Funded Projects

There are currently no medications approved by the U.S. Food and Drug Administration to treat methamphetamine use disorder, even though risky patterns of methamphetamine use and overdose deaths have increased in recent years. Research using animal models shows that immune molecules that latch onto methamphetamine (anti-methamphetamine antibodies) show promise in blocking the effects of the drug. This project aims to identify a long-acting monoclonal antibody targeted to methamphetamine and conduct development and safety studies to prepare for future testing of the antibody treatment in humans.

To respond quickly and effectively to the constantly changing dynamics of the opioid crisis, public health agencies and organizations need timely state and local data to make critical decisions about where to allocate resources and target responses. This project creates the Rapid Actionable Data for Opioid Response in Kentucky system, a near real-time statewide surveillance system. This resource will combine data from multiple state agencies to provide actionable and timely information to support opioid overdose prevention, harm reduction, evidence-based treatment, and recovery services. The project will also develop user-driven reporting and visualization tools (mobile and web-based apps) that provide immediate access to near real-time community or state level data, reports, and visual analytics.

The Acute to Chronic Pain Signatures Program is developing a comprehensive data set that can be used to help predict which patients will recover from acute pain associated with surgery or injury and which ones will develop long-lasting chronic pain. This project will support an early career faculty member from a group underrepresented in biomedicine. The research will enhance skills development toward conducting and coordinating clinical pain research, generating omics datasets, advancing understanding of statistical methods, and other activities required for career development. 

Opioid dependence is a leading cause of premature illness and death. Previous research suggests that a protein called G-protein coupled receptor (GPR88) controls many addiction-relevant behavioral and physiological actions of opioids. This research study will validate GPR88 as a drug target for opioid use disorder as well as develop novel, brain-penetrant GPR88-binding molecules with properties optimized for treating opioid dependence. This research is an initial step toward the goal of developing GPR88-binding molecules as novel therapeutics to facilitate abstinence in people dependent on opioids.

Endometriosis is an often-painful disorder in which uterine tissue grows outside the uterus. Treatment of endometriosis-associated pain involves use of opioids in many women. This project aims to study a culprit gene thought to be involved with the disorder (capillary morphogenesis gene or CMG2) as a target for new, nonopioid pain medications. The research will also clarify how CMG2 s affects endometriosis-associated pain to test the effects of new medications for endometriosis pain.

Back pain, including low back and neck pain, is one of the most prevalent and disabling pain disorders. Treatment requires ongoing self-management, but most healthcare systems do not support self-care and instead focus on costly, provider-dependent therapies that remain inaccessible to many Black and Hispanic Americans and individuals with less education and income. This project will address these health disparities by developing a personalized self-management treatment program that includes pain education, mindfulness, cognitive behavioral therapy, and exercise – and make it available in community settings.

Patients choosing treatment with medications for opioid use disorder as part of their recovery pathway often have difficulties staying on these medications for extended periods of time. Currently, no established evidence-based interventions are available to help. This project will leverage the impact of two widely used recovery support services: peer recovery support services and recovery housing. Delivered by community-based peers with lived recovery experience, the intervention will include assertive outreach, which encourages people in recovery between episodes of care to continue treatment and return to care after treatment dropout and/or resumed opioid use. This research will also examine whether these services can enhance benefits offered by the supportive recovery housing living environment.

This research provides support to strengthen data management, data sharing, and data readiness efforts within the HEAL Initiative. This support further fosters collaboration among HEAL awardees and enables maximal data discoverability, interoperability, and reuse by aligning with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. It also provides an opportunity for existing HEAL Initiative award recipients to increase data “FAIR”-ness, participate in coordinated HEAL Initiative activities to build community around data sharing, and foster sustainability of HEAL Initiative digital assets.

Despite the need for non-opioid treatments for chronic pain, few alternative treatment approaches exist. Transcutaneous auricular neurostimulation (tAN) is a safe and effective treatment for pain during opioid withdrawal; however, researchers do not understand how tAN reduces pain, which limits its clinical use. A better understanding of how tAN affects neurophysiological processes to provide pain relief would likely expand tAN development and use. This interdisciplinary project will conduct research in both healthy adults and those with chronic pain to explain the neurochemical and neurophysiological mechanisms for tAN-based pain relief, and also help optimize treatments and their use.

This research provides support to strengthen data management, data sharing, and data readiness efforts within the HEAL Initiative. This support further fosters collaboration among HEAL awardees and enables maximal data discoverability, interoperability, and reuse by aligning with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. It also provides an opportunity for existing HEAL Initiative award recipients to increase data “FAIR”-ness, participate in coordinated HEAL Initiative activities to build community around data sharing, and foster sustainability of HEAL Initiative digital assets.

Shoulder pain occurs in many patients who are recovering from a stroke. In addition to impairments in the ability to move, persistent shoulder pain contributes to depression, and often reduces quality of life. Although the cause of post-stroke shoulder pain is complex and not completely understood, it is thought to arise in part to damage of muscles and surrounding connective tissues (myofascial tissues) in the shoulder. This project will use advanced medical imaging techniques to create biomarkers of that can reliably identify myofascial tissues. The research will then test the ability of these biomarkers to monitor, and ultimately predict treatment responses in patients with post-stroke shoulder pain in the context of a randomized controlled clinical trial.

Currently no medications are approved by the U.S. Food and Drug Administration to treat cocaine use disorder, which compromises cognitive function associated with achieving goals such as working memory, the ability to update information, and mental flexibility. This project will test whether  stimulating dopamine activity in the brain with the drug rotigotine (approved to treat Parkinson’s disease) is effective for treating cocaine use disorder. Past research has also shown that rotigotine can improve nerve cell and cognitive function in Alzheimer’s disease. This project will conduct a clinical trial to test whether treatment with rotigotine combined with cognitive behavioral therapy can reduce cocaine use in people with cocaine use disorder.

Monitoring and reporting substance use and substance use disorder is difficult to obtain in real-time using conventional methods. However, social media captures large amounts of data about substance use that are reported by diverse groups of people. Analysis of these data can provide population- or subpopulation-level insights, at low cost and in near real-time. This project aims to convert large amounts of social media data on substance use into actionable knowledge using advanced natural language processing and artificial intelligence approaches. The researchers will publicly release the aggregated statistics through a dedicated dashboard and provide user-friendly, open-source tools to determine trends and analyze disparities.