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Mobile Peer Support for Opioid Use Disorders: Refinement of an Innovative Machine Learning Tool

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41DA047837-01
Agency Tracking Number: R41DA047837
Amount: $225,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: R41
Solicitation Number: PA18-575
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-04-01
Award End Date (Contract End Date): 2020-09-30
Small Business Information
8 MARKET PLACE, STE 300
Baltimore, MD 21202-4113
United States
DUNS: 080502643
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 FRANCESCA BEAUDOIN
 (401) 444-2577
 francesca_beaudoin@brown.edu
Business Contact
 SHRENIK JAIN
Phone: (908) 255-9419
Email: shrenik@sunrisehealth.co
Research Institution
 RHODE ISLAND HOSPITAL
 
593 EDDY STREET
PROVIDENCE, RI 02903-4923
United States

 Domestic nonprofit research organization
Abstract

PROJECT SUMMARY This proposal develops a novelartificial intelligenceAIenabledmobile treatment delivery method that fulfills the need for a robustsecuretechnology based peer support platform to support patients with opioid use disordersOUDsThe majority of individuals with OUDs in the United States do not receive any formal substance use treatmentand growing evidence suggests that many OUD patients turn to online social platforms to access peer support and obtain health related information about addiction and recoveryWhile engagement with peers before and during recovery is a key component of many evidence based addiction recovery programscommonly used online social platformse gRedditlack effective content moderationwith inappropriate messages ranging from misinformed advice to maliciousnessThis lack of oversight precludes a deeper integration of peer support and clinical careOur mobile platform allows patients to access a tailored support groupand is augmented with AI tools capable of understanding the emotional sentiment in messagesautomatically `flaggingandaposcritical or clinically relevant contentcreating a scalable system to keep groups safe and constructiveThis phase I proposal demonstrates the robustness of these AI tools by adapting them to catch OUD specific `flagsandaposin peer messages while also examining the adoptability of the platform itself within OUD patientsA subsequent phase II proposal will test tailoredreal time interventions to `flagsandaposallowing the commercialization of a system to harness the engagement and self disclosure of peer groups in a clinical setting PROJECT NARRATIVE The widespread and chronic nature of opioid use disorderOUDnecessitates investment in highly scalable technology solutionsOur work has the potential to dramatically broaden access to care for patientsparticularly those in highly stigmatized and rural communitieswhile taking an entirely novel approach to patient triaging and tracking through artificial intelligence technologySuch technology has the potential to enable new modalities of treatment and lays the foundation for a more cost effectiveyet personalizedapproach to chronic OUD care

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

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