CLinical impact through AI-assisted MS care

Projektinformationen

CLAIMS

ID Finanzhilfevereinbarung: 101112153

DOI

10.3030/101112153

EK-Unterschriftsdatum 15 Mai 2023

Startdatum 1 Juni 2023

Enddatum 31 Mai 2027

Finanziert unter

• Health

Gesamtkosten

€ 9 633 843,75

EU-Beitrag

€ 4 783 843,75

Koordiniert durch

CHARITE - UNIVERSITAETSMEDIZIN BERLIN
Germany

Periodic Reporting for period 2 - CLAIMS (CLinical impact through AI-assisted MS care)

Berichtszeitraum: 2024-06-01 bis 2025-11-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Multiple sclerosis (MS) is a devastating immune-mediated disorder of the central nervous system. Since there is no cure available yet for MS, the primary therapeutic goal for MS patients is to slow down disability progression and to reduce relapses at early stages of the disease. Despite many available disease modifying treatments (DMTs), the large heterogeneity of the disease, which is further complicated by the high prevalence of comorbidities and multi-pharmacy, results in a poor and variable treatment response in a real-world setting.

The CLAIMS project is a public-private partnership aiming to address this and make precision medicine for MS patients a reality through data-driven prognosis and treatment optimisation, in order to better slow down disease progression. We will develop, validate and submit for regulatory approval a companion platform, which offers the MS care team a holistic view of the patient through the visualization of relevant clinical and subclinical biomarkers and the prediction of the expected disease trajectory under different treatment options. For biomarker extraction and treatment prediction, state-of-the-art technologies that allow a reliable and scalable implementation across the world will be used. We believe this platform will initiate the paradigm shift from a trial-and-error, experienced-based treatment of MS patients to a first-time-right, value-based holistic treatment management, and will, hence, improve patient outcomes at a lower total cost of care, enhance patient experience and improve the well-being of the care team.

https://www.claims.ms/

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

During the first 2.5 years of the project, we have established the data infrastructure for both the retrospective (RECLAIM) and the prospective (PROCLAIM) studies conducted in CLAIMS. Significant effort was dedicated to implementing the CLAIMS MS-specific common data model (CDM), into which the RECLAIM dataset (comprising over 5,000 real-world and nearly 3,000 clinical trial patients) was processed, harmonised, and securely stored. Data analysis and harmonisation activities included the conversion of diverse clinical data into the CDM structure and the quantitative analysis of over 50,000 MRI scans with icobrain ms, along with initial analysis of OCT data. Furthermore, the PROCLAIM study protocol was finalised. PROCLAIM is designed as a prospective multi-country multi-site study that will compare two arms: an intervention arm implementing quantitative brain MRI as part of standard of care, and a control arm implementing standard of care without quantitative brain MRI.

In addition to setting up the RECLAIM and PROCLAIM studies, we have also made great progress on several technical aspects of the project related to the development and implementation of biomarkers to monitor disease progression in more detail. As such, we’ve developed and deployed new AI-driven image analysis pipelines for MS lesion characterisation and quantification of spinal cord atrophy. Additionally, we developed and validated two smartphone-based tests to better monitor disease progression: the icompanion Symbol Test and the icompanion Finger Dexterity Test. Both tests have been implemented in the icompanion app, and await regulatory approval for making them available to patients. Finally, based on partial data from the retrospective RECLAIM dataset, we successfully developed and validated several AI model prototypes for MS prognosis and treatment response.

Last but not least, we implemented the first version of a true holistic companion platform. This platform builds upon the previous version of the icompanion HCP portal and has received a major UX/UI overhaul, focussing on displaying the information to the treating physician which is most relevant towards making an informed decision on treatment and care for a patient. In addition, several new functionalities were implemented (MRI integration, EMR integration through smart on FHIR, a fully functional eCRF module, a revised visit preparation module and more…). The platform has been deployed in the PROCLAIM study.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

Several advances towards realising the envisioned platform and its impact have been made throughout the first 2.5 years, and some of these are already having a direct impact today.

The healthcare practitioner portal for the icompanion app, which was developed in WP3, has been released to users of the portal under the new MDR regulation. Through its improved UX/UI, neurologists now have a dashboard at hand which summarizes the most important data for them (MRI, treatments, patient reported outcomes, …), improving their workflow and contributing to a more holistic view of the patient and their disease progression.

The initial versions of the pipelines to automatically quantify paramagnetic rim lesions (PRL) and spinal cord atrophy are available for users globally now, but currently only in a research setting. This is the first step towards realising the impact of these new tools, as once they are regulatory cleared for clinical use these tools will allow to transition from a subjective assessment of these biomarkers towards a fully automated and quantitative assessment, reducing workload issues for physicians while enabling better monitoring of disease progression for patients.

The icompanion app has seen significant improvements throughout the first year of the project, which greatly increase the value it brings to both patients and their neurologists. The visit preparation module allows to focus on what patients really want, and thus improving their quality of life. The revised knowledge center increases patient empowerment, and we now have two smartphone-based tests ready for integration into the icompanion app: the icompanion Symbol Test and the icompanion Finger Dexterity Test. These tests will allow remote and continuous monitoring of two clinically important measures for disease worsening.

Lastly, we have set up two large studies: the RECLAIM study, which has collected a large retrospective database of people with MS, and the PROCLAIM study, which will prospectively evaluate the clinical impact of AI-assisted MS care.

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