A Study to Train a Machine Learning Algorithm for an Evaluation of the Use of Biometric Data Captured at the Wrist for the Identification of Acute Opioid Use Events and the Quantification of Opioid Withdrawal in Opioid Dependent Individuals

February 18, 2026 updated by: OpiAID
To train a machine learning model/algorithm for an evaluation of the use of biometric data captured at the wrist for the identification of acute opioid use events and the quantification of opioid withdrawal in opioid dependent individuals.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

The goal of this real-world, multi-center, outpatient study is to train a machine learning model/algorithm utilizing patient-specific physiological parameters from the OpiAID Strength Band Platform™ can accurately detect MOUD events during the induction phase with an 80% classification success when comparing the True Positive Rate against the False Positive Rate as plotted on a Receiver Operator Curve. In addition to MOUD detection, machine learning will be used to quantify participant withdrawal level from physiological parameters. To demonstrate that withdrawal quantification performs as well or better than current measures used for this purpose the correlation between quantified withdrawal and time since last opioid dose (TSLD) will be computed and compared against the association between SOWS and TSLD in a non-inferiority analysis.

Study Type

Interventional

Enrollment (Estimated)

420

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • United States
    • North Carolina
      • Wilmington, North Carolina, United States, 28409
    • Texas
      • Austin, Texas, United States, 78745
        • Recruiting
        • Community Medical Services
        • Contact:
        • Principal Investigator:
          • Sabrie Satterwhite, PhD
      • Austin, Texas, United States, 78753
        • Recruiting
        • Community Medical Services
        • Principal Investigator:
          • Sabrie Satterwhite, PhD
        • Contact:
      • Cedar Park, Texas, United States, 78613
        • Recruiting
        • Community Medical Services
        • Principal Investigator:
          • Sabrie Satterwhite, PhD
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Male or female
  • Age ≥22 years at signing of informed consent
  • Patients with a DSM-5 diagnosis of OUD who are eligible for MOUD induction with methadone or buprenorphine

Exclusion Criteria:

  • Sleeve tattoo covering the wrist
  • Subject unable to independently navigate and operate smartwatch applications
  • Subject not proficient with written and spoken English
  • Subject determined likely to be non-compliant by physician/HCP
  • Subject likely to not be available to complete all protocol-required study visits or procedures, and/or to comply with all required study procedures to the best of the subject and investigator's knowledge.
  • History or evidence of any other clinically significant disorder, condition, or disease that, in the opinion of the investigator, would pose a risk to subject safety or interfere with the study evaluation, procedures or completion.
  • Subject has diminished decision making capability

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Supportive Care
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Single arm 14 day monitoring period

The goal of this real-world, multi-center, outpatient study is to train a machine learning model/algorithm utilizing patient-specific physiological parameters from the OpiAID Strength Band Platform™ can accurately detect MOUD events during the induction phase with a predefined classification success when comparing the True Positive Rate against the False Positive Rate as plotted on a Receiver Operator Curve. In addition to MOUD detection, machine learning will be used to quantify participant withdrawal level from physiological parameters. To demonstrate that withdrawal quantification performs as well or better than current measures used for this purpose the correlation between quantified withdrawal and time since last opioid dose (TSLD) will be computed and compared against the association between SOWS and TSLD in a non-inferiority analysis.

Prescribing physician must determine appropriate starting dose (titration expected over 2-6 weeks)
Device: Train and evaluate the accuracy and reliability of the Strength Band Platform in identifying acute opioid dosing events from time-stamped biometric data collected from wrist-worn devices.

Subjects will be fitted with the wearable device (Samsung Galaxy Watch) for the purpose of data communication and will be instructed to wear the device continuously, except when charging the watch, showering or any activity in which submersion in water is required. Participants will wear the device for 14 days.

Study subjects will be responsible for:

  • Wearing the Samsung Galaxy watch daily except when charging the watch, showering or any activity in which submersion in water is required
  • Charging the Samsung Galaxy watch daily
  • Answering prompts on the Samsung Galaxy watch
  • Answering the daily SOWS questionnaire(s)

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Classification
Time Frame: 14 days
Accurate algorithm-based classification of acute opioid dosing events in patients receiving treatment for opioid use disorder.
14 days

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

OpiAID

Collaborators

National Institute on Drug Abuse (NIDA)

Investigators

  • Study Chair: David MacQueen, PhD, OpiAID

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 1, 2025

Primary Completion (Estimated)

December 31, 2026

Study Completion (Estimated)

March 31, 2027

Study Registration Dates

First Submitted

February 5, 2026

First Submitted That Met QC Criteria

February 5, 2026

First Posted (Actual)

February 12, 2026

Study Record Updates

Last Update Posted (Actual)

February 20, 2026

Last Update Submitted That Met QC Criteria

February 18, 2026

Last Verified

February 1, 2026

More Information

Terms related to this study

Other Study ID Numbers

  • OA-SBIR-25-01
  • 4R44DA058474-02 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

Yes

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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