Digital biomarkers are gaining momentum in multiple sclerosis (MS) care, with new findings highlighting the potential of smartphone-based assessments to transform disability monitoring. Early evidence supporting MSCopilot Detect use underscores growing industry efforts to enable scalable, remote, and standardized disease assessment, a shift that could reshape clinical  patient monitoring, and the evaluation of MS disease progression in routine practice, according to GlobalData, a leading intelligence and productivity platform.

At the 12th Congress of the European Academy of Neurology (EAN) 2026, Sanofi/Ad Scientiam presented interim analysis from the ongoing MS-DETECT (NCT05816122) study, which is one of the first pivotal trials investigating the utility of digital biomarkers. It is a multi-center trial across US, Canada, and Europe with 336 patients enrolled.

Patients that were enrolled or participating in another ongoing clinical trial were excluded from the study. The study assesses whether MSCopilot Detect can identify subtle changes concerning disability progression in MS patients caused by either relapse activity worsening or progression independent of relapses.

Christie Wong, Managing Neurology Analyst at GlobalData, comments: “The Expanded Disability Status Scale (EDSS) and the revised four-component Multiple Sclerosis Functional Composite (MSFC-4) are clinical evaluation tools which are commonly used to quantify disability and disease progression in MS. But clinicians reported that these assessments can be time consuming and it is often not feasible to conduct these during routine clinical visits. As such, MSCopilot Detect could address an unmet need for sensitive and scalable clinical measures of disability progression in patients with MS.”

Interim analysis of the study showed that MSCopilot Detect scores correlated with the MSFC-4 framework, when performed in clinic under supervision or independently by the patient in their home. This included assessments of walking capacity, cognitive processing speed, upper-limb fine dexterity, and low-contrast visual acuity. Furthermore, the correlation between the MSCopilot Detect scores and MSFC-4 scores was conserved over a 12-month period. These findings position MSCopilot Detect as a promising tool for decentralized data collection in both clinical trials and real-world settings.

Wong adds: “While MSCopilot Detect has shown promise as a tool for remote MS monitoring that can be accessed using the patients’ smartphone, the full results from the MS-DETECT study are needed to assess long-term adherence and patient attrition rates associated with use of the tool. This will be critical for evaluating real-world feasibility for monitoring disability progression.”

Further validation of MSCopilot Detect against established biomarkers for disability progression is required. For example, blood and cerebrospinal fluid biomarkers such as glial fibrillary acidic protein and neurofilament light chain, or imaging biomarkers assessing paramagnetic rim lesions, slowly expanding lesions, and accelerated brain atrophy, will be essential to strengthen MSCopilot Detect’s positioning as a surrogate or complementary endpoint in clinical trials for pipeline drugs targeting disease progression.

Wong concludes: “MSCopilot Detect represents a promising step towards more sensitive, remote, clinical assessment of MS progression, with potential implications in clinical trials and in routine monitoring of MS.”