LifeBio-ALZ: AI driven digital biomarker engine leveraging natural conversation to widely scale accessibility for early detection and assessment of Alzheimers disease progression

LifeBio-ALZ：人工智能驱动的数字生物标记引擎，利用自然对话来广泛扩展可访问性，以早期检测和评估阿尔茨海默病的进展

• 批准号: 10381308
• 负责人: Lisbeth Sanders
• 金额: $ 44.85万
• 依托单位: LIFEBIO INC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10381308
• 关键词: Affect; Algorithms; Alzheimer' s Disease; Alzheimer' s disease patient; Alzheimer' s disease test; Alzheimer’s disease biomarker; American; Amyloid; Amyloid beta-Protein; Architecture; Artificial Intelligence; Awareness; Biological Markers; Blood; Brain imaging; Caregivers; Caring; Cause of Death; Cellular Phone; Cerebrospinal Fluid; Clinical; Clinical Trials; Cognition; Consumption; Data; Data Collection; Dementia; Detection; Development; Diagnosis; Disease; Disease Progression; Disorientation; Early Diagnosis; Elderly; Emotional; Eye Movements; Family; Foundations; Health Care Costs; Health care facility; Healthcare; Impaired cognition; Incidence; Individual; Internet; Journals; Life; Life Style; Memory Loss; Modeling; Natural Language Processing; Neurologic Examination; Oxidative Stress; Patient Care; Patients; Pattern; Phase; Population; Price; Process; Reaction Time; Research Personnel; Secure; Sensitivity and Specificity; Severities; Specificity; Speech; Spinal Puncture; Staging; Symptoms; Technology; Telephone; Testing; Therapy trial; Time; Update; Videoconferencing; Visualization software; accurate diagnosis; base; care outcomes; cloud storage; common symptom; cost; dashboard; demographics; design; digital; early detection biomarkers; improved outcome; inflammatory marker; innovation; intelligent algorithm; intelligent personal assistant; language processing; life history; mental state; mild cognitive impairment; mobile application; novel; patient oriented; patient population; person centered; personalized strategies; prototype; socioeconomic disparity; software as a service; success; tau Proteins; tau-1; tool; usability

Alzheimer’s Disease (AD) is one of the most common forms of dementia to occur in elderly populations, affecting over 30 million individuals worldwide. As the U.S. elderly population continues to increase, AD incidence rises as well, as there is no neuroprotective therapy or cure. Common symptoms include memory loss, cognitive impairment, disorientation, and psychiatric issues. Traditionally, diagnosis is achieved through a combination of clinical criteria such as neurological examination, mental status tests & brain imaging. However, these strategies are challenging for detection of early AD or patients with mild symptoms, specifically during the mild cognitive impairment (MCI) stage. Mental status tests & subjective journals, kept by patients or caregivers, can track AD progression, but have low sensitivity and reliability. The most strongly established biomarkers for AD, including amyloid beta, tau protein, & phosphorylated tau, are all obtained thru CSF requiring invasive lumbar puncture. The LifeBio-ALZ technology will provide a convenient and accessible, yet comprehensive digital biomarker and analytics suite to detect & assess Alzheimer’s progression. The platform will integrate a suite of assessment domains all seamlessly captured through a single, patient-centric app that engages users in natural video chat conversation via smart digital assistant. During brief, but regular sessions, an individual answers questions following a smart sequence to evaluate awareness, engagement, cognition, reaction time, speech patterns, & emotional state. The platform will record audio/video during the conversation. Type and timing of assessments, as well as specific questions will be adaptively modulated based on AD stage, personal demographics and previous analytics to minimize user burden while still providing rich data for algorithms. Quantitative features across multiple domains will be extracted from digital speech and eye movements, and then used as inputs to an AI engine to detect and assess Alzheimer’s’ disease progression. Data will be aggregated in secure cloud storage with clinician access to dashboard visualization tools. Phase I will demonstrate core feasibility. Development will build on a strong tech foundation of an existing LifeBio platform to increase likelihood of success. Currently, LifeBio is deployed in several formats including web, phone, & mobile apps to record life histories of people reaching advanced age or facing life-threatening illnesses or memory loss. Natural language processing tools parse information into life stories shared by family or used by staff to personalize engagement in care facilities. While the existing tech provides a base, significant enhancements will be executed in Phase I. More specifically, Phase I tasks will first update platform architecture to integrate novel data domains, build on smart sequenced multidimensional questions, and enhance patient workflow interfaces. Once the enhanced app passes all technical verification testing, it will be deployed in a field data collection and usability study with wide ranging AD patient demographics and stages. Finally, collected data will be used to build and validate an AI engine for detection and assessment of Alzheimer’s progression.

阿尔茨海默病（AD）是老年人群中最常见的痴呆症之一， 随着美国老年人口的不断增加，AD 发病率影响着全球超过 3000 万人。 由于没有神经保护疗法或治愈方法，常见症状包括记忆丧失、认知能力下降。 传统上，诊断是通过综合考虑来实现的。 然而，神经学检查、精神状态测试和脑成像等临床标准。 对于检测早期 AD 或症状较轻的患者来说具有挑战性，特别是在轻度认知期间 由患者或护理人员保存的精神状态测试和主观日记可以追踪 AD。 进展，但敏感性和可靠性较低 最有力的 AD 生物标志物，包括 β 淀粉样蛋白、tau 蛋白和磷酸化 tau 蛋白均通过需要侵入性腰椎穿刺的脑脊液获得。 LifeBio-ALZ 技术将提供一种方便易用且全面的数字生物标记物 用于检测和评估阿尔茨海默病进展的分析和套件该平台将集成一套评估套件。 所有域均通过一个以患者为中心的应用程序无缝捕获，该应用程序可让用户进行自然的视频聊天 通过智能数字助理进行对话，在简短但定期的会议中，个人回答问题。 按照智能顺序评估意识、参与度、认知、反应时间、言语模式等 平台将在对话过程中记录音频/视频的评估类型和时间。 以及具体问题将根据 AD 阶段、个人人口统计数据和情况进行适应性调整 以前的分析可以最大限度地减少用户负担，同时仍然为算法提供丰富的数据。 跨多个领域的数据将从数字语音和眼球运动中提取出来，然后用作 用于检测和评估阿尔茨海默氏病进展的人工智能引擎，数据将被汇总在安全的云中。 存储，临床医生可以访问仪表板可视化工具。 第一阶段将展示核心可行性。开发将建立在现有的强大技术基础上。 LifeBio 平台可增加成功的可能性 目前，LifeBio 以多种格式部署，包括网络、 电话和移动应用程序记录高龄或面临危及生命的疾病的人的生活史 或记忆丧失。自然语言处理工具将信息解析为家人分享或使用的生活故事。 虽然现有技术提供了基础，但意义重大。 增强功能将在第一阶段执行。更具体地说，第一阶段任务将首先更新平台架构 整合新颖的数据领域，建立智能排序的多维问题，并增强患者 一旦增强的应用程序通过所有技术验证测试，它将被部署在现场。 对广泛的 AD 患者人口统计数据和阶段进行数据收集和可用性研究最后，收集数据。 将用于构建和验证用于检测和评估阿尔茨海默病进展的人工智能引擎。