Funded Projects

Sober Grid™ has developed a smartphone-based mobile application currently in use by more than 120,000 individuals worldwide who are in, or seeking, recovery from drug and alcohol addiction. The “Grid,” as it is known, is a mobile-based, social recovery community providing rapid context-specific peer support, efficient help seeking, motivational enhancement exercises, and member ratings of support content—all aimed to prevent relapse. The overarching goal of this phase II project is to extend the current capabilities of the Sober Grid app to achieve a comprehensive social recovery support app featuring intelligent, context-appropriate resource matching and 24/7 rapid-response peer coaching that is effective in reducing disordered substance use and is cost-effective. This projects tests whether providing this functionality to high-risk members will be acceptable, feasible, increase access to and engagement with resources, and have a positive effect in increasing time to relapse and days of consecutive abstinence.

There is an urgent and unmet clinical need for a reliable technology to prevent maternal opioid use relapse and neonatal opioid withdrawal syndrome (NOWS) in their infants. This project aims to assess risk for these outcomes based on individual genetic and clinical factors. The research will expand previous studies of genetic and clinical predictors of opioid-related adverse outcomes. The goal is to develop a risk predictor algorithm and software tool for use in an electronic health record, toward personalized risk assessment and prevention of maternal relapse and NOWS. 

Lumbar spinal surgery, an increasingly common surgery in adults with severe chronic back pain, is associated with acute post-surgical pain, costly postoperative opioid-related adverse effects, long hospital stays, high-risk for chronic post-surgical back pain, and persistent opioid use and dependence. Each individual responds differently to opioids based on their unique genetic and clinical factors, and the current trial-and-error approach to opioid use and prescribing promotes excessive opioid use, costly adverse outcomes, and poor surgical pain management. To address this issue, this research project will develop a preoperative diagnostic test that will use genetic and clinical information to proactively assess each person’s risk for opioid-related adverse events and chronic post-operative pain. The results will help clinicians provide personalized pain management to maximize pain relief while minimizing opioid-related safety risks, including opioid dependence.

Migraines and other headaches are often debilitating for patients, yet few treatment options providing sustained relief exist. All available therapies, including frequently prescribed opioids, have considerable side effects or limitations. Therefore, novel treatment approaches are needed to reduce or eliminate the need to use opiates and other systemic pharmaceuticals. Thermaquil Inc. has developed a new way of stopping migraine and other headache pain by noninvasively blocking pain signal transmission in the head, which in initial studies allowed patients to discontinue use of opioids and other addictive pain medications. Thermaquil will now be conducting a larger randomized controlled trial to demonstrate the safety and effectiveness of this novel approach. After a baseline period, patients will be randomly assigned to the active or control condition and receive a single treatment. The study will continue for 12 weeks with the active versus control arms, before all patients will be given active therapy for an additional 12 weeks.

Guidelines published by the Centers for Disease Control and Prevention in 2016 recommended gradual reductions in opioid medication doses (opioid tapering) for people with chronic pain and substance use disorder and recommended that those patients with pain and opioid use disorder should be switched to opioid use disorder medications. Despite wide implementation, little is known about the consequences of opioid tapering among patients with co-occurring chronic pain and substance use disorder. This project will use various databases (Cerner Real-World DataTM, American Hospital Association data, and U.S. Census data) to create a representative electronic health records database. This database will be used to determine the relationship between opioid tapering, multidisciplinary pain treatment, and medications for opioid use disorder – as well as monitor outcomes for patients with chronic pain and co-occurring substance use disorder.

Although medications for opioid use disorder are effective and available, providers currently lack methods to monitor patients and thus inform improved dosing. This project will develop Strength Band Platform, an innovative artificial intelligence-based digital platform. The wearable device will collect patient physiological characteristics to detect relapse and withdrawal during treatment with medications for opioid use disorder in real-world settings. 

For many individuals in recovery from a substance use disorder, certain cues—including stress and drug-related cues—can trigger a physiological state in which they are more likely to relapse. In this SBIR project, the investigators intend to deploy a system—consisting of a wearable sensor, a smartphone app, and a clinical portal—to provide individuals in recovery and their treatment providers with an opportunity to identify moments of high risk for relapse and to access real-time intervention opportunities. The sensors will identify signals of stress or drug use, interface with a smartphone app, and provide options for annotations, stress-reduction techniques, or contact with an individual’s support system and treatment providers, as well as log and encourage healthy behaviors. This study will deploy and optimize the system, as well as test its effects on addiction-related outcomes, such as rate of relapse.

