Funded Projects

This study will challenge current clinical approaches to managing the pregnant woman with opioid use disorder. Dosing of buprenorphine (BUP) in pregnant women is based on studies in non-pregnant subjects, which suggests that symptoms of withdrawal occur when plasma BUP concentrations are < 1ng/ml. No such data exist for pregnant women, but this is a prerequisite for defining an appropriate dosing regimen of BUP in pregnant women. We will define this threshold by monitoring women undergoing mild, medically directed withdrawal. The Clinical Opioid Withdrawal Scale score and the Finnegan score for NAS are key to defining when withdrawal occurs and thus dictate treatment in mother and baby. Neither scoring system is based on plasma BUP concentrations and thus, may not reflect true opioid withdrawal. This proposal aims to develop physiologic-based scoring systems that refine the accuracy of diagnosis and optimize treatment.

One novel approach to address the opioid crisis is predicting the likelihood of retention in treatment for opioid use disorder (OUD) by assessing someone?s risk of early departure from treatment. Current methods rely on providers intuition to identify when an individual is at risk of leaving treatment early in order to intervene. This intervention, when it happens, often comes too late. Mobile health (mHealth) and Machine Learning (ML) predictive analytics offer a new opportunity to personalize OUD treatment, improve retention in OUD care, and mitigate the risk of relapse and overdose episodes. Project Motivate will combine physiological and behavioral data from disparate sources in order to predict when an individual is at risk of early departure from OUD treatment. If successful, results of the study will save lives, and lower medical costs, municipal emergency response costs, recidivism, workplace accidents, lost workplace productivity and costs to families.

Identifying optimal chronic low back pain treatments on a patient-specific basis is an important and unresolved challenge. Tailoring interventions according to patient movement characteristics is one option. This research is characterizing patients based on spinal motion during functional tasks and daily activities and will use artificial intelligence to objectively characterize motions of the spine during both clinical assessments and day-to-day life. During clinical assessments, participants will be asked to perform functional tasks while wearing motion sensors. Data collected from the sensors will be used to identify tasks of interest, such as activities of daily living and aberrant/painful motions. An artificial intelligence approach will then interpret data collected continuously during assessment in patients’ homes over a 7-day testing period. Ultimately, this data could be used to help clinicians tailor treatments that are responsive to a patient’s real-world functional impairments.

Medications have proven to be effective for treating opioid use disorder (OUD). Increasing accessibility to buprenorphine provides an opportunity for many with OUD to benefit from its proven effectiveness. Adherence to medication-based treatments however is low, in part because of the stigma associated with use of this and other effective drugs and as such, leads to inadequate treatment and poor outcomes. This study aims to understand the effects of stigma on patient engagement, retention, and outcomes of buprenorphine treatment. Knowledge drawn from the HIV Stigma Theory and tools developed to reduce HIV associated stigma will be used to assess OUD stigma and to develop interventions to reduce it in the context of buprenorphine treatment. The study findings may provide resources to address stigma and thus maximize treatment adherence among those affected by OUD.

The Appalachian Node of NIDA Clinical Trials Network (CTN) will address clinical research questions that arise from Central Appalachia, an epicenter of the current opioid epidemic. Its rural geography, culture of independence, strained economy, and lack of access to substance use treatment have all contributed to the epidemic. The three aims of the node are to (1) conduct multi-site trials that address the current opioid crisis, with an emphasis on conducting studies among rural and other underserved populations; (2) propose studies to test innovative uses of existing resources to implement evidence-based practices that will extend state-of-the-art care into resource-poor regions, both rural and urban; and (3) disseminate CTN findings to regional payers and policymakers, practitioners, and the community. Proposed studies built on the work of node investigators include “Serious Bacterial Infections Related to Injection Drug Use: Quality Metrics and Intervention” and “Pharmacist-Assisted Buprenorphine Treatment,” among others.

The research team developed an in vitro multi-component joint on a chip (microJoint), in which engineered osteochondral complexes, synovium, and adipose tissues were integrated. This study will introduce sensory innervation into the microJoint and a neuron-containing microfluidic ally will be developed to innervate the microJoint. The osteoarthritis (OA) model will be created in the Neu-microJoint system. The research team will assess activation and/or sensitization of nociceptive afferents with electrophysiology, as well as neurite outgrowth. They will mechanically insult the Neu-microJoint and assess the emergence of “pain” in response to prolonged mechanical stress. Researchers will assess the impact of drugs used clinically for management of OA on OA models and will then use “omic” approaches to identify new biomarkers and therapeutic targets. Researchers will assess the impact of opioids—which they hypothesize will increase the rate of joint degeneration and potentiate the release of pain-producing mediators—on neural activity in the presence and absence of joint injury, as well as the integrity of all joint elements.

