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

icometrix

Status

Enrolling

Conditions

NMO Spectrum Disorder

Multiple Sclerosis

Myelin Oligodendrocyte Glycoprotein Antibody-associated Disease

Radiologically Isolated Syndrome

Clinically Isolated Syndrome

Study type

Observational

Funder types

Other

Industry

Identifiers

NCT06280755

ICO-S-002

Details and patient eligibility

About

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.

Full 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.

Enrollment

7,000 estimated patients

Sex

All

Ages

18+ years old

Volunteers

Accepts Healthy Volunteers

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.