• A Strategic Initiative

    for the University of Pavia
  • Local and National factors

    in the right place
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Big-data enabled bio-medical informatics systems for translational medicine

The University of Pavia has a recognized international leadership in the area of Bio-medical Informatics, thanks to the Laboratory of Biomedical Informatics “Mario Stefanelli” (BMI) and the Laboratory of Bioinformatics, Mathematical modeling and Synthetic Biology (BMS), both of the Department of Electrical, Computer and Biomedical Engineering.  Their activity develops though the collaboration with the biomedical departments of the University of Pavia, with the Pavia IRCCS hospitals and with pharmacological industries, and result in a number of national and international projects.

Biomedical Informatics research and activities can be of clear benefit for the development of the CHT, both in terms of confirming the international leadership of the University of Pavia and in providing tools and systems that may provide the informatics backbone of the disease-related research projects carried on by the CHT. For these reasons, within the years 2015-2017, biomedical informatics activities will concern big-data enabled bio-medical informatics systems for translational medicine.

A challenge of clear importance for the development of CHT research is the extension of biomedical informatics systems to manage, analyse, and extract knowledge from data collections that can be referred to as “Big Data”. 

Big Data is data whose scale, diversity, and complexity require new architectures, techniques, algorithms, and analytics to manage them and extract hidden value from them. Health care, biomedical research, and population health are a source of Big Data, due to broad adoption of electronic health records in primary and specialized care, growth in clinical registries and trial databases, national programs for health IT, advances in molecular technology and digital imaging, and the increased role of patients generating health information, for instance through wearable sensors and social media.

The work within this pillar will therefore involve the following activities: