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Artificial Intelligence will help us cure rare diseases in children

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Artificial Intelligence will help us cure rare diseases in children

Combining data from specialized children’s hospitals across Europe to improve the diagnosis and treatment of rare genetic diseases. It is the aim of the European project Better which kicked off on April 10, in Stresa, and which brings together experts and institutions in the medical and technological fields. Thanks to Artificial Intelligence, it puts the vast wealth of health data stored by hospitals at the service of science and the community, strictly observing the GDPR regulation to protect citizens’ privacy.

A platform for European hospitals

The aim is to create an easy-to-consult platform that doctors in European hospitals will be able to use to view comparable and filterable data by pathology or genetic parameters and thus train predictive models, respecting the most stringent privacy regulations.

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Leading the way in this Horizon project worth 10 million euros are Italian entities: technological partner is Datrix, an international group based in Milan that develops AI solutions to accelerate the data-driven growth of companies together with the Polytechnic of Milan and the Buzzi Children’s Hospital in Milan, together with numerous technological partners from all over Europe: they are university and hospital centers that will make their data available, including Klinikum Der Universitaet Zu Koeln (Germany), Maastricht University (Holland), Universitat Politècnica de València (Spain), Aston University (Great Britain), Universitetet i Tromsø (Norway), RheaSoft ApSm (Denmark), Noosware Bv (Holland), Fundació de Recerca Sant Joan de Déu (Spain), Hospital Sant Joan de Déu, Fundació Docència i Recerca Mutua de Terrassa (Spain), Hospital Universitario y Politécnico La Fe (Spain), Institute of Molecular Genetics and Genetic Engineering (Serbia), and Hadassah Medical Center (Israel).

“We’re talking about rare diseases: by uniting different centres, the number of case studies increases and it is therefore easier to find a cure and an effective path – he comments Matteo Bregonzio, coordinator of the Better project as well as CTO and head of the R&D department of the Datrix Group -. Thanks to the Better project, for the first time it will be possible to pool health data from medical institutions for the benefit of citizens to help doctors with research and diagnoses, giving hope to the fight against rare diseases, for which there are few funds available”.

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Half of the resources used in the project will be used for genetic sequencing, since the genetic component is essential in the pathologies being analyzed, divided into three macro areas and as many applications: rare pediatric diseases, disorders linked to the autism spectrum in children and adolescents and congenital visual problems , with a focus on retinal diseases.

How data is collected

The revolution is represented by the way in which the data will be collected and analyzed: the approach, called “Federated Learning”, trains the AI ​​models in a distributed way: it therefore does not require an exchange or sharing of data. The remain within the hospitals themselves, then generating a global model.

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“Precision medicine takes into account individual characteristics and variability at a genetic, metabolic and environmental level, offering a personalized therapeutic path and minimizing side effects – says Bregonzio -. By pooling these data, precision medicine will allow us to make the health service more efficient and to offer frontier therapies to patients”.

This is just one of the first steps towards an increasingly “data driven” medicine. “There is also a strong push from the European Commission with initiatives in favor of genetic screening and the exploitation of cross-hospital data such as the European ‘1+ Million Genomes’ Initiative and the European Health Data Space. Much evidence – concludes Bregonzio – shows that exploiting the data for patient care is functional from a medical point of view and also for reducing time and costs”.

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