The proposed SBIR Phase II program seeks to select a first-in-class, peripherally-restricted, and long-acting somatostatin receptor 4 (LA-SSTR4) agonist clinical candidate for development as a novel non-addictive analgesic able to replace opioids for the treatment of moderate-to-severe chronic pain. The program is based on strong scientific evidence showing that activation of peripheral SSTR4 produces broad spectrum analgesic activity and pursues a unique therapeutic strategy.   Unlike opioids, SSTR4 agonists do not induce constipation, respiratory depression, dependence, addiction, or abuse. Finally, unlike SSTR2 and SSTR5, SSTR4 expression in the pituitary and pancreas is very low, supporting that selective SSTR4 agonists are unlikely to perturb peripheral endocrine functions. The preceding SBIR Phase I program has already established the feasibility of conjugating a short-acting, potent, and selective peptide SSTR4 agonist to the antibody carrier. The resulting LA-SSTR4 agonist lead series has high agonist potency and selectivity for SSTR4 and has demonstrated antinociceptive activity in an animal pain model. The proposed SBIR Phase II program seeks to: optimize the existing lead series and select a clinical candidate for development,  validate and prioritize the indication(s) for clinical development using disease-relevant mouse pain models, and characterize the pharmacokinetics and safety/toxicology profile of the clinical candidate in rat and non-human primates to help design subsequent investigational new drug (IND)-enabling studies.

Pain is one of the most common and debilitating symptoms of a wide range of injuries and diseases. Safe and effective alternatives for treating pain that reduce dependence on opioids are, therefore, a primary goal of the NIH. This project proposes a non-invasive, non-pharmacological alternative to treat pain by combining an innovative electroencephalography (EEG)-based Neurofeedback (NF) solution in an immersive virtual reality (VR) environment. NF and VR have been shown to independently produce ameliorative effects on pain, and it is hypothesized that an NF training in VR would have synergistic effects, as VR would distract from pain perception to improve patient compliance in more engaging NF protocols that improve their ability to control pain perception. In the scope of this project, we will initially focus our work on chronic low back pain (cLBP), as this is a growing segment of chronic pain sufferers with a 39 percent worldwide lifetime prevalence, and whose sufferers have historically been heavy users of opiates; later stages of this project will expand this application to address other forms of pain.

Many current pain relief treatments rely on use of opioid drugs. This research is conducting preclinical development on a non-addictive, non-opioid therapeutic that uses antibodies to target the sodium channel Nav1.7. This channel is known to be one of the primary routes for generating pain signals – thus it is a target for reducing pain. The antibody approach offers potential for greater specificity than small molecule approaches, potentially resulting in fewer side effects.

Chemokines (hormones of the immune system that mediate innate immune inflammation) enhance pain, reduce opioid analgesia, and promote drug-seeking behavior and addiction, giving them a central role at the crossroads of chronic pain and the opioid crisis. Blocking chemokines (rather than opioid receptors) provides an exciting treatment opportunity for both pain and opioid use disorder. This research continues previous work studying the efficacy of RAP-103, a small, orally stable chemokine receptor blocker. The previous research has shown that RAP-103 is safety and effective in preclinical models that mimic human drug-taking. This research will now optimize the dose required to achieve decreased motivation to maintain opioid use, establish manufacturing scale-up feasibility, provide RAP-103 for safety testing in animals, and conduct stability testing of RAP-103 toward the goal of submitting an Investigational New Drug application to the FDA.

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.

Over-the-counter medicines such as non-steroidal anti-inflammatory drugs are ineffective for treating severe chronic pain and may have serious side effects from continued use, which limits treatment options. A kinase (an enzyme whose activity targets a specific molecule) called TAK1 is involved in the chronic pain process. This research will develop a molecule previously shown to be effective in a model of inflammatory pain that also inhibits TAK1. A main goal will be to determine if this inhibitor (takinib analog HS-276) can cross the blood-brain barrier and, if successful, pursue FDA  Investigative New Drug-enabling safety studies leading to a Phase I clinical trial and a potential new chronic pain treatment.