Case Study

5000 genomes for Valle d’Aosta

ABSTRACT
High Performance Computing and Machine Learning supports genomic research to create personalized healthcare pathways.

Where: italy
Challenge
The Centre for Genome and Big Data Analysis in Valle d'Aosta is integrated into the regional healthcare system and aims to promote and accelerate the adoption of precision medicine in healthcare, improve diagnostic processes and provide personalised therapies for patients.
Approach
Engineering D. HUB is is the technological partner and provides its experience and innovative technologies in both infrastructure and data integration and analysis to create a high performance computing (HPC) infrastructure, a genomic screeening facility and a holistic health record for patients. The project aims to sequence about 5,000 genomes in 5 years on patients suffering from neurological, neurodegenerative and oncological diseases. In the process, the patient's genomic profile is analysed together with data from medical history and lifestyle habits to define personalised therapies, also with the help of Artificial Intelligence solutions.
Digital Ecosystem
Solution
Digital Ecosystem

Create and manage the High Performance Computing IT infrastructure, which must meet relevant computational and performance requirements necessary for the laboratory's activities.

Implement a holistic EHR (Electronic Health Record) solution to make patients' genetic information available through both the data already present in their medical records and additional unconventional data related to their lifestyle and well-being useful for diagnostic activities. 

In addition to the AUSL VdA medical facilities, Engineering D. HUB is collaborating with OAVDA and IIT, the project's scientific partners, to support computational development groups that use machine learning and deep learning algorithms to analyse genomic information for the diagnosis of target diseases and the identification of more effective therapeutic pathways.

Results
Markets
Ecosystem
Technologies

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