Skip to main content

Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients


Start Date
End Date
Total Funding
€ 4 337 475
Funding Programme
European Countries Involved

The vision of IASIS is to turn the wave of data heading our way into actionable knowledge for decision makers. This will be achieved by integrating data from disparate sources, including genomics, electronic health records and bibliography, and applying advanced analytics methods to discover useful patterns. Big Data in healthcare is in its early days, and most of the potential for value creation is being unclaimed. One of the main challenges is the analysis of acquired data. While information is becoming ever easier to obtain, the infrastructure to collect, integrate, share, and mine the data remains lacking. These data are an invaluable resource for deriving insights to improve decision and policy making. The goal is to turn these large amounts of data into actionable information to authorities for planning public health activities and policies. The integration and analysis of these heterogeneous sources of information will enable the best decisions to be made, allowing for diagnosis and treatment to be personalised to each individual. IASIS aims to pave the way towards comprehensive access to data from disparate sources and the results of analysis, in the form of actionable knowledge for policy-making. The project will offer a common representation schema for the heterogeneous data sources. The infrastructure will be able to convert clinical notes into usable data, combine them with genomic data, related bibliography, image data and more, and create a global knowledge base. This will facilitate the use of intelligent methods in order to discover useful patterns across different resources. Using semantic integration of data will give the opportunity to generate information that is rich, auditable and reliable. This information can be used to provide better care, reduce errors and create more confidence in sharing data, thus providing more insights and opportunities. Data resources for two different disease categories will be explored, dementia and lung cancer.

Project partners

Athens Technology Center Anonymi Biomichaniki Emporiki Kai Techniki Etaireia Efarmogon Ypsilis Technologias
Grupo Espanol De Investigacion En Cancer De Pulmon
The University System Of Maryland Foundation
Alzheimer'S Research Uk
Servicio Madrileno De Salud
Rheinische Friedrich-Wilhelms-Universitat Bonn
St George'S Hospital Medical School
Fundacio Centre De Regulacio Genomica
Universidad Politecnica De Madrid
Gottfried Wilhelm Leibniz Universitaet Hannover
National Center For Scientific Research ""Demokritos

Alzheimer Europe's database on research projects was developed as part of the 2020 Work Plan which received funding under an operating grant from the European Union’s Health Programme (2014–2020).