The collaborative project aims to unleash powerful artificial intelligence technologies on genomic and longitudinal health data in order to develop and test next-generation tools for the prevention, diagnosis and personalised treatment of both common and rare diseases.
One of its main focal points will be to develop and test the validity of improved genetic risk scores, statistical tools created based on genome-wide profiling of individuals. The scores will be integrated with life-long clinical and laboratory data to design predictive tools and identify individuals with an elevated disease risk.
The effectiveness of the tools will be tested on three diseases with a massive health burden – cardiovascular disease, type-2 diabetes and breast cancer – in Finland, Estonia and Italy.
The project also aims to establish a European platform that enables researchers and clinicians to calculate genetic scores and, ultimately, the adoption of such scores as a gold standard in clinical research.
“There is a pressing need for developing efficient development and testing platforms to enhance clinical validation of these powerful algorithms,” said Samuli Ripatti, a professor at the University of Helsinki. “Furthermore, we need the novel tools to be able to automatically calculate the scores in different ancestry groups and to communicate the risk information to clinicians and to citizens in an understandable manner.”
Ripatti highlighted that the project consortium has brought together leaders in artificial intelligence, biobanks, clinical research, information technology, and ethical, legal and societal impact from across the world.
The emphasis on the ethical and regulatory ramifications of genomics prediction is evidence of a desire to establish a framework for wider, ethically and legally responsible adoption in practice.
“We are very excited to have gathered so many brilliant and dedicated experts, very impressive datasets and world-class data analysis platform in this unprecedented joint effort to transform clinical research and precision medicine,” rejoiced Andrea Ganna, a project co-lead from the University of Helsinki.