While the mu opioid receptor (MOR) antagonist naloxone has proven invaluable as an opioid overdose antidote, naloxone suffers from a very short duration of action (half-life is approximately 1 hour) and has been found to be less effective against newer, long-acting opioids, including fentanyl (half-life is approximately 7–10 hours). This leads to a highly lethal and increasingly prevalent phenomenon known as “renarcotization,” wherein an overdose patient revived with naloxone can re-enter an overdose state from residual fentanyl in the body. Thus, there is a critical need to develop a long-acting MOR antagonist formulation that can address renarcotization by providing multi-hour protection. The goal of this project is to reformulate naloxone using FDA-approved microencapsulation technology into a long-acting injectable (LAI) that can provide 12–24 hours of sustained antagonist activity in vivo. It will employ a proprietary Computational Drug Delivery™ software, called ADSR™, to perform in silico formulation optimization as well as to predict its in vitro dissolution and in vivo pharmacokinetic behavior.

Severe tissue injury generates central sensitization. Latent sensitization (LS) is a silent form of central sensitization that persists after tissue has healed and overt signs of hyperalgesia have resolved. Pain remission during LS is likely maintained by tonic opioid receptor activity. The opioid receptor inverse agonist, naloxone, can reinstate experimental pain when delivered one week after the resolution of secondary hyperalgesia following first degree thermal injury. Our aims are to test: 1) the hypothesis that burn or surgery triggers LS and long-term opioid analgesia in humans; 2) the hypothesis that mu-opioid receptor (MOR) constitutive activity (MORCA) receptors by opioid peptides maintains endogenous analgesia and restricts LS to a state of pain remission; 3) the extent to which MORs inhibit neural activity in the DH and synaptic strength in presynaptic terminals of primary afferent nociceptors during LS; and 4) whether MORs inhibit spinal NMDA receptor subunits to block pain during LS.

Recently, concerns have been voiced that medications to treat opioid use disorder (OUD) may contribute to dental problems, including cavities and tooth loss. These concerns may contribute to barriers preventing use of these medications. A better understanding of the effects of these medications on oral complications is critical. This project will use national databases to link dental, medical, and pharmacy claims data for Medicaid- or commercially-insured new users of various medications for OUD to determine and compare oral health outcomes. The project will also examine the perspectives and experiences of people with OUD on oral health.

Multiple factors, including inflammation contribute to chronic low back pain. Inflammation is mediated by numerous genes. The study aims to determine how variations in the genes encoding key inflammatory mediators impact the response of patients with chronic low back pain to physical therapy treatment. Gene variations that are known to be linked to inflammation and pain will be tested against their possible association on physical therapy treatment outcomes, to inform clinical decisions on optimal care. This study will support training in clinical research on pain within the context of the HEAL BACPAC Mechanistic Research Center. It will provide resources for a research project relevant to the parent grant and the career development of an individual in the field of pain research. The ability to identify a set of genetic variations and classify patients according to treatment response might enable use of DNA testing as a screening tool for targeted treatments for patients with CLBP.

Chronic pain is a debilitating condition for which there is a pressing need for safe, effective treatments. Neurostimulation therapies that target nerve structures such as the dorsal root ganglion (DRG) and the spinal cord, have shown promising results for treating chronic pain, but researchers don’t know how they work. This project focuses on two prevailing models used to explain the therapeutic effects of neurostimulation: the gate-control model in which pain signals are blocked from reaching the brain and the T-junction filtering model in which pain signals are blocked from reaching the spinal cord. Strategies will include innovative behavioral, electrophysiological, imaging, and computational modeling techniques. The results of these studies will help explain why neurostimulation therapies work and potentially offer new treatment strategies for improved pain relief.

Rates of neonatal abstinence syndrome have reached a staggering 6.5 per 1,000 births nationwide, creating an urgent need to identify how in-utero exposure to opioids and associated risk factors influence the developing brain. A multidisciplinary team will address these challenges in Oregon, a state particularly hard hit by the opioid epidemic. Through linking sites, the impact of the Phase I project is enhanced and will provide critical information to support a national-level effort for Phase II of the HEALthy Brain and Child Development Study. Aim 1 will develop, implement, and evaluate innovative recruitment and retention strategies for high-risk populations. Aim 2 will address anticipated challenges of the planned Phase II study by implementing and evaluating a multi-site, standardized research protocol including multimodal MRI of placenta, fetus, neonate, and 24-month-old brain; biospecimen collection; and assessment of substance use and other key domains. Aim 3 will evaluate data acquisition, processing, and statistical considerations to maximize data quality, usability, and integration across sites.