# Development of an AI-empowered device that utilizes multimodal data-visualization to aid in the diagnosis, and treatment, of OUD

> **NIH NIH R44** · WAVI COMPANY · 2023 · $319,080

## Abstract

Abstract
Assessing the effectiveness of opioid use disorder (OUD), where high relapse rates create
financial and social tolls, is a pressing clinical problem in need of better measurement tools.
The ability to identify cognitive changes should improve outcomes but current intake into
rehabilitation programs doesn’t typically include cognitive tests. Simple, quick, cost-effective,
and objective measures are needed. This is the problem this proposal seeks to address.
This proposal utilizes the experience of 8 different rehab clinics which serve 150 patients
weekly, and WAVi, a commercialized brain-assessment platform that combines EEG evoked
responses (ERP) with 5 other tests also sensitive to addiction (heart rate variability, physical
reaction times, MoCA, Trail Making, and Flanker). This user-friendly platform focuses on
minimizing testing times and cost while maximizing information.
For this fast-track application, we will have the following milestones:
 - Collect more OUD data from different clinics to refine existing clustering algorithm
 and increase sensitivities and specificities so that we have a robust archetype for OUD
 vs healthy patients
 - Collect follow-up OUD data and correlate follow-up scans with successful outcomes
 of rehabilitation treatment and therefore identify those addicts whose cognitive state
 requires modified treatment approaches, with the aim of decreasing relapse rates and
 recidivism rates.
 - Develop a scalable multimodal product, including EEG with ERP, for rehabilitation
 facilities that is readily accessible to clinicians and create a dynamic data asset to help
 longitudinally predict outcomes.

## Key facts

- **NIH application ID:** 10683816
- **Project number:** 1R44DA058431-01
- **Recipient organization:** WAVI COMPANY
- **Principal Investigator:** DAVID OAKLEY
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $319,080
- **Award type:** 1
- **Project period:** 2023-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10683816

## Citation

> US National Institutes of Health, RePORTER application 10683816, Development of an AI-empowered device that utilizes multimodal data-visualization to aid in the diagnosis, and treatment, of OUD (1R44DA058431-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10683816. Licensed CC0.

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