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
• 负责人: JEFFREY A KAYE
• 金额: $ 206.81万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10483176
• 关键词: Adverse event; Aging; Alzheimer' s Disease; Alzheimer' s disease risk; Alzheimer' s disease therapy; Amyloid; Amyloid beta-Protein; Biological Markers; Blood Vessels; Clinic; Clinical; Clinical Research; Clinical Trials; Clinical assessments; Cognition; Cognitive; Computers; Data; Development; Devices; Disease; Early Diagnosis; Elderly; Enrollment; Environment; Evaluation; Failure; Foundations; Gait speed; Goals; Health; Home; Homocysteine; Hospitals; Image; Impaired cognition; Individual; Inflammation; Injury; Interleukins; Life; Life Experience; Magnetic Resonance Imaging; Matrix Metalloproteinases; Measures; Mediating; Memory; Methodology; Methods; Monitor; Moods; Multivitamin; Nerve Degeneration; Nutritional; Oregon; Pain; Participant; Patient Self-Report; Patients; Persons; Pharmaceutical Preparations; Physiological; Placebos; Positron-Emission Tomography; Protocols documentation; Questionnaires; Reporting; Research; Research Design; Risk; Sample Size; Sleep; Socialization; System; Technology; Testing; Time; Translating; Vascular Cell Adhesion Molecule-1; Vascular Endothelial Growth Factors; Visit; advanced disease; base; blood-based biomarker; clinical translation; cognitive function; cognitive testing; digital; effective therapy; efficacy testing; fall injury; functional decline; improved; intercellular cell adhesion molecule; pre-clinical; primary outcome; prospective; remote assessment; response; sensor; simulation; social engagement; therapy development; treatment response; β-amyloid burden

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.

项目概要 这项研究（DETECT-AD 或支持 AD 临床转化的数字评估和技术） 目标从根本上来说是 无症状的 改善早期预或早期有意义的认知功能的评估 阿尔茨海默病 (AD) 主要使用被动的家庭数字评估方法。 为了实现这一目标，该方法将在为期 36 个月的临床前 AD 试验模拟中进行测试，使用 当前的、可共享的、与技术无关的、基于家庭的评估平台，不断产生被动 和交互式传感器衍生的生物标志物 (DB) 以及日常认知和功能指标（数字 该平台还允许远程捕获传统的临床数据。 具有明确淀粉样蛋白状态的参与者（基于相对淀粉样蛋白 PET 的 Aβ 高与 Aβ 低） Aβ 高的参与者将像接受安慰剂的参与者一样进步； Aβ 负担的进展会较小，模拟有效的治疗。 每天服用多种维生素作为研究“药物”来模拟试验条件，主要结果将是改变。 来自四个关键领域的 DB 和复合 DIALS：移动性（步态速度）、认知（计算机使用）、 睡眠（睡眠时间）、社交（外出时间） 具体目标是： 1) 确定进展速度。 DB（移动性、认知、睡眠和社交参与）单独和作为聚合指标（DIALS） 在FDA 1-3期AD（Aβ高与Aβ低）参与者中，通过建立早期基准率（第一个月） 2) 确定这些数据库的效用 试验中使用的常规措施（CDR-SoB、ADCS-PACC）；以及 3) 调查探索性目标 检查这些数据库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， 3.2) 确定神经退行性变、血管风险或损伤以及营养健康随时间的变化； 嵌入式“认知时钟”（完成每周定期在线报告查询和每月认知报告的时间） 3.3) 确定不良事件随时间的波动（情绪、疾病、疼痛、急诊室、医生、医院就诊； 伤害；非研究药物变化）通过每周远程评估；以及 3.4）评估研究伙伴的情况； DB 相对于 AD 患者而言会发生变化（活动能力、睡眠、社交参与）。 学习 因此 顺利完成本次 将提供经过验证的基础 DB 和 DIALS 数据，提高治疗反应读数的灵敏度； 提高 AD 临床试验能力和能力。目的不仅是验证单个应用程序或设备， 但为了推进生态有效的多领域评估，以及特定环境的整个试验， DB 促进的方案可以进行调整和共享，以供未来的任何临床试验使用。