MSCopilot® App for Multiple Sclerosis

(MS-DETECT Trial)

Recruiting at42 trial locations

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: Ad scientiam

Disqualifiers: Medically unstable, Visual acuity, Pregnancy, others

No Placebo Group

Approved in 8 Jurisdictions

Trial Summary

What is the purpose of this trial?

This trial is testing MSCopilot® Detect, a smartphone app that helps people with Multiple Sclerosis (MS) monitor their condition from home. The app aims to make it easier to track disease progression and improve patient care. It involves 314 MS patients from several countries who will use the app to complete periodic questionnaires and tests. MSCopilot is a software medical device designed for the self-assessment of people with Multiple Sclerosis (PwMS), validated against traditional tests.

Do I need to stop my current medications for the trial?

The trial protocol does not specify if you need to stop your current medications. However, you must be clinically stable and not have changed your disease-modifying therapy (DMT) in the last 3 months before joining the study.

What data supports the effectiveness of the MSCopilot® App treatment for Multiple Sclerosis?

Research shows that the MSCopilot app is reliable and effective for self-assessing disability in people with Multiple Sclerosis, correlating well with traditional tests. Additionally, mobile health apps, like MSCopilot, have shown small to moderate benefits in improving cognitive function and reducing fatigue in MS patients. ^{1 2 3 4 5}

Is the MSCopilot app safe for use in humans?

The available research does not provide specific safety data for the MSCopilot app, but it is described as a software medical device for self-assessment in multiple sclerosis, suggesting it is non-invasive and likely safe for general use. ^{1 2 6 7 8}

How is the MSCopilot® App treatment different from other treatments for multiple sclerosis?

The MSCopilot® App is unique because it allows people with multiple sclerosis to self-assess their condition using a smartphone, focusing on walking, dexterity, cognition, and vision, unlike traditional hospital tests that are more time-consuming and less frequent. ^{1 2 3 4 9}

Research Team

Eligibility Criteria

This trial is for adults aged 30-65 living with Relapsing-Remitting or Secondary Progressive Multiple Sclerosis, who've been stable for the last 3 months and have an EDSS score of 2.5 to 6.5. Participants must own a smartphone compatible with the MSCopilot® Detect app, be able to use it effectively, and not be pregnant or nursing.

Inclusion Criteria

I am between 30 and 65 years old with relapsing-remitting or secondary progressive MS.

My disability level is moderate to severe but I can still walk.

My health has been stable for the last 3 months without any worsening.

Exclusion Criteria

Current drugs or/and alcohol abuse that could influence performance on the tests (clinician's judgment)

Patients have participated in another clinical study within the previous 30 days of screening or are currently participating in another study that, in the opinion of the Investigator, might interfere with the patient's full participation in the study or confound the assessment of the patient or outcome of the study

Medically unstable conditions that may hinder patient's ability to comply with the study procedures

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Inclusion

Participants download the MSCopilot® Detect app and complete an inclusion visit

1 day

1 visit (in-person)

Monitoring

Participants use the MSCopilot® Detect app for at-home monitoring and complete digital tests every 3 months

18-24 months

Digital tests every 3 months

Follow-up

Participants attend follow-up visits to assess disease progression and app usability

18-24 months

3-4 visits (in-person) at 6, 12, 18, and optionally 24 months

Treatment Details

Interventions

• MSCopilot® mobile application (Behavioural Intervention)

Trial Overview The study tests MSCopilot® Detect, a mobile app designed for MS patients to monitor their disease progression at home. It aims to standardize remote monitoring by assessing changes in symptoms and predicting shifts in disability status through digital questionnaires and tests.

Participant Groups

Group I: MSCopilot® Detect Experimental Treatment 1 Intervention

Performance of digital tests and standard test in clinic at D0, M6, M12, M18 and M24 (if applicable) Use of MSCopilot® Detect at-home in between visits during 18 or 24 months (if applicable)

MSCopilot® mobile application is already approved in Canada for the following indications:

Approved in Canada as MSCopilot Detect for:

• Monitoring of Multiple Sclerosis progression

Who Is Running the Clinical Trial?

Ad scientiam

Lead Sponsor

Trials

12

Recruited

1,500+

Findings from Research

The MSCopilot software device was validated against the Multiple Sclerosis Functional Composite (MSFC) in a study involving 141 patients with multiple sclerosis (PwMS) and 76 healthy controls, showing that it is as effective as MSFC in identifying disability in PwMS.

MSCopilot demonstrated strong correlation with MSFC scores (r = 0.81) and good reproducibility, making it a reliable tool for self-assessment of MS-related disability in clinical practice.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

MSCopilot, a new multiple sclerosis self-assessment digital solution: results of a comparative study versus standard tests. Maillart, E., Labauge, P., Cohen, M., et al.[2021]

Mobile health applications (mHealth) show promise in improving cognitive function and reducing fatigue in people with multiple sclerosis, with a small effect size for cognitive training (SMD = 0.28) and a moderate effect for fatigue (SMD = 0.61) based on a review of 36 studies involving 3091 patients.

Despite the positive findings, the current level of evidence is still unclear, and more studies are needed to validate the efficacy of mHealth interventions across various functioning problems in multiple sclerosis management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Is mHealth a Useful Tool for Self-Assessment and Rehabilitation of People with Multiple Sclerosis? A Systematic Review. Bonnechère, B., Rintala, A., Spooren, A., et al.[2021]

The smartphone-based Symbol Digit Modalities Test (sSDMT) demonstrated improved reproducibility in measuring cognitive function in 102 patients with multiple sclerosis, with a standard error of measurement of 2.94 and a smallest detectable change of 8.15, making it a reliable tool for monitoring cognitive impairment.

