Funded Projects

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Project # Project Title Research Focus Area Research Program Administering IC Institution(s) Investigator(s) Location(s) Year Awarded
2R44DA051289-02
Wearable Sensor for Opioids Detection Based on Electrochemical Sensor Array Integrated with Bluetooth Device Cross-Cutting Research Small Business Programs NIDA EMITECH, INC. LEVITSKY, IGOR A Fall River, MA 2022
NOFO Title: HEAL Initiative: America’s Startups and Small Businesses Build Technologies to Stop the Opioid Crisis (R43/R44 - Clinical Trial Optional)
NOFO Number: RFA-DA-19-019
Summary:

This project will develop and refine a wearable device (forearm bracelet) designed to rapidly sense and report the presence of opioids in the wearer. This research will optimize this device to provide ultra-high sensitivity, enhanced drug specificity, long-term durability, low power consumption, and cost-effective production. The findings could support a path toward commercialization of this new device.
1UH2AR076723-01
Wearable nanocomposite sensor system for diagnosing mechanical sources of low back pain and guiding rehabilitation Clinical Research in Pain Management Back Pain Consortium Research Program NIAMS BRIGHAM YOUNG UNIVERSITY BOWDEN, ANTON E Provo, UT 2019
NOFO Title: HEAL Initiative: Back Pain Consortium (BACPAC) Research Program Technology Research Sites (UH2/UH3 Clinical Trial Optional)
NOFO Number: RFA-AR-19-028
Summary:

Chronic low back pain (cLBP) is recurrent and often nonresponsive to conservative treatments. Biomechanists, physical therapists, and surgeons each utilize a variety of tools and techniques to assess and interpret qualitative movement changes to understand potential mechanical and neurological sources of low back pain and as critical elements in their treatment paradigm. However, objectively characterizing and communicating this information is currently impossible, since clinically feasible (i.e., cost-effective, objective, and accurate) tools and quantitative benchmarks do not exist. This research addresses the challenge to improve cLBP outcomes through the use of unique, inexpensive, screen-printable, elastomer-based, nanocomposite, piezoresponsive sensors, which will be integrated into a SPInal Nanosensor Environment (SPINE) sense system to measure lumbar kinematics and provide an objective, quantitative platform for diagnosis, monitoring, and follow-up assessment of cLBP.
3UG1CA189824-07S2
Wake Forest NCORP Research Base Clinical Research in Pain Management Pain Management Effectiveness Research Network (ERN) NCATS WAKE FOREST UNIVERSITY HEALTH SCIENCES LESSER, GLENN J Winston-Salem, NC 2020
NOFO Title: Notice of Special Interest to Encourage Eligible NIH HEAL Initiative Awardees to Apply for Administrative Supplements to Promote Training in Clinical Research on Pain (Admin Supp ? Clinical Trial Not Allowed)
NOFO Number: NOT-NS-20-044
Summary:

Pain is one of the most common symptoms in cancer patients and one least likely to be adequately treated. It is particularly common in advanced cancer, affecting an estimated 64% of patients with advanced disease. Pain treatment guidelines state patients should have access to behavioral pain interventions that educate them about pain and teach them skills for managing it. The parent grant will evaluate the effectiveness of an evidence based pain management intervention called ?Pain Coping Skills Training? in a web based format for patients with advanced cancer. This supplement will provide support for a training opportunity that aligns with the goals of the parent grant and includes community outreach and engaging underserved populations in clinical research.
3UG1CA189824-08S1
Wake Forest NCORP Research Base Clinical Research in Pain Management Pain Management Effectiveness Research Network (ERN) NCI WAKE FOREST UNIVERSITY HEALTH SCIENCES LESSER, GLENN J Winston-Salem, NC 2021
NOFO Title: Notice of Special Interest to Encourage Eligible NIH HEAL Initiative Awardees to Apply for PA-20-222: Research Supplements to Promote Diversity in Health-Related Research (Admin Supp - Clinical Trial Not Allowed)
NOFO Number: NOT-NS-20-107
Summary:

Cancer remains a leading cause of death among Hispanic/Latino populations in the United States. Compared with non-Hispanic Whites, Hispanic/Latino cancer patients are more likely to experience poor quality of life and inadequate cancer-related care, including less effective pain relief and poor patient‒provider communication. Additionally, Hispanic/Latino populations often have inadequate access to pain treatment, due to both social disparities and language barriers. However, most behavioral and psychosocial oncology research continues to focus on non-Hispanic Whites, and empirically validated and effective treatment interventions, particularly psychosocial interventions, are often not available in Spanish. This project will generate a Spanish-language version of the painTRAINER internet-based coping skills training program that is both linguistically and culturally sensitive and will evaluate its feasibility and acceptability in Hispanic/Latino patients with persistent cancer-related pain.
R24DA055306-01
Wake Forest IMPOWR Dissemination Education and Coordination Center (IDEA-CC) NIDA Wake Forest University Health Sciences ADAMS, MEREDITH C B Winston-Salem, NC 2022
NOFO Title: Administrative Supplements to Support Collaborations to Improve the AI/ML-Readiness of NIH-Supported Data
NOFO Number: NOT-OD-22-067
Summary:

This research is intended to create multidisciplinary team science collaborations to develop effective interventions, best models of care for delivery of services, and sustainable implementation strategies for access to quality care for complex patients with chronic pain and opioid use disorder or opioid misuse. To allow comparison and analysis of data created in nine unique clinical trials funded across four centers, common data elements (CDEs) were selected to assess all aspects of a patient’s condition and experience. The purpose of this project is to make the IMPOWR CDE data more FAIR (Findable, Accessible, Interoperable, Reusable) by building a tool that will automate the mapping/conversion of HEAL-related data to the Observational Medical Outcomes Partnership data model that allows for systematic analysis of data from different databases. Upon completion, this tool would be shared with the HEAL research community as a new resource to enable broader harmonization and secondary data analysis.