PROJECT SUMMARY 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 that provides care to approximately 200 MG patients - 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 (i.e. dysarthria and ptosis), which are the most common symptoms of MG. The mobile application will also enable the transfer of data from the wearable device to BioSensics HIPAA-compliant backend cloud called BioDigit Cloud that can be accessed via a secure website. The project will complement outcome and biomarker research by MGNet and represent significant public health need and market opportunity for BioSensics. A key application and market for the proposed solution technology is pharmaceutical clinical trials. Wearable sensors and digital technologies like the technology proposed here will allow drug developers to test and iterate faster, providing a valuable new method for evaluating efficacy. BioSensics is a leader in providing wearable sensor and digital technologies for clinical trials. This project will significantly broaden BioSensics offerings and capabilities by providing mobile health (mHealth) technologies for remote monitoring of motor symptoms, speech and ptosis in MG and other neurological diseases. Clinically, the proposed solution can be used to predict an individual's response to immunosuppressive drugs and to improve mediation 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.

PROJECT NARRATIVE Myasthenia gravis (MG) symptoms are currently assessed in person through a 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, which is a hallmark of MG. In this project, we will develop and validate MGWear, a wearable sensor solution 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 (i.e., dysarthria and ptosis), which are the most common symptoms of MG.