Funded Projects

Among the most common symptoms experienced by individuals suffering with opioid use disorder (OUD) are severe sleep and circadian disruptions. The relationship between opioid dependence and sleep and circadian systems is not well understood. A circadian-dependent mechanism has been shown to modulate fentanyl reward-related behaviors in the nucleus accumbens (NAc). The study team will use a combination of behavioral, slice electrophysiology, and molecular approaches to 1) investigate the role of the circadian transcription factor NPAS2 in medium spiny neurons with dopamine 1 (D1R-MSNs); 2) assess the impact of fentanyl on synaptic plasticity at D1R-MSNs and investigate whether NPAS2 mediates the potentiation of excitatory synapses at specific diurnal phases; 3) elucidate the cell-type-specific NPAS2-dependent transcriptional mechanisms of fentanyl-seeking and relapse behaviors; and 4) investigate whether NPAS2 rescue and buprenorphine medication-assisted treatment (MAT) improve fentanyl-induced sleep disturbances. This study will define the role for circadian-dependent transcriptional mechanisms and uncover the therapeutic potential of NPAS2 for opioid dependence and relapse.

Rapid technological advances are leading to field-deployable mobile sensing devices that can quantify complex dynamics of key physical, biological, behavioral, social, and environmental factors, enabling us to understand causation in complex disorders. Significant new investment is needed to develop and disseminate data analytics tools. The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) will generate generalizable theory, methods, tools, and software to address major barriers to processing complex mobile sensor data and its use in biomedical knowledge discovery and just-in-time care delivery. We will develop and implement a standards-based, interoperable, extensible, and open-source big data software platform for efficient implementation of MD2K data analytics. MD2K will demonstrate the feasibility, utility, and generalizability of this approach by implementing the entire MD2K data analytics system in the context of two biomedical applications: reducing relapse among abstinent daily smokers and reducing readmission among congestive heart failure patients

Given recent increases in co-use of opioids and methamphetamine, there is a dire need for novel treatment strategies that prevent relapse to drug use in both opioid use disorder (OUD) and methamphetamine use disorder (MUD). The localization of certain receptors for the neurotransmitter glutamate—metabotropic glutamate receptor subtypes 2 and 3 (mGlu2/3)—and the mechanism through which they transmit signals, strongly suggest that activation of both of these receptors will effectively treat multiple symptoms that contribute to relapse, such as responsiveness to drug cues, physical withdrawal symptoms, neuroinflammation, and sleep disturbances. This project seeks to evaluate molecules that can activate mGlu2/3 receptors without binding to the same site as glutamate (i.e., positive allosteric modulators) as a novel pharmacological treatment for preventing relapse to OUD. The research also will examine the potential of such modulators for treating MUD.

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.

There is a significant treatment gap between patients diagnosed with OUD and those who seek treatment, and only a small proportion of those seeking treatment receive MOUD. Primary care is the most common point of health care contact in the U.S. and is an important venue to address stigma, improve access to treatment and improve quality of care. Over the past decade, electronic health record (EHR)-linked Web-based point-of-care clinical decision support (CDS) systems designed to improve quality of chronic disease care have become increasingly sophisticated and successful. A Web-based and EHR-integrated OUD CDS system to offer expert guidance to primary care providers (PCPs) on the diagnosis and management of OUD was developed and piloted. This project will implement the OUD clinical decision support system in three large diverse health care systems and randomize a minimum of 30 clinics to receive the OUD-CDS intervention or usual care (UC). The project will evaluate the impact of OUD CDS on practice process measures and patient outcomes. The study will also prepare for scalability and dissemination by evaluating facilitators and barriers to implementation, determining the costs of implementation and maintenance and assessing the short-term cost impacts of the OUD-CDS.

There is a significant treatment gap between patients diagnosed with OUD and those who seek treatment, and only a small proportion of those seeking treatment receive MOUD. Primary care is the most common point of health care contact in the U.S. and is an important venue to address stigma, improve access to treatment and improve quality of care. Over the past decade, electronic health record (EHR)-linked Web-based point-of-care clinical decision support (CDS) systems designed to improve quality of chronic disease care have become increasingly sophisticated and successful. A Web-based and EHR-integrated OUD CDS system to offer expert guidance to primary care providers (PCPs) on the diagnosis and management of OUD was developed and piloted. This project will implement the OUD clinical decision support system in three large diverse health care systems and randomize a minimum of 30 clinics to receive the OUD-CDS intervention or usual care (UC). The project will evaluate the impact of OUD CDS on practice process measures and patient outcomes. The study will also prepare for scalability and dissemination by evaluating facilitators and barriers to implementation, determining the costs of implementation and maintenance and assessing the short-term cost impacts of the OUD-CDS.

