Funded Projects

The HEAL Initiative is establishing a HEAL Data Ecosystem to help investigators manage and share HEAL-generated data, and quickly and efficiently disseminate HEAL results broadly to stakeholders. The HEAL Platform, built by the University of Chicago, will enable broad sharing of HEAL data by linking data stored in various locations, annotated and curated to various extents, to one central interface where studies, data, and digital assets can be discovered and accessed via metadata query. The Platform will also provide secure workspaces so that under appropriate conditions, data can be pulled from disparate repositories and computed on in the same cloud space, using tools and analytic suites provided within. The Platform team will collaborate closely with the HEAL Data Stewardship Group (Renascence Computing Institute at the University of North Carolina Chapel Hill and RTI, International) to meet the needs and goals of the HEAL Data Ecosystem.

There is increasing evidence that satellite glial cells (SGCs) surrounding neurons in the dorsal root ganglia modulate sensory processing and are important for chronic pain. Tissue inhibitor of metalloproteinase 3 (TIMP3) signaling occurs in SGCs and has unique plethoric functions in inhibiting matrix metalloproteinases, the tumor necrosis factor-?-converting enzyme, and the vascular endothelial growth factor receptor 2, all of which have been implicated in inflammation and pain. This study will test the hypothesis that expression of TIMP3 in SGCs is critical for the neuroimmune homeostasis in sensory ganglia, as well as for the development of pain, and therefore could be a novel therapeutic target for acute and chronic pain. Given the expression of TIMP3 in human SGCs and the strong validation of multiple small molecules targeting TIMP3 signaling, including FDA-approved drugs, in various animal models of pain and in cultured human SGCs, the successful completion of this research project has a high likelihood of rapid translation into therapeutic testing in inflammatory pain conditions that are a risk for opioid abuse.

The growing opioid use epidemic in the U.S. has been associated with a significant increase in the prevalence of pregnant opioid-dependent women and neonatal abstinence syndrome, which is associated with adverse health effects for the infant and with costly hospitalizations. Maintenance with sublingual (SL) buprenorphine (BUP) is efficacious for opioid use disorder but has disadvantages that may be heightened in pregnant women, including the potential for poor adherence, treatment dropout, and negative maternal/fetal effects associated with daily BUP peak-trough cycles. Extended release (XR) formulations may address some of these disadvantages. The primary objective of CTN-0080 is to evaluate the impact of treating opioid use disorder in pregnant women (n = 300) with BUP-XR, compared to BUP-SL, on maternal-infant outcomes. Other objectives include testing a conceptual model of the mechanisms by which BUP-XR may improve maternal-infant outcomes, relative to BUP-SL; determining the economic value of BUP-XR, compared with BUP-SL, to treat OUD in pregnant women; and evaluating the impact of BUP-XR, relative to BUP-SL, on neurodevelopment when the infant/child is approximately 12 and 24 months of age. Ultimately, this study will help in increasing access to treatment as well as provide quality care for pregnant/postpartum women.

The growing opioid use epidemic in the U.S. has been associated with a significant increase in the prevalence of pregnant opioid-dependent women and neonatal abstinence syndrome, which is associated with adverse health effects for the infant and with costly hospitalizations. Maintenance with sublingual (SL) buprenorphine (BUP) is efficacious for opioid use disorder but has disadvantages that may be heightened in pregnant women, including the potential for poor adherence, treatment dropout, and negative maternal/fetal effects associated with daily BUP peak-trough cycles. Extended release (XR) formulations may address some of these disadvantages. The primary objective of CTN-0080 is to evaluate the impact of treating opioid use disorder in pregnant women (n = 300) with BUP-XR, compared to BUP-SL, on maternal-infant outcomes. Other objectives include testing a conceptual model of the mechanisms by which BUP-XR may improve maternal-infant outcomes, relative to BUP-SL; determining the economic value of BUP-XR, compared with BUP-SL, to treat OUD in pregnant women; and evaluating the impact of BUP-XR, relative to BUP-SL, on neurodevelopment when the infant/child is approximately 12 and 24 months of age. Ultimately, this study will help in increasing access to treatment as well as provide quality care for pregnant/postpartum women.

Community pharmacies are optimal—yet underutilized—settings for identifying individuals with opioid use disorder (OUD) and increasing their access to treatment. Approximately 93 percent of individuals in the U.S. live within 5 miles of a community pharmacy. The most common opioid-related tool available to pharmacists is the prescription drug monitoring program (PDMP), which provides highly limited information and support for clinical decision making. Appriss Health, the largest U.S. PDMP vendor, covering 42 states, has developed an opioid risk measure, the NarxScore. This study will clinically validate the NarxScore metric and identify high, moderate and low opioid risk thresholds to inform OUD care management within urban and rural community pharmacies. This is a prospective cross-sectional comprehensive OUD risk and behavioral/physical health survey administered electronically with patients (n = 1,523) filling opioid medications in urban/rural community pharmacies in Ohio (pharmacy sites: n = 12) and Indiana (pharmacy sites: n = 3), states that continue to have disproportionately high rates of overdose and opioid prescribing. Correlation, regression and kappa statistics will be calculated for validation; receiver operating curves with sensitivity/specificity values will be employed for threshold identification (with >95 percent power to detect an area of 0.7 under the curve value).

