(duplicate) SPIDeRR
Research type
Research Study
Full title
Stratification of Patients using advanced Integrative modelling of Data Routinely acquired for diagnosing Rheumatic complaints
IRAS ID
350899
Contact name
Arthur Pratt
Contact email
Sponsor organisation
Newcastle upon Tyne Hospitals
Clinicaltrials.gov Identifier
10180711, HORIZON (EU) Project number
Duration of Study in the UK
4 years, 11 months, 30 days
Research summary
The ambition of the SPIDeRR consortium is to unravel the real-life complexity of early diagnosis of rheumatic diseases by considering the complete web of factors influencing patients’ symptoms. SPIDeRR’s approach will go well beyond the state-of-the-art in the following ways:
1. By identifying disease groups that require different therapies, amongst patients with similar symptoms, in contrast to the traditional approach, which captures only one disease early.
2. By integrating all relevant data dimensions (symptoms, comorbidities, social circumstances, electronic health records (EHR), biomarkers and genetics) from each healthcare level (primary and secondary care as well as patients independently seeking advice online). Access to such data will enable physicians to promptly choose a therapy that will target the specific molecular pathways that are active in the individual patient, taking both short-term effects and long-term effects — including risks for co-morbidities — into account.
3. By translating and applying machine learning techniques from the “omics” field to clinical patient data, we will develop new pipelines for translational data science, which will yield opportunities for novel therapies and treatment strategies.
We will deliver validated, science-based and data-driven diagnostic and treatment support tools for all stakeholders in the healthcare chain. Our project promises to achieve high impact through transformation of the healthcare scene for all patients with musculoskeletal symptoms, specifically at the rheumatology level, from the earliest stages of disease development — stemming from genetic predisposition combined with environmental risk factors — towards first symptoms, the onset of chronic disease and identification of the optimal treatment.REC name
London - Camden & Kings Cross Research Ethics Committee
REC reference
24/LO/0922
Date of REC Opinion
19 Dec 2024
REC opinion
Favourable Opinion