Funded Projects

Little is known about what motivates people to use multiple drugs. Understanding these factors is important for tailoring treatment services. Behavioral economic theory, which determines how much value individuals assign to drugs and potential negative consequences, provides a framework to understand the choices people make. This project will identify patterns, motivating factors, and long-term trajectories of opioid-involved polysubstance use behaviors and treatment. This research will use a range of methods to analyze substance use episodes as well as examine motives and preferences associated with polysubstance use behaviors and how they change over time. The findings will be combined into a toolkit to inform timing, type, and tailoring of interventions and policies to guide implementation of effective clinical strategies and policies for managing polysubstance use in healthcare systems.

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.

It is unclear if long-term use of opioids by head and neck cancer patients affects risk for depression, which is higher in this population compared to people without cancer. This knowledge could inform interventions such as increased opioid prescription safety or alternative pain management approaches and could thus help reduce the risk for depression-related outcomes. This project will use data from a national cancer database linked to Medicare claims and a Veterans Administration database to determine whether people with head and neck cancer that take opioid medications for more than 90 days have increased risk for new-onset or worsening depression or suicide death.

Although methadone is an effective treatment for opioid use disorder, many individuals drop out of treatment, putting them at risk of relapse and overdose. One of the factors associated with poor retention in methadone treatment is concurrent cocaine use. There is currently no effective medical treatment for cocaine use disorder. However, contingency management, in which individuals receive tangible rewards for desired behaviors such as abstinence, has been shown to be effective for cocaine use. This project will test the value of a digital therapy app, DynamiCare Health Contingency Management, in methadone treatment programs to promote treatment for polysubstance use.

First responders prevent many overdose deaths by providing life-saving resuscitation and giving naloxone to reverse an opioid overdose. This project will use a modeling approach to assess the impact of Good Samaritan Laws that protect people from certain criminal penalties if they call 911 to save an overdose victim by giving naloxone on overdose mortality. This research will develop and test a novel, scalable, telehealth platform that can be used at the time of an opioid overdose to link patients with access to medication for opioid use disorder, harm reduction services, and recovery support. The research will be informed by patient-outcome data.

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.

Few integrated treatments are available that simultaneously address the fundamental causes of chronic pain and opioid misuse/opioid use disorder and focus on well-being among individuals with chronic pain and opioid misuse/opioid use disorder. This research will inform development of patient-centered interventions that increase quality of life and engagement in valued activities, are culturally appropriate for use by diverse patient populations, and reduce stigma related to chronic pain and opioid misuse/opioid use disorder. The results of this project will be used to inform future research focused on developing mobile health treatments for individuals with chronic pain and opioid use disorder, and for developing culturally appropriate treatments for chronic pain and opioid use disorder in Hispanic/Latino individuals.

Pain in the muscles and surrounding connective tissues (myofascial pain) can affect many regions of the body and is a key component of chronic low back pain. Patients with chronic low back pain have a range of musculoskeletal problems perpetuating their pain. There is a significant clinical need to identify the components of myofascial pain in people with chronic low back pain. Advances in ultrasound technology have allowed researchers to identify several differences in muscle and connective tissues related to myofascial pain. This project will develop and validate an ultrasound-based biomarker signature for myofascial pain in the low back. This research will also refine the biomarker signature using advanced machine learning approaches, toward future testing in in a randomized controlled clinical trial.

Effective treatments for opioid use disorder need to address the complex needs of patients, which may include mental health problems and substantial chronic pain. This project will measure lifetime trauma experienced by men and women who take medication for opioid use disorder, as well analyze the association between types of trauma and symptomatic distress. The project will also explore whether an individual’s perceptions of sensations from inside their body (interoceptive awareness) affect emotional control and mental health. This research will fill knowledge gaps i critical to better understanding opioid use disorder treatment and relapse.

Many molecular gates known as ion channels control the flow of electrical signals to sensory neurons and are thus key mechanisms and targets for understanding and interrupting pain signals. Recent breakthroughs in structural and computational biology shave illuminated specific molecular shapes of ion channels, which permits the improved design and refinement of small, stable protein-like molecules (peptide antigens). These peptides can stimulate an immune response that can then be targeted with a bioengineered antibody to match the peptide antigen. This project will test bioengineered antibodies in a rat model of chemotherapy-induced peripheral neuropathy within a region of the rat spinal cord that transmits signals to and from the brain.

Current evidence indicates that chronic pain after a traumatic injury is influenced by the body’s response to stress. This project will conduct a comprehensive analysis of gene expression after traumatic stress exposure in a range of animal models in various body regions including the brain (amygdala, hippocampus, hypothalamus) and spinal cord, as well as nerves and immune cells throughout the body. These studies will be conducted in animals with no stress exposure as well as in animals treated with a molecule (FKBP51) known to block the stress response. This research will enhance understanding of how FKBP51 and post-injury stress affect pain processes.

The Interagency Pain Research Coordinating Committee has identified a need for organized opportunities for early-stage pain researchers to meet and learn from more experienced pain researchers and mentors – who are exiting the field at a faster rate than they are being replaced. This project will create a coordinating center for early-stage pain researchers, with an online networking platform to encourage interactions and collaboration among these scientists. The research will also develop a training curriculum and make it accessible to NIH funded, early-stage pain scientists.

Pain in the muscles and surrounding connective tissue (myofascial pain) is a significant and poorly understood health concern affecting hundreds of millions of Americans. There is a great need for tools to assess changes to myofascial tissues in individuals with chronic pain as well as to measure the effect of commonly used therapies. This project will use three imaging tools to look at differences between shoulder tissue in people with myofascial pain compared to those without pain. Using a machine learning approach, this research aims to develop a biomarker signature for myofascial pain, which will be evaluated in a randomized controlled clinical trial based on its ability to predict patient responses to myofascial pain treatments.