AI-assisted care for Multiple Sclerosis
Official title: Clinical Impact Through AI-assisted MS Care - A Retrospective Multi-center Observational Study
Run by icometrix · NCT06280755 · Data updated 2026-11-12
This study is testing whether using AI can help doctors better diagnose and treat people with Multiple Sclerosis by analyzing real-world data.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 7000 (estimated) |
| Sponsor | icometrix Industry-sponsored |
| Locations | 3 sites (Prague, Praha 2 and 2 other locations) |
| Status | Recruiting |
| Started | March 1, 2024 |
| Main results expected | April 2027 |
| Study ends | April 2027 |
| Registry record updated | December 12, 2025 |
| Trial ID | NCT06280755 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates include individuals with a confirmed diagnosis of Multiple Sclerosis, NMOSD, MOGAD, Clinically Isolated Syndrome, or Radiologically Isolated Syndrome.
✕Probably not a fit
Patients under 18 years of age or those deemed unsuitable by the investigator will not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
The RECLAIM study aims to create a centralized dataset to support the development of AI models that enhance diagnosis and prognosis for patients with Multiple Sclerosis and related conditions. By analyzing real-world data, the study seeks to optimize treatment strategies and monitor disease progression effectively. It focuses on differentiating between various forms of disease worsening and aims to develop MRI-based tools and biomarker models to improve patient outcomes.
Why it matters
Potential benefit: If successful, this study could lead to more personalized and effective treatment strategies for patients with Multiple Sclerosis.
How similar studies have gone: Other studies utilizing AI and data-driven approaches in Multiple Sclerosis have shown promise, indicating potential for success in this novel approach.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion criteria: * Patients must have a confirmed diagnosis of MS, NMOSD, MOGAD, CIS or RIS. * Patient (or patient's legal representative) has previously signed and dated an informed consent form (ICF) for the secondary use of their data, or assent form. Alternatively, the secondary use of the patient's data is allowed following Institutional Review Board (IRB)/Ethical Committee (EC) approval in accordance with national and local subject privacy regulations. Exclusion criteria: * Patients under 18 years of age will be excluded. * Other unspecified reasons that, in the opinion of the Investigator or Joint Steering Committee, make the patient unsuitable for participation in the study.
Where it's running
-
General University Hospital Prague
Prague, Praha 2, Czechia Recruiting -
Katholisches Klinikum Bochum - St. Joseph-Hospital
Bochum, Bochum, Germany Recruiting -
ERC Charité - Universitätsmedizin Berlin
Berlin, State of Berlin, Germany Recruiting
Study contacts
- Principal investigator: Friedemann Paul, PhD, MD — Max Delbrück Center - Charite University, Berlin, Germany
- Study coordinator: Diana M Sima, PhD
- Email: diana.sima@icometrix.com
- Phone: +32 16 369 000
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
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This trial will try a dedicated optic nerve MRI in people who recently had a first demyelinating event (clinically isolated syndrome) to see if optic nerve involvement predicts who will have a second relapse and be diagnosed with multiple sclerosis.
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Evaluating eye movement diagnostics for neurological conditions
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.