Using Artificial Intelligence To Monitor Medication Adherence in Opioid Replacement Therapy

NCT ID: NCT02243670

Last Updated: 2017-09-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

9 participants

Study Classification

INTERVENTIONAL

Study Start Date

2016-08-31

Study Completion Date

2017-03-31

Brief Summary

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This study uses an artificial intelligence platform to automatically confirm medication ingestion. The Health Insurance Portability and Accountability Act (HIPAA)-compliant platform can be downloaded as an 'app' onto any smartphone to automate directly observed therapy (Automated DOT®). Real-time patient adherence data are encrypted and automatically sent to a centralized web-based dashboard for use by healthcare professionals or research staff. Unlike Facetime® or Skype®, the system relies on computer vision algorithms to confirm the process of medication administration; no human review is necessary.

The purpose of this study is to evaluate the feasibility and acceptability, and measure the accuracy, of the AiCure platform ("platform") in patients being treated for opioid dependence with Zubsolv® over the course of 12 weeks. The following aims will be tested: 1) to assess the feasibility and acceptability to both participants and study staff in using AiCure to monitor medication adherence; 2) to evaluate the acceptability of using AiCure to optimize care pathways; and 3) to measure the reliability and validity of AiCure in detecting interruptions in treatment. To assess feasibility and acceptability of the platform, we will measure rates of physician satisfaction and user acceptance. Optimization of care pathways will be measured by assessing the sustainability of AiCure use over 12 weeks (retention rates) and measuring illicit opioid use (urine drug screens) compared to historical data. Reliability and validity of AiCure will be measured by comparing AiCure adherence against pharmacokinetic data.

All participants will be requested to take each of their prescribed doses using the app. Participants will be able to download the app onto their own smartphone or will be provisioned a device at the start of the study. The data captured during the medication ingestion process will be automatically encrypted and stored on the participant smartphone and uploaded wirelessly to a cloud-based dashboard. If a participant is non-adherent (missed dose, incorrect dosage) or if suspicious behavior is detected, an automated alert will be sent to study staff via email or SMS to prompt immediate intervention. In addition, all participants will receive treatment as usual.

Detailed Description

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This study will employ a multi-site, single-arm design. A total of approximately 50-100 participants - patients stable for at least 2 weeks on their current opioid replacement medication - will be recruited for the study. All participants will receive their doctor's treatment-as-usual. Patients not currently prescribed Zubsolv® will be switched to Zubsolv®.

Study visits include a screening visit, one baseline visit (which ideally will occur between 7 and 14 days after the screening visit), and bi-weekly visits for the 12 weeks (six visits) following the baseline visit. During the baseline visit, participants will be trained on how to use the AiCure app. Training consists of a number of interactive training steps to teach the participant how to use the app correctly. Participants will be provided with three placebo tablets for the training.

Study participants will be reimbursed to cover their time and transportation costs in accordance with Institutional Review Board (IRB) guidelines. Participants will receive contingency management (CM) to reinforce regular use of the app. Orexo AB will provide the study drug, Zubsolv®, to all participants throughout the 12-week treatment duration.

For the length of the study, participants will be requested to take each dose of their prescribed Zubsolv® regimen using the AiCure app. Each medication administration event will be saved onto the participant's smartphone and encrypted data (including de-identified video and time and date of administration) will be automatically transmitted to the centralized dashboard. Research staff will have access to the dashboard to view real-time and detailed dosing histories for each participant. Access to the dashboard is roles-based and password-protected. If a participant does not dose using the AiCure app (misses/skips a dose), self-reports on the device or over the phone, or is tagged for suspicious behavior, the participant will receive a combination of automated SMS text messages and tailored SMS text messages / phone calls from research staff based on the pre-defined escalation protocol.

Conditions

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Opiate Addiction Medication Non-adherence Addiction Opioid Dependence

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

TREATMENT

Blinding Strategy

NONE

Study Groups

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AiCure monitoring and intervention

Participants will use the AiCure app to monitor ingestion of all prescribed doses of Zubsolv®.

Group Type EXPERIMENTAL

AiCure monitoring and intervention

Intervention Type DEVICE

Participants will use the AiCure app to monitor ingestion of all prescribed doses of Zubsolv®. If a participant misses a dose, takes an incorrect dose, or their data are flagged for suspicious activity, they will be contacted by research staff or the AiCure study team through automated SMS text or by phone.

Interventions

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AiCure monitoring and intervention

Participants will use the AiCure app to monitor ingestion of all prescribed doses of Zubsolv®. If a participant misses a dose, takes an incorrect dose, or their data are flagged for suspicious activity, they will be contacted by research staff or the AiCure study team through automated SMS text or by phone.

Intervention Type DEVICE

Other Intervention Names

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Automated DOT

Eligibility Criteria

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Inclusion Criteria

* Is a male or female at least 18 years of age.
* Has been on a stable dose of buprenorphine/naloxone for at least 2 weeks.
* Is willing to sign an agreement to return the AiCure provisioned device if not able to download AiCure app onto personal smartphone.
* Is willing to use the AiCure app properly each time they ingest their daily dose of buprenorphine/naloxone.
* Is willing to allow research staff (and good clinical practice-trained AiCure personnel) to contact them via the app or other specified means regarding issues related to medication non-adherence.
* Speaks and understands English well enough to participate in the informed consent process and the study assessments and procedures.
* Agrees to come for a research visit monthly for 12 weeks (three visits) after being accepted into the study and two times during screening/baseline.

Exclusion Criteria

* Is unlikely to remain under the care of their healthcare provider for the duration of the study.
* Appears to be incapable of learning the AiCure system.
* In the opinion of the investigator, is someone who should not be part of the study due to behavioral, mental, physical, or other issues.
* Is under court mandate to obtain treatment.
* Has a known allergy to any of the substances comprising the study medication.
* Is planning to be detoxified from Zubzolv during the course of the study.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Orexo AB

INDUSTRY

Sponsor Role collaborator

Montefiore Medical Center

OTHER

Sponsor Role collaborator

AiCure

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Alain Litwin, MD

Role: PRINCIPAL_INVESTIGATOR

Montefiore Medical Center

Adam Hanina, MBA, MPhil

Role: STUDY_DIRECTOR

AiCure

Locations

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Montefiore Medical Center

New York, New York, United States

Site Status

Countries

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United States

Other Identifiers

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HHSN271201300036C

Identifier Type: OTHER

Identifier Source: secondary_id

AIC-HHSN271201300036C-01

Identifier Type: -

Identifier Source: org_study_id

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