Health virtual twins for the personalised management of stroke related to atrial fibrillation
Health virtual twins for the personalised management of stroke related to atrial fibrillation
批准号:
10102834
负责人:
金额:
$105.6万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --
中文摘要
房颤(AF)是世界范围内最常见的心律失常,导致限制生命的并发症,高经济负担和显著的资源利用。在欧洲,中风是房颤的一种衰弱性并发症,是最常见的死亡原因之一,也是导致残疾的主要原因。房颤患者发生缺血性卒中的风险增加了5倍。房颤相关性卒中(AFRS)的功能恢复通常不令人满意,导致严重残疾,生活质量下降和高死亡率。TARGET的目标是从健康状态、病理生理和疾病发病、进展、治疗和恢复开始,为房颤相关卒中途径开发新型个性化、集成、多尺度计算模型(虚拟双胞胎)和决策支持工具。TARGET旨在帮助预防房颤和AFRS,优化急性管理和康复,减少长期残疾,为患者和护理人员提供更好的生活质量,并降低医疗保健成本。我们将确保患者是项目的核心,与经验丰富的商业合作伙伴的联系将确保塔吉特的新技术得到迅速采用。新的观察数据将通过4项精心设计的前瞻性临床研究收集,这些研究将用于使用临床试验模拟(虚拟/计算机)测试和验证个性化工具和虚拟双胞胎模型,以证明有临床意义的结果。TARGET还将有助于巩固现有的心脏、大脑和神经肌肉骨骼系统的机械虚拟双胞胎模型,丰富这些双胞胎以完成更复杂的任务,并支持研究向更综合的人类虚拟双胞胎迈进。TARGET是一个里程碑式的项目,旨在改善房颤和AFRS患者的护理和康复,在疾病的风险预测、诊断和管理方面引入了范式转变,并加速了转化研究的实践。
英文摘要
Atrial fibrillation (AF) is the most common heart arrhythmia worldwide, leading to life-limiting complications, high financial burden and significant resource utilisation. In Europe, stroke as a debilitating complication of AF, is amongst the commonest causes of death and the leading cause of disability. AF patients have a 5-fold increased risk for ischaemic stroke. Functional recovery from AF-related stroke (AFRS) is often unsatisfactory, leading to severe disability, reduced quality of life and high mortality. TARGET’s ambition is to develop novel personalised, integrated, multi-scale computational models (virtual twins) and decision-support tools for the AF-related stroke pathway, starting from the healthy state, pathophysiology and disease onset, progression, treatment and recovery. TARGET aims to help prevent AF and AFRS, optimise acute management and rehabilitation, reduce long-term disability, provide a better quality of life for patients and caregivers, and lower healthcare costs. We will ensure patients are at the heart of the project, and the association with experienced commercial partners will ensure the swift adoption of TARGET’s novel technologies. New observational data will be collected via 4 carefully designed prospective clinical studies, which will be used to test and validate the personalised tools and the virtual twin models using a clinical trial simulation (virtual/in-silico), to demonstrate evidence of clinically meaningful results. TARGET will also help consolidate existing mechanistic virtual twin models of the heart, the brain and the neuromusculoskeletal system, enriching these twins to deliver more complex tasks, and supporting research to move towards a more integrated human virtual twin. TARGET represents a milestone project to improve the care and rehabilitation of patients with AF and AFRS, introducing a paradigm shift in risk prediction, diagnosis and management of the disease, and accelerating translational research into practice.
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