📋 Tender Overview
Grant agreement ID: 101080581
DOI
10.3030/101080581
EC signature date
11 April 2023
Start date
1 July 2023
End date
30 June 2027
Description
Parkinson's disease (PD) is characterised by the progressive loss of dopamine-producing brain cells, leading to diverse motor and non-motor symptoms. PD is often missed or misdiagnosed as early signs are subtle and common with other diseases, while selecting the optimal treatment is usually a lengthy process, leading to unnecessary suffering. Funded by the Horizon Europe programme, the AI-PROGNOSIS project aims to advance PD diagnosis and care by harnessing the power of AI. The consortium will develop predictive models for PD risk and prognosis based on in-depth health and genetic data and combine them with specific biomarkers measured in everyday life. Project work will lead to the creation of a digital health toolkit offering persons affected by PD and healthcare professionals valuable insights for informed health management.
Objective
Parkinson’s disease (PD) is the most common neurodegenerative movement disorder, with a multifactorial aetiology, heterogeneous manifestation of motor and non-motor symptoms, and no cure. PD is often missed or misdiagnosed, as early symptoms are subtle and common with other diseases, allowing for considerable damage to occur before treatment. Moreover, selecting the optimal medication regimen is usually a lengthy, trial and error process, leading to critical, costly non-adherence. Following a trustworthy and inclusive approach to AI development and based on multidisciplinary expertise and broad stakeholder engagement, AI-PROGNOSIS aims to advance PD diagnosis and care by: 1) developing novel, predictive AI models for personalised PD risk assessment and prognosis (in terms of time to higher disability transition and response to medication) based on multi-source patient records and databases, including in-depth health, phenotypic and genetic data, 2) implementing a system of biomarkers informing the AI models by tracking key risk/progression markers in daily living, and ultimately 3) translating the models and digital biomarkers into a validated, privacy-aware AI-driven toolkit, supporting healthcare professionals (HCPs) in disease screening, monitoring and treatment optimization via quantitative, explainable evidence, and empowering individuals with/without PD with tailored insights for informed health management.
