Clinical Impact Through AI-assisted MS Care - A Retrospective Multi-center Observational Study. (RECLAIM)

Clinical Impact Through AI-assisted MS Care - A Retrospective Multi-center Observational Study

The RECLAIM study aims to gather a centralized and harmonized dataset, enabling the secondary use of data for building AI-based models that will support diagnosis and prognosis of individual Multiple Sclerosis patient's disease course and treatment response in a real-world setting. Additionally, the data will be used to generate further insights on Multiple Sclerosis progression as well as to develop the tools to monitor this progression.

Study Overview

• Status: Recruiting
• Conditions: Multiple Sclerosis; Clinically Isolated Syndrome; Radiologically Isolated Syndrome; NMO Spectrum Disorder; Myelin Oligodendrocyte Glycoprotein Antibody-associated Disease

Detailed Description

There is a clear need for a data-driven and personalized treatment optimisation tool for people with Multiple Sclerosis (MS), in order to enable/support physicians to deploy appropriate therapeutic measures that will help to better slow down disease progression and eventually, progressive disability worsening. While early diagnosis and prognostic modelling is important to make data-driven recommendations for treatment optimisation, being able to disentangle and monitor the disability accumulation due to 'relapse associated worsening' or due to 'progression independent of relapse activity' will be key to optimizing treatment for the best possible long-term outcomes. The latter strongly depends on the availability of biomarkers that can detect and differentiate between these different forms of disease worsening.

With the RECLAIM study, we focus on gathering a centralized and harmonized dataset, enabling the secondary use of data to support prognosis for people with MS, as well as treatment optimisation in a real-world setting. As such, RECLAIM aims to develop MRI-based tools to better monitor disease progression in people with MS, as well as AI-based models that will support prognosis of individual disease course and treatment response, comprising: (i) a biomarker-based MS progression model, (ii) an MRI-focused generative model to predict brain characteristic evolution, and (iii) an interventional model for treatment optimisation. Additionally, the data will be used to generate further insights on Multiple Sclerosis progression as well as to develop the tools to monitor this progression.

• Study Type: Observational
• Enrollment (Estimated): 7000

Contacts and Locations

• Study Contact: Name: Diana M Sima, PhD; Phone Number: +32 16 369 000; Email: diana.sima@icometrix.com
• Study Contact Backup: Name: Vincenzo Anania; Phone Number: +32 16 369 000; Email: vincenzo.anania@icometrix.com

Study Locations

• Czechia
  • Praha 2
    • Prague, Praha 2, Czechia, 128 00
      • Recruiting
      • General University Hospital Prague
      • Contact: Dana Horakova, Doc. MUDr., PhD
• Germany
  • Bochum
    • Bochum, Bochum, Germany, 44791
      • Recruiting
      • Katholisches Klinikum Bochum - St. Joseph-Hospital
      • Contact: Carsten Lukas, Prof. Dr. med.
  • State of Berlin
    • Berlin, State of Berlin, Germany, 131256
      • Recruiting
      • ERC Charité - Universitätsmedizin Berlin
      • Contact: Tanja Schmitz-Hübsch, PD Dr.

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Probability Sample

Study Population

The study will include patients with a confirmed diagnosis of MS (Thompson et al., 2018), CIS, RIS, NMOSD (Wingerchuck et al., 2015), or MOGAD (Banwell et al., 2023). No other specifications are included. We envision a database that captures the diversity and heterogeneity of the population, in order to address factors influencing disease worsening that have not been investigated yet or have only been investigated to a very limited extent in previous studies.

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Data from real-world clinical practice; Retrospective, real-world clinical data obtained via the 6 participating clinical centers in the study.
Data from the control arms of relevant clinical trials; Data from the control arms of relevant clinical trials obtained via the 4 participating pharmaceutical partners in the study.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
The number of patients from each institution who have contributed data to the database.	4 years
The number of patients from each institution whose data was mapped to the common data model of the harmonised database.	4 years
The number of patients from the control arms of clinical trials who have contributed data to the database.	4 years
The data completeness of each variable in the harmonised database.	4 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The representativeness of the harmonised dataset for the MS patient population as evaluated by age range, gender balance, the distribution of country of residence, the distribution of race/ethnicity and the distribution of educational level		4 years
The validity of the data through an assessment of the amount of erroneous or impossible data entries for each variable.		4 years
The temporal uniformity of each institution's data over time as assessed by the number of changes to variables over time (addition of new variables or variables no longer being captured, alterations to how variables are captured).		4 years
The temporal uniformity of the harmonised dataset over time as assessed by the average time between subsequent assessments of each variable.		4 years
The presence of contextual information on standard data gathering and analysis processes of each institution		4 years
The presence of a unique and pseudonymised patient ID for all data of each patient, allowing to link such data of each patient.		4 years
The temporal uniformity of MRI data over time as assessed by the comparability of MRI scans and the average time between subsequent MRI assessments for each patient.		4 years
The percentage of MRI data sets which are compliant with the MAGNIMS-CMSC-NAIMS acquisition guidelines.		4 years
The percentage of MRI data sets for which the automated quality control process of icobrain ms did not indicate any quality issues upon analysis.		4 years
The percentage of patients with a complete disease modifying treatment history available, from the date of diagnosis to the current day.		4 years
The percentage of patients with a complete disease history available, from the date of diagnosis to the current day.		4 years
The validity and temporal uniformity for disability assessment as clinically determined by EDSS, Functional systems score, T25FWT, 9HPT and SDMT.	Each of these scores will be assessed individually for the amount of erroneous or impossible data entries, as well as for the average time between subsequent assessments of each variable.	4 years

Collaborators and Investigators

• Sponsor: icometrix
• Collaborators: Bristol-Myers Squibb; Charite University, Berlin, Germany; Hoffmann-La Roche; Ruhr University of Bochum; University Hospital, Lille; Technische Universität Dresden; Aalto University; General University Hospital, Prague; AB Science; Imcyse SA; Casa di Cura IGEA; Nocturne UG
• Investigators: Principal Investigator: Friedemann Paul, PhD, MD, Max Delbrück Center - Charite University, Berlin, Germany

Publications and helpful links

Helpful Links

• Website of the EU-funded CLAIMS project of which this study is a part.

Study record dates

Study Major Dates

• Study Start (Actual): March 1, 2024
• Primary Completion (Estimated): April 1, 2027
• Study Completion (Estimated): April 1, 2027

Study Registration Dates

• First Submitted: January 23, 2024
• First Submitted That Met QC Criteria: February 19, 2024
• First Posted (Actual): February 28, 2024

Study Record Updates

• Last Update Posted (Actual): December 12, 2025
• Last Update Submitted That Met QC Criteria: December 5, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Multiple Sclerosis; Progression; Prognosis; AI models; disease worsening
• Additional Relevant MeSH Terms: Nervous System Diseases; Pathologic Processes; Disease Attributes; Autoimmune Diseases; Immune System Diseases; Eye Diseases; Demyelinating Autoimmune Diseases, CNS; Autoimmune Diseases of the Nervous System; Demyelinating Diseases; Myelitis, Transverse; Optic Neuritis; Optic Nerve Diseases; Cranial Nerve Diseases; Pathological Conditions, Signs and Symptoms; Multiple Sclerosis; Disease Progression; Neuromyelitis Optica; Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease
• Other Study ID Numbers: ICO-S-002

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No