# Remote and Non-Invasive Opioid Use Screening to Lower Barriers to Substance Use Disorder Diagnosis and Treatment

> **NIH NIH R43** · TENVOS INC. · 2024 · $293,170

## Abstract

Project Abstract
Substance use disorder (SUD) diagnosis and treatment requires laboratory drug testing, which
inflicts monetary, time, and interpersonal barriers to professional care. To date, there are no
remote, non-invasive and instant opioid testing options available, limiting the potential for clinical
outreach. Tenvos’ solution is an Artificial Intelligence based technology that detects opioid use
from 15 seconds of speech. Tenvos allows clinicians to screen for opioid use remotely,
mitigating the barriers to clinical intervention, streamlining the clinical workflows, reducing costs,
and improving the overall quality of patient care. Tenvos’ solution is an easily-deployable
API-first product, allowing for seamless integration into various workflows– integration with
virtual health platforms, phone appointments, or large scale automatic phone-based screening
campaigns. This new approach will increase access for rural and low-income populations as
well as incarcerated individuals.
This project aims to further develop Tenvos’ solution and the understanding of opioids’ effects
on voice production, while comparing the detection solution to current gold standard tests. The
specific aims for the project’s Phase I set of activities include: Aim 1: Collecting clinical data
from patients before and after the opioid treatment. Aim 2: Identifying 10 vocal characteristics
that are affected by opioid use and ranked from Most Affected to Least Affected. Aim 3:
Determining the accuracy of the machine learning model trained on this data measured by
Sensitivity and Specificity and 95% CI. This project will achieve the aforementioned aims
through a multisite observational study at Doctors Medical Center and Loma Linda University
Health. Selected patients in the sites’ emergency departments will provide voice samples prior
to and following opioid administration. This data collection will allow for vocal analysis to identify
characteristic differences between the voice samples taken before opioid administration and
those taken after. Furthermore, this sample collection will provide the initial feasibility data to
facilitate the necessary steps toward commercialization.

## Key facts

- **NIH application ID:** 10983723
- **Project number:** 1R43DA061400-01
- **Recipient organization:** TENVOS INC.
- **Principal Investigator:** Rima Seiilova-Olson
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $293,170
- **Award type:** 1
- **Project period:** 2024-09-15 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10983723

## Citation

> US National Institutes of Health, RePORTER application 10983723, Remote and Non-Invasive Opioid Use Screening to Lower Barriers to Substance Use Disorder Diagnosis and Treatment (1R43DA061400-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10983723. Licensed CC0.

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