# Software as a Medical Device for detecting opioid use through voice.

> **NIH NIH R43** · TENVOS INC. · 2024 · $400,000

## Abstract

Abstract
Patients affected by opioid use disorder (OUD) face numerous challenges, ranging from stigma
to policy barriers that impede their access to care. Even after engaging OUD patients in
treatment, retention rates are disappointingly low due to a multitude of factors. Despite the
widespread adoption of virtual counseling and treatment solutions, such as telemedicine
programs using medications for opioid use disorder (MOUD), during the COVID-19 pandemic,
addiction treatment still requires in-person visits for regular drug testing. However, this
requirement can lead to non-compliance and being dropped from what is often their only
therapeutic option available. Innovative and FDA-cleared opioid use testing methods that can be
performed outside of laboratory environments address these issues and hold the promise of
increasing retention rates and improving clinical outcomes.
Tenvos’ product will be integrated into a smartphone app, enabling patients to test for opioid use
from the comfort of their home and send instant results to the clinician without the need for an
in-person visit. The proposed solution will not only improve clinical outcomes in the outpatient
OUD treatment setting but can be adopted in many other settings due to its convenience and
can, potentially, unlock new workflows that were not feasible before. The FDA-regulated SaMD
itself, which is a ML-based solution, will be exposed through an API enabling its integration into
a large number of systems and applications. The API can be integrated into virtual health
solutions and provide opioid use assessment real-time during an appointment. It can be
integrated into a wearable device and serve as a remote patient monitoring device that notifies
the treating physician in case of a relapse. It can also be used for population health and risk
stratification by integrating into case management calls at managed care organizations to
identify individuals who may benefit from OUD treatment. The specific aims for the Phase I set
of activities include: Aim 1: Collecting clinical data with gold standard test results and patient
voice samples to study the correlation between them. Aim 2: Validating and fine-tuning the
machine learning models with the collected clinical data. Aim 3: Engaging with the FDA Center
of Devices and Radiological Health (CDRH) through a pre-submission process to obtain
feedback on the most appropriate pathway, such as PMA, De Novo, or 510(k).

## Key facts

- **NIH application ID:** 10916742
- **Project number:** 1R43DA060696-01
- **Recipient organization:** TENVOS INC.
- **Principal Investigator:** Rima Seiilova-Olson
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $400,000
- **Award type:** 1
- **Project period:** 2024-08-01 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10916742

## Citation

> US National Institutes of Health, RePORTER application 10916742, Software as a Medical Device for detecting opioid use through voice. (1R43DA060696-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10916742. Licensed CC0.

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