BEAMER

BEAMER is a research project that develops a comprehensive, disease-agnostic behavioural and patient adherence model, aiming to improve the quality of healthcare services, clinical outcomes, and the cost-effectiveness of healthcare systems
Project ID
Funding Organization:
Funding Programme:
H2020-JTI-IMI2-2020-23
Funding Instrument:
Research and Innovation Action (RIA)
Start Date:
01/09/2021
Duration:
60 months
Total Budget:
11,794,911 EUR
ITI Budget:
401,562 EUR
Scientific Responsible:

The BEAMER project aims to develop an innovative behavioural and patient adherence model, which can be applied independently of disease and tailored to the needs of each individual patient. The model leverages Real World Data derived from patient behaviour and healthcare systems, enabling a better understanding of the patient journey and treatment adherence levels. Through the use of Artificial Intelligence, Machine Learning, and Natural Language Processing, BEAMER transforms the way healthcare stakeholders interact with patients. The project will be evaluated through pilot implementations in six European countries, involving more than 18,000 patients, while at the same time creating an open European database for the continuous improvement and exploitation of project outcomes.

CERTH/ITI (Centre for Research and Technology Hellas / Information Technologies Institute) plays an important technical and research role in the BEAMER project, contributing to the development and evaluation of data-driven solutions for patient adherence. In particular, CERTH focuses on the design and implementation of technologies for the collection, integration, and analysis of Real World Data, supporting the development of interoperable infrastructures and data analytics frameworks. It also contributes to the development of the BEAMER platform, including data visualisation and decision-support tools, as well as to the validation and optimisation of the behavioural model. Through its contribution, CERTH helps ensure that the proposed solutions are robust, scalable, and suitable for deployment in real-world healthcare environments, addressing challenges related to data interoperability, performance, and reliability.

Consortium

Universidad Politécnica de Madrid (UPM), Spain
Open Evidence, Spain
Universidade do Porto (UPORTO), Portugal (until July 2023)
Empirica GmbH, Germany
University of Oslo (UiO), Norway
CERTH, Greece
Tilburg University (TiU), Netherlands
APDP, Portugal
FISM, Italy
ECHAlliance, Ireland
Servicio Madrileño de Salud (SERMAS), Spain
UDG Alliance, Switzerland
Akershus University Hospital (A-HUS), Norway
UPPMD, Netherlands
MEDIDA, Portugal
Innovation Sprint, Belgium
University Hospital Cologne (UHC), Germany
MySphera, Spain
Heinrich-Heine University Düsseldorf (UDUS), Germany
IDIAP Jordi Gol, Spain
Pfizer Ltd, United Kingdom
Astellas Pharma Europe, Netherlands
Link2Trials, Netherlands
Janssen Pharmaceutica, Belgium
Novo Nordisk, Denmark
Servier, France
Takeda Pharmaceuticals International AG, Switzerland
Merck KGaA, Germany
PredictBy, Spain

Contact

Dr. Konstantinos Votis
(Scientific Responsible)
Building A - Office 2.8

Information Technologies Institute
Centre of Research & Technology - Hellas
6th km Harilaou - Thermis, 57001, Thermi - Thessaloniki
Tel.: +30 2311 257722
Fax: +30 2310 474128
Email: kvotis@iti.gr