Optimization of an at-home continuous multi-domain monitoring and assessment system to improve Alzheimer's and related disorders clinical trials

摘要：阿尔茨海默病和阿尔茨海默病相关痴呆（AD/ADRD） 影响我们庞大且不断增长的老龄化人口。估计有580万65岁及以上的美国人 患有AD，预计到2050年这一数字将达到1380万。非裔美国人和拉丁裔美国人 由于缺乏获得临床治疗的机会， 试验和医疗护理。一系列广泛的症状与这些疾病和每个病人的 进展是独特的，临床上变化很大。在临床试验期间，当纵向研究 在几个月到几年的时间里，病人的大部分生活方式和功能都没有受到监测，因为他们在 与伴侣在家或独自在家，不与专业提供者接触。不经常收集数据 依赖于患者准确检索自上次检查以来有关其生活的相关细节的能力， 由于自我报告和回忆的挑战，其固有地不准确或不完整。因此，有一个 临床试验迫切需要更频繁、准确和完整的患者监测，尤其是在 目前服务不足的社区。为了满足这一需求，Life Analytics正在进一步开发 一个家庭监控平台，称为生活分析监控平台（LAMP）。LAMP基于 NIH和VA资助了使用技术的协作衰老研究（CART）倡议系统。CART是一个 端到端（硬件和软件）平台，提供老年疾病的高频监测 通过测量真实世界的数据，从而为学术界提供数字远程评估模型， 研究社区。CART系统是由我们的研究团队在2005年建立的，并由我们的研究团队进一步开发。 俄勒冈州老龄化和技术中心（ORCATECH）。通过这些努力， 支持和部署这些系统用于学术研究的可推广基础设施已经 确立了习到目前为止，ORCATECH/CART平台已经安装在1000多个家庭， 目前正在收集数据并将其传输回ORCATECH服务器进行分析。 此外，洛杉矶团队通过出版物表明，高频率的家庭监测数据允许 临床研究的把握度适当，患者数量较少。因此，该平台具有很高的潜力， 改变临床试验的进行方式--如果这样一个系统能够广泛传播的话。这个Fastrack 将协助进行改进现有ORCATECH/CART所需的关键研究和开发 通过以下目标将LAMP平台转化为商业化的LAMP平台：SA 1（第一阶段）： ORCATECH/CART系统可确保可扩展的云操作性。SA 2（第二阶段）：LAMP的优化 数据传输、存储和分析。SA 3（第二阶段）：通过Alpha测试证明LAMP可用性， 第三方，场外位置。

Summary/Abstract: Alzheimer’s Disease and Alzheimer’s Disease-Related Dementias (AD/ADRD) adversely impact our large and growing aging population. An estimated 5.8 million American’s 65 years and older are suffering from AD, with that number projected to hit 13.8 million by 2050. Aging African American and Latinx populations are particularly hard-hit by AD/ADRD, as are rural communities due to lack of access to clinical trials and medical care. A broad range of symptoms are associated with these diseases and each patient’s progression is unique and clinically quite variable. During a clinical trial, when longitudinal studies are conducted over months to years, much of the patient’s lifestyle and function goes unmonitored as they are at home with their partner or alone and without contact with professional providers. Infrequent data collection relies on the ability of patients to accurately retrieve relevant details about their lives since the last checkup, which is inherently inaccurate or incomplete due to the challenges of self-report and recall. Thus, there is a critical need in clinical trials for more frequent, accurate, and complete patient monitoring especially in communities that are currently underserved. To meet this need, Life Analytics is furthering the development of an at-home monitoring platform, called Life Analytics Monitoring Platform (LAMP). LAMP is based off of the NIH and VA funded Collaborative Aging Research Using Technology (CART) initiative system. CART is an end-to-end (hardware and software) platform, which provides high-frequency monitoring of geriatric disease progression by measuring real-world data, thus providing a digital remote assessment model to the academic research community. The CART system was built by, and has been further developed by, our research team in the Oregon Center for Aging and Technology (ORCATECH). Through these efforts a highly functional generalizable infrastructure for support and deployment of these systems for academic research has been established. To date, the ORCATECH/CART platform has been installed in more than 1000 homes across North America and is currently collecting and transmitting data back to ORCATECH servers for analysis. Additionally, the LA team has shown through publication that high-frequency in-home monitoring data allows clinical studies to be appropriately powered with fewer patients. Therefore, this platform has the high potential to change the way that clinical trials are conducted – if such a system can broadly disseminated. This Fastrack will assist with the critical research and development required to improve the existing ORCATECH/CART platform into the commercialized LAMP platform through the following Aims: SA 1 (Phase I): Migrate ORCATECH/CART system to secure and scalable cloud operability. SA 2 (Phase II): Optimization of LAMP for data transfer, storage, and analysis. SA 3 (Phase II): Demonstrate LAMP usability with Alpha-testing with a third party, off-site location.