Clinical decision support tools help clinicians make treatment decisions based on routinely collected data and offer a promising strategy to implement evidence-based practices for safe and effective pain management. This project will use clinical decision support tools embedded into electronic health records to help healthcare providers make treatment decisions that align with opioid prescribing guidelines from the Centers for Disease Control and Prevention (CDC). The project will also use information from prescription drug monitoring programs, insurance claims, and mortality data to evaluate patient outcomes. This research will evaluate how prescribing practices that align with CDC guidelines affect patient outcomes and whether clinical decision support tools provide an advantage over standard care practices for pain management.

Currently available treatments for opioid use disorder (OUD) are insufficient for many patients. Novel compounds that can promote alterations in brain connections (i.e., neural plasticity) possess enormous potential for improving substance use disorder (SUD) treatments. Psychedelic compounds induce neural plasticity and can elicit long-lasting, beneficial impacts on a wide variety of SUDs. However, these compounds have significant side effects, including hallucinations and cardiotoxicity. Researchers have developed a novel, synthetic derivative of the psychedelic ibogaine, called tabernanthalog, that does not have these side effects. This compound has demonstrated both short- and long-term therapeutic effects in a preclinical model of OUD. This research study will determine the molecular and neural mechanisms through which tabernanthalog affects opioid seeking. It will also evaluate whether the effects are specific to opioids and do not alter response to natural rewards and will examine the efficacy of tabernanthalog in a preclinical model of comorbid opioid and alcohol use disorder.

The project will address gaps in both risk identification and clinical management by utilizing comprehensive clinical data from a mature health information exchange containing more than 2.3 million patients across the spectrum of clinical care (hospitals, primary care, specialty care, community health centers, urgent care) to develop a statistically robust method to measure suicide risk associated with prescription opioid use. First, the team will couple data fusion techniques with machine learning-based approaches in identifying the clinical and demographic characteristics associated with elevated risk of suicidal behavior among prescription opioid users. Second, the team will develop clinical profiles of patients with higher risk of suicidal behavior associated with prescription opioids, and to incorporate these profiles in a clinical decision support platform that can be used for identification and intervention at the point of care. The clinical decision support tool developed under this proposal will provide a generalizable platform that could be extended to other more conventional opioid related outcomes such as OUD and overdose.

Opioids have been significantly over-prescribed and are associated with numerous deaths, resulting in the nation’s current opioid crisis. The FDA recently approved the ?2 adrenergic agonist lofexidine as a non-addictive, non-opioid treatment for opioid use disorder (OUD), but there is a continued, urgent need to develop additional pharmacological alternatives to address both pain and OUD. The psychoactive, natural product, Mitragyna speciosa (kratom), has triggered significant interest in this space because Mitragynine, its main alkaloid, can interact with both mu opioid and ?2 receptors, offering a totally new approach for treating OUD. This project involves the synthesis and research of a series of Mitragynine analogs to better understand the pharmacological mechanisms that underlie Mitragynine’s opioid and adrenergic activities. If successful, this project will result in templates for the design of novel opioid receptor ligands. This advance would greatly improve the knowledge of interactions of these structurally novel compounds with opioid receptors and facilitate the development of these ligands as treatments for OUD.

A major barrier to developing new pain treatments has been the absence of infrastructure to facilitate well-designed and carefully conducted clinical trials to test the efficacy of promising treatments. The UF Health Specialized Clinical Center Network will include UF Health as “hub” and statewide partners serving as spokes as part of the EPPIC Network. The University of Florida (UF) has the capability to reach more than 50% of the population of Florida, the third most populous state of the United States, and the capacity to successfully enroll patients with varying pain conditions into clinical trial protocols through its hub and spoke infrastructure as part of EPPIC-Net.

Buprenorphine is commonly used in medication-assisted treatment of opioid use disorders. The U.S. Food and Drug Administration recently issued a warning that the drug may lead to serious tooth damage in some patients. It is thought that high concentrations of the drug in saliva may contribute to tooth damage and decay. This project will use a mouse model of dental caries to explore the mechanism leading to high buprenorphine concentrations in saliva and examine ways to reduce concentrations in the mouth but not the rest of the body; it will also examine buprenorphine’s effects on the bacteria that lead to caries development.

Health services for the treatment of opioid use disorder (OUD) are fragmented in west Chicago, an epicenter for overdose deaths. This project will develop a data-driven opioid response plan involving key partners. These include local health departments, community organizations, health care systems, and people with lived experience. The research will develop a digital screening tool for OUD that can be used in hospitals and their emergency departments. The tool will be built from machine learning of data from electronic health records, the prescription drug monitoring program, and patient-reported measures. The research will test the value of the screening tool for connecting people to treatment and preventing fatal overdoses mortality in local neighborhoods.