PREDICTOM_Prediction of neurodegenerative disease using an AI driven screening platform

PREDICTOM_使用人工智能驱动的筛查平台预测神经退行性疾病

• 批准号: 10083181
• 金额: $ 129.86万
• 依托单位: KING'S COLLEGE LONDON
• 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=10083181
• 关键词: PREDICTOM_Prediction; neurodegenerative; 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 progressin the search for effective therapeutic interventions and it is clear that any treatment islikely to be most effective if administered at the earlieststage 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，在寻找有效的治疗干预措施方面取得了一些进展，很明显，如果在疾病的早期阶段进行治疗，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、具有成本效益的诊断标记物、工具和程序，以便在护理点识别风险增加的人群，以便分层进行个性化干预，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选平台，利用现有的在线资源来节省时间和金钱，为一般人群筛查AD和相关疾病提供证据基础。我们将通过研究使用可在家中获得的样本(例如手指刺血、唾液（用于遗传学和表观遗传学）和粪便（用于微生物组）进行诊断生物标志物分析的可行性，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、眼动追踪和基于血液的生物标志物。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，以防止进一步的认知能力下降和痴呆症的发展。我们将根据该项目产生的证据，通过制定新的临床实践指南，寻求促进当前医疗实践对阿尔茨海默病早期诊断的改变。通过提高对痴呆症早期症状患者的识别难度，我们预计将对欧洲和全世界痴呆症的个人和经济负担产生重大影响。