Using a local linear trend model on weekly sSDMT scores allows for detailed tracking of cognitive changes over time, enabling the detection of significant changes with assessments every 12 days, thus enhancing individualized patient monitoring in clinical practice.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Towards individualized monitoring of cognition in multiple sclerosis in the digital era: A one-year cohort study. Lam, KH., Bucur, IG., Van Oirschot, P., et al.[2022]

Digital technology tools are increasingly being integrated into clinical trials for multiple sclerosis (MS), enhancing treatment delivery and disease monitoring through methods like psychotherapy apps and robot-assisted exercises.

These technologies improve the standardization of outcome measures and enable better detection of symptoms and treatment adherence, shifting data collection from traditional paper-based methods to more efficient internet-based systems, which can also facilitate remote rehabilitation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Digital Technology in Clinical Trials for Multiple Sclerosis: Systematic Review. De Angelis, M., Lavorgna, L., Carotenuto, A., et al.[2021]

A study is being conducted to test whether a mobile application can significantly increase the reporting of adverse drug reactions (ADRs) among patients with relapsing-remitting multiple sclerosis (RR-MS) who are using disease-modifying drugs (DMDs).

The trial aims to enroll 180 patients across 24 centers, with the expectation that the app will boost ADR reporting by ten times compared to traditional methods, highlighting the importance of patient involvement in monitoring drug safety.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Dedicated mobile application for drug adverse reaction reporting by patients with relapsing remitting multiple sclerosis (Vigip-SEP study): study protocol for a randomized controlled trial. Defer, G., Le Caignec, F., Fedrizzi, S., et al.[2019]

The Optimise:MS study has recruited over 2,000 participants from 14 hospitals in the UK to assess the safety profile of disease-modifying therapies (DMTs) for multiple sclerosis (MS) in real-world settings, focusing on serious adverse events (SAEs).

The study's statistical analysis plan is designed to address complex confounding factors and will provide valuable insights into the long-term outcomes of DMTs, including the effects of treatment switching and pregnancy outcomes, which are often not covered in randomized controlled trials.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Challenges and Opportunities of Real-World Data: Statistical Analysis Plan for the Optimise:MS Multicenter Prospective Cohort Pharmacovigilance Study. Waddingham, E., Miller, A., Dobson, R., et al.[2022]

The PatientConcept mobile app, used by about 3000 MS patients since its launch in 2018, enhances communication between patients and physicians while allowing patients to track their health data securely and anonymously.

The app supports adherence to treatment plans by mapping risk management for disease-modifying therapies and enables continuous monitoring of Patient Reported Outcomes (PROs), making it a valuable tool for managing multiple sclerosis and potentially other chronic diseases.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

An ID-Associated Application to Facilitate Patient-Tailored Management of Multiple Sclerosis. Lang, M., Rau, D., Cepek, L., et al.[2021]

The 5 U-Turn Test (5UTT) demonstrated good-to-excellent test-retest reliability for measuring U-turn speed in people with multiple sclerosis (MS), with an intraclass correlation coefficient of 0.87, indicating it is a reliable tool for assessing gait and balance impairment.

U-turn speed from the 5UTT was significantly correlated with established in-clinic measures of walking speed and overall MS-related disability, suggesting that this smartphone-based assessment can effectively monitor mobility changes in a home setting.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

U-turn speed is a valid and reliable smartphone-based measure of multiple sclerosis-related gait and balance impairment. Cheng, WY., Bourke, AK., Lipsmeier, F., et al.[2021]

References

1. Netherlands pubmed.ncbi.nlm.nih.gov

MSCopilot: New smartphone-based digital biomarkers correlate with Expanded Disability Status Scale scores in people with Multiple Sclerosis. [2021]

2. England pubmed.ncbi.nlm.nih.gov

MSCopilot, a new multiple sclerosis self-assessment digital solution: results of a comparative study versus standard tests. [2021]

3. Switzerland pubmed.ncbi.nlm.nih.gov

Is mHealth a Useful Tool for Self-Assessment and Rehabilitation of People with Multiple Sclerosis? A Systematic Review. [2021]

4. Netherlands pubmed.ncbi.nlm.nih.gov

Towards individualized monitoring of cognition in multiple sclerosis in the digital era: A one-year cohort study. [2022]

5. Switzerland pubmed.ncbi.nlm.nih.gov

Digital Technology in Clinical Trials for Multiple Sclerosis: Systematic Review. [2021]

6. England pubmed.ncbi.nlm.nih.gov

Dedicated mobile application for drug adverse reaction reporting by patients with relapsing remitting multiple sclerosis (Vigip-SEP study): study protocol for a randomized controlled trial. [2019]

7. Switzerland pubmed.ncbi.nlm.nih.gov

Challenges and Opportunities of Real-World Data: Statistical Analysis Plan for the Optimise:MS Multicenter Prospective Cohort Pharmacovigilance Study. [2022]

8. Switzerland pubmed.ncbi.nlm.nih.gov

An ID-Associated Application to Facilitate Patient-Tailored Management of Multiple Sclerosis. [2021]

9. England pubmed.ncbi.nlm.nih.gov

U-turn speed is a valid and reliable smartphone-based measure of multiple sclerosis-related gait and balance impairment. [2021]