for AD) objective is to fundamentally asymptomatic improve assessment of meaningful cognitive function in early pre- or Alzheimer's Disease (AD) using largely passive home-based digital assessment methods.To achieve this goal the approach will be tested in a prospective 36-month pre-clinical AD trial simulation using a current, sharable, technology agnostic, home-based assessment platform, continuously generating passive and interactive sensor-derived digital biomarkers (DBs) and metrics of everyday cognition and function (digital indicators of active life status or DIALS). The platform also allows for remote capture of conventional clinical assessments. Participants with defined amyloid status (Aβ-high vs. Aβ-low based on relative amyloid PET burdens) will be enrolled. Aβ-high participants will progress as if they were receiving placebo; those with lower Aβ burdens will have less progression, simulating effective treatment. Participants will be asked to take a daily multivitamin as a study `drug' to mimic trial conditions. The primary outcome will be change in the DBs and composite DIALS from four key domains: mobility (gait speeds), cognition (computer usage), sleep (sleep times), socialization (time out of home). Specific Aims are to: 1) Determine rates of progression of DBs (of mobility, cognition, sleep and social engagement) individually and as an aggregate metric (the DIALS) in FDA stage 1-3 AD (Aβ-high vs. Aβ-low) participants, by establishing early base rates (first months of monitoring) of progression, and then, longitudinal change; 2) Establish the utility of these DBs compared to conventional measures (CDR-SoB, ADCS-PACC) used in trials; and 3) Investigate Exploratory Aims examining several high-value features of these DBs for application in trials and related studies including: 3.1) Correlate DBs and DIALS with conventional imaging and blood-based biomarkers of inflammation, neurodegeneration, vascular risk or injury, and nutritional health; 3.2) Determine the change over time of embedded “cognitive clocks” (time to complete regular weekly online report queries and monthly cognitive tests); 3.3) Establish adverse event fluctuations over time (mood; illness; pain; ER, doctor, hospital visits; injury; non-study medication changes) via weekly remote assessment; and 3.4) Assess the study partner's DBs change relative to the person with AD (mobility, sleep, social engagement). study thus Successful completion of this will provide foundational validated DB and DIALS data improving treatment response readout sensitivity; advancing AD clinical trial capability and capacity.The intent is to not only validate a single app or device, but to advance ecologically valid multi-domain assessment, as well as an entire trials-environment specific, DB-facilitated protocol that could be adapted and shared for use by any clinical trial going forward.
项目摘要 这项研究(DETECT-AD或数字评估和技术使AD的临床翻译) 目标是从根本上 无症状 改善术前早期有意义认知功能评估 阿尔茨海默氏症(AD)使用主要是被动的家庭数字评估方法。 为了实现这一目标,该方法将在前瞻性36个月临床前AD试验模拟中进行测试, 当前的、可共享的、技术不可知的、基于家庭的评估平台, 以及交互式传感器衍生的数字生物标志物(DB)和日常认知和功能的度量(数字 活动生命状态或DIALS的指示器)。该平台还允许远程捕获常规临床 评估。具有确定的淀粉样蛋白状态(基于相对淀粉样蛋白PET的Aβ高vs Aβ低)的受试者 负担)将被录取。Aβ高的参与者将像接受安慰剂一样进步;那些低A β的参与者将像接受安慰剂一样进步。 Aβ负荷的进展较小,模拟有效治疗。参与者将被要求 每天服用多种维生素作为研究“药物”,以模拟试验条件。主要结局将是 DBs和复合DIALS来自四个关键领域:移动性(步态速度),认知(计算机使用), 睡眠(睡眠时间),社会化(外出时间)。具体目标是:1)确定进展率 DB(移动性,认知,睡眠和社会参与)单独和作为一个整体指标(DIALS) 在FDA 1-3期AD(Aβ高vs. Aβ低)受试者中,通过建立早期基础率( 监测)的进展,然后,纵向变化; 2)建立这些DB的效用相比, 试验中使用的常规措施(CDR-SoB、ADCS-PACC);和3)调查探索性目标 检查这些DB的几个高价值特征,以应用于试验和相关研究,包括:3.1) 将DB和DIALS与常规成像和基于血液的炎症生物标志物相关联, 神经变性、血管风险或损伤以及营养健康; 3.2)确定 嵌入式“认知时钟”(完成每周定期在线报告查询和每月认知 3.3)建立不良事件随时间的波动(情绪;疾病;疼痛; ER、医生、医院就诊; 损伤;非研究药物变化);以及3.4)评估研究伴侣的 DB相对于AD患者发生变化(活动性,睡眠,社会参与)。 研究 因此 成功完成本 将提供基础验证的DB和DIALS数据,改善治疗反应读出灵敏度; 推进AD临床试验能力和容量。目的不仅是验证单个应用程序或设备, 而是为了推进生态有效的多领域评估,以及整个试验环境的具体, DB促进的方案,可以调整和共享,以供任何临床试验使用。

项目成果

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JEFFREY A KAYE其他文献

JEFFREY A KAYE的其他文献

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{{ truncateString('JEFFREY A KAYE', 18)}}的其他基金

The Pacific Aging and Cancer Studies (PACS): An Infrastructure Advancing the Use of Digital Biomarkers and Related Technologies for Research on Functional Aging and Survivorship in Cancer
太平洋老龄化与癌症研究 (PACS):促进使用数字生物标志物和相关技术进行癌症功能性衰老和生存研究的基础设施
  • 批准号:
    10648477
  • 财政年份:
    2023
  • 资助金额:
    $ 147.5万
  • 项目类别:
DETECT-AD: Digital Evaluations and Technologies Enabling Clinical Translation for Alzheimer's Disease
DETECT-AD:数字评估和技术支持阿尔茨海默病的临床转化
  • 批准号:
    10483176
  • 财政年份:
    2021
  • 资助金额:
    $ 147.5万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10203769
  • 财政年份:
    2020
  • 资助金额:
    $ 147.5万
  • 项目类别:
Oregon Alzheimer's Disease Research Center
俄勒冈阿尔茨海默病研究中心
  • 批准号:
    9922085
  • 财政年份:
    2020
  • 资助金额:
    $ 147.5万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10369034
  • 财政年份:
    2020
  • 资助金额:
    $ 147.5万
  • 项目类别:
Administrative Core
行政核心
  • 批准号:
    10641024
  • 财政年份:
    2020
  • 资助金额:
    $ 147.5万
  • 项目类别:
Oregon Alzheimer's Disease Research Center
俄勒冈阿尔茨海默病研究中心
  • 批准号:
    10203767
  • 财政年份:
    2020
  • 资助金额:
    $ 147.5万
  • 项目类别:
Oregon Alzheimer's Disease Research Center
俄勒冈阿尔茨海默病研究中心
  • 批准号:
    10369033
  • 财政年份:
    2020
  • 资助金额:
    $ 147.5万
  • 项目类别:
ORCATECH Collaborative Aging (in Place) Research Using Technology (CART)
ORCATECH 协作老龄化(就地)研究使用技术 (CART)
  • 批准号:
    9210975
  • 财政年份:
    2016
  • 资助金额:
    $ 147.5万
  • 项目类别:
ORCATECH Collaborative Aging (in Place) Research Using Technology (CART)
ORCATECH 协作老龄化(就地)研究使用技术 (CART)
  • 批准号:
    9755339
  • 财政年份:
    2016
  • 资助金额:
    $ 147.5万
  • 项目类别:

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