STRATA-FIT | Stratification of Rheumatoid Arthritis: CompuTational models to personalise mAnagement strategies for difFIcult-to-Treat disease

Summary
Difficult-to-treat rheumatoid arthritis (D2T RA) is an area of huge unmet medical need with major socio-economic consequences for patients and society. Contributing factors have been identified including co-morbidities, drug-related, biological and behavioral factors. However, identifying these patients with specific underlying and overlapping problems, or patients at risk, is a big challenge in practice.
Currently, treatment decisions are random and not sufficiently patient tailored nor data-driven. Therefore, the STRATA-FIT consortium sets out to develop and validate computational models to identify and stratify D2T RA patients into clinically relevant phenotypes using real world clinical data. We will also measure biomarkers of inflammation to further characterise these phenotypes.
Subsequently, we will execute a pilot study with a clinical decision aid based on our models to assess the effectiveness of personalised treatment strategies.
In parallel we will develop a computational model to identify early RA patients at risk of developing D2T RA. By doing so, not only will we provide better treatment for patients with D2T RA, but also work towards its prevention in early RA patients. STRATA-FIT will establish a unique European Learning Healthcare System, using a privacy-proof, state-of-the-art federated learning infrastructure in which patients with, or at risk of D2T RA are identified, stratified and treated in a personalised manner.
STRATA-FIT builds on previous work by consortium partners, who initiated and lead the European Task Force on developing points to consider for managing D2T RA. It brings together clinical experts, patient research partners and clinical-, biological-, data- and computer-scientists to tackle this major clinical challenge. When successful, STRATA-FIT will lead to more (cost-) effective D2T RA care and will greatly improve the quality of life of D2T RA patients while lowering the burden of D2T RA on Europe’s health care systems and society.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101080243
Start date: 01-05-2023
End date: 30-04-2029
Total budget - Public funding: 6 099 650,00 Euro - 6 099 650,00 Euro
Cordis data

Original description

Difficult-to-treat rheumatoid arthritis (D2T RA) is an area of huge unmet medical need with major socio-economic consequences for patients and society. Contributing factors have been identified including co-morbidities, drug-related, biological and behavioral factors. However, identifying these patients with specific underlying and overlapping problems, or patients at risk, is a big challenge in practice.
Currently, treatment decisions are random and not sufficiently patient tailored nor data-driven. Therefore, the STRATA-FIT consortium sets out to develop and validate computational models to identify and stratify D2T RA patients into clinically relevant phenotypes using real world clinical data. We will also measure biomarkers of inflammation to further characterise these phenotypes.
Subsequently, we will execute a pilot study with a clinical decision aid based on our models to assess the effectiveness of personalised treatment strategies.
In parallel we will develop a computational model to identify early RA patients at risk of developing D2T RA. By doing so, not only will we provide better treatment for patients with D2T RA, but also work towards its prevention in early RA patients. STRATA-FIT will establish a unique European Learning Healthcare System, using a privacy-proof, state-of-the-art federated learning infrastructure in which patients with, or at risk of D2T RA are identified, stratified and treated in a personalised manner.
STRATA-FIT builds on previous work by consortium partners, who initiated and lead the European Task Force on developing points to consider for managing D2T RA. It brings together clinical experts, patient research partners and clinical-, biological-, data- and computer-scientists to tackle this major clinical challenge. When successful, STRATA-FIT will lead to more (cost-) effective D2T RA care and will greatly improve the quality of life of D2T RA patients while lowering the burden of D2T RA on Europe’s health care systems and society.

Status

SIGNED

Call topic

HORIZON-HLTH-2022-TOOL-12-01-two-stage

Update Date

31-07-2023
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Horizon Europe
HORIZON.2 Global Challenges and European Industrial Competitiveness
HORIZON.2.1 Health
HORIZON.2.1.0 Cross-cutting call topics
HORIZON-HLTH-2022-TOOL-12-two-stage
HORIZON-HLTH-2022-TOOL-12-01-two-stage Computational models for new patient stratification strategies
HORIZON.2.1.5 Tools, Technologies and Digital Solutions for Health and Care, including personalised medicine
HORIZON-HLTH-2022-TOOL-12-two-stage
HORIZON-HLTH-2022-TOOL-12-01-two-stage Computational models for new patient stratification strategies