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A digital tool for monitoring speech decline in ALS

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R42DC019877-01A1
Agency Tracking Number: R42DC019877
Amount: $332,831.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: NIDCD
Solicitation Number: PA21-262
Timeline
Solicitation Year: 2021
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-06-01
Award End Date (Contract End Date): 2023-05-31
Small Business Information
420 MONTICELLO ST
San Francisco, CA 94127-2861
United States
DUNS: 117371425
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 JORDAN GREEN
 (402) 617-7064
 jgreen2@mghihp.edu
Business Contact
 DAVID PAUTLER
Phone: (617) 643-4658
Email: david.pautler@modality.ai
Research Institution
 MGH INSTITUTE OF HEALTH PROFESSIONS
 
36 FIRST AVE CHARLESTOWN NAVY YARD
CHARLESTOWN, MA 02129-4557
United States

 Domestic Nonprofit Research Organization
Abstract

PROJECT SUMMARYAmyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease resulting in the progressive
loss of limb, trunk, and head and neck (bulbar) motor function and is the most common adult-onset motor neuron
disease. The disease is characterized by significant across-patient heterogeneity in the onset region and in
pattern and progression rate, making early and accurate diagnosis difficult. Most individuals with ALS will
eventually acquire bulbar symptoms, including a loss of speech and swallowing. The social and psychological
impact of communication loss on the quality of life of patients with ALS is significant and a diagnostic tool to
detect these changes early, accurately, and easily remains unmet.Moreover, improved speech testing tools are critically needed in ALS to (1) improve diagnostic testing
and monitoring, and (2) expediting clinical trials of behavioral and pharmacologic interventions. Although speech
testing is a core component of many neurological assessment batteries, few commercial digital speech
monitoring tools have been developed or scientifically validated, especially for ALS. This project aims to develop
and scientifically validate a digital speech assessment tool – the Modality Digital Speech Monitoring Tool (M-
DSMT) - for monitoring speech decline due to ALS.The M-DSMT is fully automated, online, objective, scalable, accessible, and is used in real-time. The tool
is operating-system and device-agnostic, running on commercially available laptops, tablets, or smartphones.
Therefore, if demonstrated to be effective, the proposed tool can be rapidly commercialized and deployed into
standard care and clinical trials for ALS. Our specific aims are to (1) optimize the quality and yield of remote
audio and video recordings for automated measurement, (2) determine the analytical validity of the M-DSMT,
(3) determine the clinical validity of the M-DSMT, and (4) determine the usability of the M-DSMT. This projectandapos;s
objectives are to improve diagnosis for patients with ALS, decrease costs of speech assessment, and allow
patients who have difficulty traveling to continue to have access to regular speech assessments. Ultimately, we
aim to improve the quality of care in persons with ALS and facilitate ongoing efforts to discover a cure for this
fatal disease through the development of this innovative technology.PROJECT NARRATIVE
One of the most devastating effects of Amyotrophic Lateral Sclerosis (ALS) is the progressive loss of speech
function. By creating a digital tool for assessing speech on a patient’s own computer or mobile device, Modality.AI
and MGH of Health Professionals aim to develop a telehealth service to determine communication status in
patients with ALS and document treatment outcomes in a real-world setting. Ultimately, this technology aims to
improve diagnosis for patients with ALS, decrease costs for patients and healthcare providers, and provide
access to accurate speech assessments while eliminating the need for travel.

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

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