Wearable Sensor and Digital Technologies for Quantitative Assessment and Remote Monitoring of Symptoms in Myasthenia Gravis

Myasthenia gravis (MG) is a chronic autoimmune neuromuscular disease characterized by fluctuating muscle weakness and symptoms that interfere with activities of daily living and negatively impacts quality of life. MG symptoms are currently assessed in person through a careful history and physical exam by a neuromuscular disease expert. Such in-clinic assessments are time-consuming, subjective, only provide a snapshot of a patient's disease and do not adequately reflect the spectrum of fluctuating weakness and symptoms. In 2019, NIH funded a rare disease clinical research consortium called MGNet. The consortium is focused on improved characterization of clinical phenotypes, discovery of biomarkers, and advancing clinical trial readiness for MG, which would enhance the development of more effective and personalized treatments. In this Fast Track SBIR project, BioSensics will collaborate with Massachusetts General Hospital - one of the key Consortium sites for MGNet - to develop and validate a wearable sensor solution (MGWear) for continuous remote monitoring of motor symptoms and function in MG patients and also a secure mobile application (MG app) for automatic assessment of speech and facial characteristics. The mobile application will also enable the transfer of data from the wearable device to BioSensics HIPAA-compliant backend cloud called BioDigit Cloud.

The objective of the study is to evaluate the feasibility of using wearable sensor and digital technologies to measure motor and speech function as well as developing metrics to measure ocular and facial expression to monitor disease activity and fluctuating muscle weakness in people with Myasthenia Gravis (MG).To achieve this objective, the investigators will conduct an observational study is to investigate the correlation between outcomes as measured by the PAMSys sensor and digital health technologies with the total score and sub-scores of MG specific outcome measures.

A key application and market for the proposed solution technology is pharmaceutical clinical trials. Wearable sensors and digital technologies like the technology proposed here could allow drug developers to test and iterate faster, providing a valuable new method for evaluating efficacy. Clinically, the proposed solution could be used to predict an individual's response to immunosuppressive drugs and to improve medication titration. Such solutions can enable detecting subtle changes in movement-based and digital biomarkers and provide insight into the phase of clinical disease onset. Additionally, the growing use of telemedicine to expand access and potentially reduce costs of high-quality care will require remote assessment strategies. 20% of states in the US (10 out of 50 states) have no specialized care for MG. Travel time, distance and cost may limit patients' access to expert care, even in states with identified MG specialists. The proposed remote monitoring technologies have potential to lessen barriers to quality care access for MG patients.