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

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R44NS122672-01A1
Agency Tracking Number: R44NS122672
Amount: $540,712.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 000
Solicitation Number: PA21-345
Timeline
Solicitation Year: 2021
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-09-15
Award End Date (Contract End Date): 2023-07-02
Small Business Information
57 Chapel St, Suite 200
Newton, MA 02458-1080
United States
DUNS: 802270988
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 ASHKAN VAZIRI
 (888) 589-6213
 ashkan.vaziri@biosensics.com
Business Contact
 ASHKAN VAZIRI
Phone: (888) 589-6213
Email: ashkan.vaziri@biosensics.com
Research Institution
N/A
Abstract

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.

* Information listed above is at the time of submission. *

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