Using Artificial Intelligence To Monitor Medication Adherence in Opioid Replacement Therapy

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.