Observational Study on Biomarker Identification for Multiple Sclerosis
A study is planned to identify biomarkers linked to disease activity and progression in multiple sclerosis (MS) by integrating clinical, imaging, and omic data from 800 participants across four countries. Participants will provide various health data, but results are currently unavailable as enrollment has not yet started.
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Why it matters
This study aims to improve patient stratification and create personalized treatment strategies, which can enhance care for people with MS despite existing therapies that often fail to predict individual responses.
What this does not prove
The study is observational and does not yet demonstrate clinical outcomes. No results are available, and planned enrollment has not started.
Next milestone
No next milestone was established from the available source.
Study facts
- Study design
- Not reported
- Participants / samples
- Not reported
- Randomised
- Not reported
- Controlled
- Not reported
- Primary endpoint met
- Not reported
- Relevant MS type
- Not reported
- Publication date
- Not reported
- Evidence reviewed
- Trial registry record
- Regulatory approval
- Not reported
- Research areas
- AI, Other
Original sources
Supporting passages (5)
subjectsArtificial intelligence and data science will be applied to integrate information from sources such as MRI, deep molecular phenotyping, exposome data, Patient Reported Outcome Measures (PROMs)/Patient-Reported Experience Measures (PREMs), and connected devices.\n\nUp to 800 participants with early MS, transitioning to progressive disease, or undergoing treatment change will be enrolled in France, Switzerland, Germany, and Luxembourg (about 100 at Centre Hospitalier du Luxembourg (CHL)).
research categories"officialTitle": "Clinnova-MS: A Prospective Cohort Study of Patients With Multiple Sclerosis: A Trans-regional Digital Health Effort Unlocking the Potential of Artificial Intelligence and Data Science in Health Care",
primary endpoint"description": "Identify clinical, epidemiological, imaging and omics characteristics associated with changes of status for different subtypes of MS patients allowing the stratification of these patients according to similar patterns and disease courses.The primary endpoint will be the change of status of the patients' disease between the baseline and at Year 1.
findings"briefSummary": "The Clinnova-Multiple Sclerosis (MS) study is part of the Clinnova program (NCT06526364; NCT06235684 and NCT05733702), which seeks to advance precision medicine and the digitalization of healthcare through high-quality, interoperable health data.\n\nThis program focuses on people with multiple sclerosis (MS) and aims to identify objective surrogate markers derived from clinical, epidemiological, imaging, and omics data that can predict disease activity, such as progression or relapses.\n\nBy combining data science and artificial intelligence, the project seeks to improve patient stratification, support personalized therapeutic decisions, and provide insights into the mechanisms underlying treatment response and disease progression.\n\nAlthough many therapies are available for MS, it remains challenging to determine the most appropriate strategy for each patient and to prevent long-term disability.
limitationsTrial registry record. Publication date: unknown. No results are posted. Planned enrolment and endpoints are not findings.
AI assessment, not yet reviewed by a person · version 1 · Community votes are separate from evidence review.