This proposal develops a novel, artificial-intelligence (AI) enabled, mobile treatment delivery method that fulfills the need for a robust, secure, technology-based peer support platform to support patients with opioid use disorders (OUDs). The majority of individuals with OUDs in the United States do not receive any formal substance use treatment, and growing evidence suggests that many OUD patients turn to online social platforms to access peer support and obtain health-related information about addiction and recovery. While engagement with peers before and during recovery is a key component of many evidence-based addiction recovery programs, commonly-used online social platforms (e.g. Reddit) lack effective content moderation, with inappropriate messages ranging from misinformed advice to maliciousness. This lack of oversight precludes a deeper integration of peer support and clinical care. Our mobile platform allows patients to access a tailored support group 24/7, and is augmented with AI tools capable of understanding the emotional sentiment in messages, automatically `flagging' critical or clinically relevant content, creating a scalable system to keep groups safe and constructive. This phase I proposal demonstrates the robustness of these AI tools by adapting them to catch OUD-specific `flags' in peer messages while also examining the adoptability of the platform itself within OUD patients. A subsequent phase II proposal will test tailored, real-time interventions to `flags', allowing the commercialization of a system to harness the engagement and self-disclosure of peer groups in a clinical setting.

Public Health Relevance

The widespread and chronic nature of opioid use disorder (OUD) necessitates investment in highly scalable technology solutions. Our work has the potential to dramatically broaden access to care for patients, particularly those in highly stigmatized and rural communities, while taking an entirely novel approach to patient triaging and tracking through artificial intelligence technology. Such technology has the potential to enable new modalities of treatment and lays the foundation for a more cost-effective, yet personalized, approach to chronic OUD care.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Small Business Technology Transfer (STTR) Grants - Phase I (R41)
Project #
1R41DA047837-01
Application #
9679778
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Sazonova, Irina Y
Project Start
2019-04-01
Project End
2019-12-31
Budget Start
2019-04-01
Budget End
2019-12-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Beacon Tech, Inc.
Department
Type
DUNS #
080502643
City
Baltimore
State
MD
Country
United States
Zip Code
21202