[W1/2.2] – Amber 3
Models and simulation techniques for discovering diabetes influence factors



The MOSAIC project is devoted to the development of mathematical models and algorithms that can enhance the current tools and standards for the diagnosis of T2DM, IGT and IFG; that can improve the characterization of patients suffering those metabolic disorders and that can help evaluating the risk of developing T2DM and related complications. These objectives respond to the recognized need of improving the current standards for diabetes diagnosis and treatment, enhancing the way diabetes is currently managed in Europe. The MOSAIC consortium counts on the expertise of four modelling partners who have worked over 25 years in the development of models of the human metabolic response in diabetes that will be enhanced in the project with the information related to environmental and clinical factors relevant for the objectives defined, such as socio-economic aspects, geographic localization, cultural background and nutrition. Multiple data bases cutting across geographic boundaries are available to the MOSAIC consortium as a result of the activities of previous studies and projects of the members: (a) the METABO 7FP EU project; (b) the “Healthy Breakfast” study enriched with Medtronic’s CareLink©; (c) VIVA and BOTINA longitudinal epidemiological studies over 10 years long and the 6-year follow-up of the PPP-Botnia study ; (d) outpatient clinical and administrative data of patients treated over more than 10 years by FSM of Pavia, Health Department ‘Valencia-La Fe’ and Athens Hospital; (e) data bases generated in ongoing 7FP EU studies like ePREDICE and (f) Medtronic’s CareLink© iPro2 data base for continuous glucose monitoring systems. MOSAIC integrates these models into a technological platform for diabetes management and monitoring, to facilitate the interpretation and visualization of the data so to enable a comprehensive understanding of the information by the health care professionals. Furthermore, the platform will be used during the validation phase to acquire data during the prospective study to feed the models under test.


Prof. Riccardo Bellazzi, is Full Professor of Bioengineering at the University of Pavia. His current research interests are related to Intelligent Data Analysis and knowledge-based systems, Data Mining in clinical medicine, Bioinformatics.

List of Speakers

Mr. José Verdú (Medtronic Ibérica, Spain)
Mrs. Lucia Sacchi (University of Pavia, Italy)
Mr. Francesco Sambo (University of Padova, Italy)
Mr. Antonio Martínez (Tecnologías para la Salud y el Bienestar, Spain)