AIND: Personalized Data-driven Prevention of Neurodegenerative Disorders: a Datalake & Artificial Intelligence approach

Datalakes and AI to improve neurodegenerative disorders prevention
Thematic area: Health, Projects
Financing: ICSC Innovation Grants
Enabling Technology: Artificial Intelligence, High Performance Computing

The social burden of neurodegenerative disorders (NDD) of the elderly are growing in importance worldwide. To contain their progression and related healthcare costs early diagnosis and prevention are needed. Through personalized prevention systems, obtainable with the implementation of a datalake, it is possible to improve the processes of diagnosis and cure. 

Italian Research Center on High Performance Computing Big Data and Quantum Computing (ICSC), project funded by European Union – NextGenerationEU – and National Recovery and Resilience Plan (NRRP) – Mission 4 Component 2. 

The goal

The social burden of neurodegenerative disorders (NDDs) of older adults is growing in importance worldwide. Early diagnosis and prevention are needed to contain their progression and related healthcare costs.  

The project aims to develop customized artificial intelligence solutions to determine the risk of contracting NDDs based on data derived from multiscale NDD health datalakes consisting of available clinical databases, available disease models and previously proposed predictive algorithms. 

The initial challenge

The prevalence of Alzheimer’s disease and related dementia disorders (AD-NDD), which currently accounts for 57.4 million people worldwide, will grow to 152.7 million in 2050. The prevalence of Parkinson’s disease and related motor disorders (PD-NDDs) is expected to double by 2040, from the current 7 million to 14 million worldwide. Considering the significant impact on quality of life, personal and family suffering, and social costs, early diagnosis and prevention are the most promising approach, with the aim of containing the progression of disorders and related healthcare costs.  

Knowledge of a reasonable risk of developing an NDD in the next 4-8 years could help each individual make educated decisions regarding lifestyle changes, commitment to new disease-modifying treatments, and prospective assessment of the impact on the personal/family organization over the years. Recent scientific findings have confirmed that lifestyle changes can affect the risk of NDD, while new disease-modifying drug treatments, effective if dosing starts in the early stages of A-NDD, will be available as early as 2024 (and hopefully also for PD-NDD in the next 2-3 years). 

The solution

The project proposes to develop personalized artificial intelligence (AI) solutions to determine the risk of contracting NDDs, such as AD and PD, in otherwise healthy adults with early prodromal markers. 

The systems are based on converged data derived from multiscale NDD datalakes consisting of a broad inclusion of public or private (but available) databases and evidence-based peer reviewed datasets, as well as disease models and predictive algorithms previously proposed and published in specialized scientific papers. 


The outcome of this project is expected to provide material for a “proof-of-concept” that could generate intellectual property, contributing to the impact of the ICSC in the biomedical area covered by Spoke 8.  

It will contribute in a unique way to the training of young AI/Data-Science specialists in biomedical applications. 


Participating Spoke

Spoke 8


For further information, please contact:

Sustainable Development Goals


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