PREDICTION OF ALZHEIMER’S DISEASE USING AN AI DRIVEN SCREENING PLATFORM

使用人工智能驱动的筛查平台预测阿尔茨海默病

• 批准号: 10091560
• 金额: $ 150.87万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10091560
• 关键词: PREDICTION; ALZHEIMER; DISEASE; USING; AI

Alzheimer’s disease (AD) and related disorders leading to dementia are associated with staggering costs and suffering. Recently, there has been some progress in the search for effective therapeutic interventions and it is clear that any treatment is likely to be most effective if administered at the earliest stage of disease, but the health care system is not ready for this new scenario. There is an urgent need, therefore, to establish scalable, cost-efficient diagnostic markers, tools and procedures that can identify people at increased risk, at point of care for stratification into personalized interventions to prevent or delay dementia. PREDICTOM will develop an open-source, interoperable and customisable biomarker screening platform, utilizing an existing online resource to save time and money, to generate an evidence base for general population screening for AD and related disorders. We will bring diagnostics closer to the patient by examining the feasibility of using samples which can be obtained at home (e.g. finger-prick blood, saliva (for genetics and epigenetics) and stool for microbiom) for diagnostic biomarker analysis. We will also evaluate innovative technologies for disease risk identification, including digital technologies and novel MRI, EEG, eye tracking, and blood-based biomarkers. The platform will use artificial intelligence models to analyse data from all biomarkers to identify users at high risk of developing dementia and to direct them to personalized intervention to prevent further cognitive decline and development of dementia. We will seek to facilitate a change in current healthcare practice for early diagnosis of AD through development of new clinical practice guidelines based on evidence generated in the project. By improving the ease of identification of those with early signs of dementia we expect to have a significant impact on personal and financial burden of dementia in Europe and across the world.

阿尔茨海默病(AD)和导致痴呆症的相关疾病与惊人的成本和痛苦有关。最近，在寻求有效的治疗干预措施方面取得了一些进展，显然，如果在疾病的最早阶段进行治疗，任何治疗都可能是最有效的，但卫生保健系统还没有为这种新的情况做好准备。因此，迫切需要建立可扩展的、成本效益高的诊断标记、工具和程序，以便在护理时识别风险增加的人，并将其分层为个性化干预措施，以预防或延缓痴呆症。PREDICTOM将开发一个开源、可互操作和可定制的生物标志物筛查平台，利用现有的在线资源节省时间和金钱，为AD和相关疾病的一般人群筛查生成证据基础。我们将通过研究使用可以在家里获得的样本(例如指刺血液、唾液(用于遗传学和表观遗传学)和粪便用于微生物组)进行诊断生物标记物分析的可行性，使诊断更接近患者。我们还将评估疾病风险识别的创新技术，包括数字技术和新型MRI、EEG、眼睛跟踪和基于血液的生物标记物。该平台将使用人工智能模型分析来自所有生物标志物的数据，以识别患痴呆症的高风险用户，并指导他们进行个性化干预，以防止认知能力进一步下降和痴呆症的发展。我们将寻求通过根据项目中产生的证据制定新的临床实践指南，促进当前医疗实践的变化，以早期诊断AD。通过改善对早期痴呆症患者的识别，我们预计将对欧洲和世界各地痴呆症的个人和经济负担产生重大影响。