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. 

The objective of the Early Phase Pain Investigation Clinical Network (EPPIC-Net) and EPPIC- Net initiatives is to rapidly and efficiently translate advances in the neurobiology of pain into treatments for people with chronic and acute pain, conditions associated with a significant burden to both patients and society. The Clinical Coordinating Center (CCC) for EPPIC-Net will promote and facilitate, from initial conception through final analysis, clinical trials in adult and pediatric populations with acute or chronic pain by providing efficient methodological, organizational, and logistical support. The EPPIC-Net-CCC will adopt and establish processes aimed at dramatically increasing the efficiency of multicenter clinical trials, improving the overall quality of clinical trials, promoting patient recruitment and retention as well as increasing the number of clinical investigators and research staff well trained and passionate about leading and conducting multicenter clinical trials.

There are alarming rates of substance abuse and diversion in hospitals, with multiple studies finding that roughly 10% of our nation’s nurses, anesthesiologists, and pharmacists are currently diverting drugs in their workplaces. Diversion continues even though most hospitals already lock addictive drugs in Automated Dispensing Machines (ADMs) and run monthly “anomalous usage” computer reports to try to detect diversion. This SBIR project will research mechanisms to detect when health care workers (HCWs) in hospitals steal or “divert” legal drugs, either to abuse themselves or to illegally sell to others, by building a computer system with (a) automated data feeds from multiple existing hospital computer systems and (b) advanced analytics to flag potential diversion for investigation. This research has the potential to reduce injuries to HCWs who are becoming addicted, destroying their careers, jeopardizing their patients’ safety, and increasingly dying from drug diversion overdoses.

There is a need for pharmacologic treatment options for opioid use disorder (OUD) that do not pose addiction liability and do not require complete withdrawal from opioids prior to treatment. Nonclinical studies support a role for the orexin system in drug seeking; compounds that selectively block signaling at the orexin-1 receptor (OX1R) reduce drug use. C4X3256, a non-opioid, highly selective OX1R antagonist, has a long residence time at the OX1R along with reduced intravenous self-administration and cue-induced reinstatement in animal models of nicotine addiction, suggesting it could be an addiction treatment. Proposed studies will move C4X3256 from preclinical development through Phase I testing in subjects with OUD. The clinical, preclinical, and supporting pharmaceutical development studies proposed will allow C4X3256 to move to Phase II studies.

The research team has developed ultrasonic drug uncaging for neuroscience, in which neuromodulatory agents are uncaged from ultrasound-sensitive biocompatible and biodegradable drug-loaded nanocarriers. This project will clinically translate ultrasonic ketamine uncaging for chronic pain therapy. In the UG3 phase, the research team will scale our nanoparticle production processes to human scales and adapt them to pharmaceutical standards. In the UH3 phase, they will complete a first-in-human evaluation of the safety and efficacy of ultrasonic ketamine uncaging by quantifying how much ketamine is released relative to the ultrasound dose and assessing whether the uncaged ketamine can modulate the sensitivity and affective response to pain, in patients suffering from chronic osteoarthritic pain. This project aims to yield a novel, noninvasive, non-opioid therapy for chronic pain that maximizes the therapeutic efficacy of ketamine over its side effects, by targeting its action to a critical hub of pain processing.

Spinal cord stimulation (SCS) has been shown to provide effective relief for most people with chronic pain and eliminated the need for opioid therapy in more than half of those treated. However, traditional SCS approaches have encountered problems when glial cells coat the stimulation electrodes that distance the device from targeted neurons. This project will develop a novel hybrid Closed Loop Omnidirectional Neuromodulation with Electromagnetic fields (CLONE) system that is combined with magnetic-based stimulation to overcome glial coating of SCS electrodes, better target neurons in dorsal spine tissue, which may lead to better treatment of chronic neuropathic neck and low back pain.

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.