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Digital Therapeutic Development of Virtual Cognitive-Affective Training for Opioid Use Disorder

University of Utah Principal Investigator (PI) / Project Lead:

GARLAND, ERIC

Prime/Overall Principal Investigator (PI) / Project Lead:

Risa B. Weisberg, at BehaVR, Inc

Funding Organization:

National Institutes of Health, National Institute on Drug Abuse

RFP / FOA Number:

RFA-DA-19-019

Award Number:

R44DA053848

Project Period:

5/15/2021 – 7/31/2025

Total Funding:

 $2,779,659

Project Status:

In progress

 

Project Description:

Medications for opioid use disorder (MOUD) like buprenorphine are currently the most effective form of intervention for opioid use disorder (OUD); however, novel behavioral adjuncts are needed to remediate dysregulation in brain reward systems, enhance MOUD adherence, and prevent relapse. BehaVR, LLC will meet this need by translating an evidence-based biobehavioral treatment approach into an innovative digital therapeutic for OUD that will increase accessibility to services to improve the patient's chances of long-term treatment success.

 

Abstract:

The US is experiencing an opioid crisis, with an estimated 2.5 million Americans meeting full criteria for opioid use disorder (OUD). Medications for opioid use disorder (MOUD) like buprenorphine are currently the most effective form of intervention for OUD. In spite of the proven efficacy of MOUD, nearly half of people who begin a MOUD relapse within six months. As such, novel and efficacious behavioral adjuncts to MOUD are needed to improve treatment outcomes. Mindfulness-Oriented Recovery Enhancement (MORE), a cognitive-affective training intervention generated through a NIDA-funded treatment development process has shown significant promise, demonstrating therapeutic effects in four randomized controlled trials (RCTs) by reducing opioid use and misuse and modulating neurophysiological responses during drug cue-reactivity and natural reward processing. However, the MORE intervention requires significant human interaction and is therefore resource intensive. Further, in light of the COVID-19 pandemic, people with OUD may be reticent to engage in face-to-face interventions due to the risk of viral spread. To overcome these implementation barriers and increase access to treatment, the proposed project will develop and test a virtual reality version of the MORE intervention (MORE-VR) built on BehaVR LLC's VR existing, commercially available platform, the Dynamic eXperience Engine (DXE). The DXE uses machine learning to integrate biometrics into the VR experience to personalize addictions treatment, boosting patient engagement and optimizing the efficacy of clinical intervention. In Phase I, we will develop and test the MORE-VR prototype in a single arm clinical study of OUD patients receiving buprenorphine in an opioid treatment program (OTP), focusing on patient safety and engagement. If the prototype is perceived to have adequate usability and Net Promoter Scores, as well as to produce improvements in proximal measures of craving and affective state, the project will progress to Phase II. In Phase II, we will first develop the MORE-VR Minimal Viable Program using feedback from our Phase I study to optimize the intervention, and then conduct a RCT of MORE-VR vs. MOUD treatment as usual. Our robust and unbiased research design will triangulate clinical outcome measurement with biochemical verification of abstinence, ecological momentary assessments (EMA), and neurophysiological assessment of cue-reactivity. Further, we will integrate the MORE-VR Program into the OTP operational environment, building Fast Healthcare Interoperability Resources interfaces to ingest patient data from electronic medical records (EMRs) and to export patient utilization, assessment, and biometric data back to EMRs to create patient records and inform clinicians of patient progress. Activities in Phase I and Phase II will help define the regulatory pathway and establish regulatory feasibility to precede Food and Drug Administration (FDA) approval of the MORE-VR system as a Class II medical device. In sum, this project will translate an evidence- based biobehavioral treatment approach into an innovative digital therapeutic for OUD.

 

Outcomes:

Project currently in progress.

 

 

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Last Updated: 4/4/23