Funded Projects

NOFO Title: Notice of Special Interest to Encourage Eligible NIH HEAL Initiative Awardees to Apply for PA-20-222: Research Supplements to Promote Diversity in Health-Related Research (Admin Supp - Clinical Trial Not Allowed)
NOFO Number: NOT-NS-20-107
Summary:

Although digital health technologies are now widely available for both therapeutic and monitoring applications, there are wide variations in patient knowledge, attitudes, beliefs, and preferences regarding their uptake and effectiveness. There are also sociodemographic variations in willingness to participate in digital health research studies, both for chronic pain and other common disorders. However, few efforts have systematically examined patient-level predictors of digital health uptake and benefit among diverse individuals who experience chronic pain. This research will employ mixed methods to examine variations in engagement and benefit among diverse participants in a large clinical trial examining the benefits of virtual reality for treatment of chronic lower back pain.

NOFO Title: HEAL Initiative: Restoring Joint Health and Function to Reduce Pain Consortium (RE-JOIN) (UC2 Clinical Trial Not Allowed)
NOFO Number: RFA-AR-22-009
Summary:

This project will use a variety of technologies to create a comprehensive, 3D map of how sensory neurons activate knee joints in both mice and humans. The research will use imaging techniques and molecular approaches that measure gene expression. The findings will help create a comprehensive gene expression profile map of individual cells in the nerve fibers leading to the knee, as well as describe how nerve cells and joint cells interact at the most fundamental level. This research will generate a rich anatomical and molecular resource to understand the molecular basis of joint pain and guide the development of novel pain-relieving strategies.

NOFO Title: Notice of Special Interest to Encourage Eligible NIH HEAL Initiative Awardees to Apply for PA-20-222: Research Supplements to Promote Diversity in Health-Related Research (Admin Supp - Clinical Trial Not Allowed)
NOFO Number: NOT-NS-20-107
Summary:

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.

NOFO Title: Notice of Special Interest to Encourage Eligible NIH HEAL Initiative Awardees to Apply for Administrative Supplements to Support Career Enhancement Related to Clinical Research on Pain (Admin Supp – Clinical Trial Not Allowed)
NOFO Number: NOT-NS-21-048
Summary:

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.

NOFO Title: Notice of Special Interest to Encourage Eligible NIH HEAL Initiative Awardees to Apply for Administrative Supplements to Support Career Enhancement Related to Clinical Research on Pain (Admin Supp – Clinical Trial Not Allowed)
NOFO Number: NOT-NS-21-048
Summary:

There are numerous pharmacological and non-pharmacological interventions for chronic low back pain, yet no treatment is universally effective. This award supports an early career physician to develop skills to prepare for a career in clinical pain research in an environment aiming to understand patient characteristics that predict differential responses to pain interventions and thus allow for tailored treatments. This research assesses the impact of mindfulness-based stress reduction on pain interference reported by people with chronic low back pain and explores neurobiological effects of mindfulness-based stress reduction through advanced imaging and clinical assessments.

NOFO Title: HEAL Initiative: Back Pain Consortium (BACPAC) Research Program Technology Research Sites (UH2/UH3 Clinical Trial Optional)
NOFO Number: RFA-AR-19-028
Summary:

Despite the significance of spine disorders, there are few reliable methods to determine appropriate patient care and evaluate intervention effectiveness. The research and tool development take the critical next step in the clinical translation of faster, quantitative magnetic resonance imaging (MR) of patients with lower back pain. The multidisciplinary Technology Research Site (Tech Site) of BACPAC will develop Phase IV (i.e., technology optimization) technologies and/or methods (TTMs) to leverage two key technical advancements: development of machine learning-based, faster MR acquisition methods and machine learning for image segmentation and extraction of objective disease related features from images. The team will develop, validate, and deploy end-to-end deep learning-based technologies (TTMs) for accelerated image reconstruction, tissue segmentation, and detection of spinal degeneration to facilitate automated, robust assessment of structure-function relationships between spine characteristics, neurocognitive pain response, and patient-reported outcomes.

NOFO Title: Notice of Special Interest to Encourage Eligible NIH HEAL Initiative Awardees to Apply for PA-20-222: Research Supplements to Promote Diversity in Health-Related Research (Admin Supp - Clinical Trial Not Allowed)
NOFO Number: NOT-NS-20-107
Summary:

Chronic low back pain affects millions of Americans and is difficult to treat. Currently, there are no reliable methods to determine the best treatment options for patients, or to objectively evaluate the effectiveness of various interventions. This research will develop an imaging technology that uses machine learning to make automated assessments of spine characteristics, pain response, and patient-reported outcomes in people with chronic low back pain. This award will be used to recruit and support two postdoctoral fellows from populations underrepresented in biomedicine. The research will focus on whether use of the imaging tool helps clarify clinical diagnoses, as measured by the level of agreement between radiologists before and after using the tool.

NOFO Title: HEAL Initiative: Back Pain Consortium (BACPAC) Research Program Technology Research Sites (UH2/UH3 Clinical Trial Optional)
NOFO Number: RFA-AR-19-028
Summary:

Chronic low back pain (cLBP) is recurrent and often nonresponsive to conservative treatments. Biomechanists, physical therapists, and surgeons each utilize a variety of tools and techniques to assess and interpret qualitative movement changes to understand potential mechanical and neurological sources of low back pain and as critical elements in their treatment paradigm. However, objectively characterizing and communicating this information is currently impossible, since clinically feasible (i.e., cost-effective, objective, and accurate) tools and quantitative benchmarks do not exist. This research addresses the challenge to improve cLBP outcomes through the use of unique, inexpensive, screen-printable, elastomer-based, nanocomposite, piezoresponsive sensors, which will be integrated into a SPInal Nanosensor Environment (SPINE) sense system to measure lumbar kinematics and provide an objective, quantitative platform for diagnosis, monitoring, and follow-up assessment of cLBP.

NOFO Title: HEAL Initiative: Pragmatic and Implementation Studies for the Management of Pain to Reduce Opioid Prescribing (PRISM)(UG3/UH3 Clinical Trial Optional)
NOFO Number: RFA-AT-19-004
Summary:

Fibromyalgia (FM) is a chronic pain condition characterized by widespread musculoskeletal pain, tenderness, and stiffness associated with fatigue and sleep disturbance. The investigators have recently completed a trial that demonstrated efficacy of active transcutaneous electrical nerve stimulation (TENS) compared with placebo TENS or no treatment in women with FM. While physical therapists are trained in using TENS, it is underused in clinical practice. This application proposes a pragmatic clinical trial of TENS for patients with FM to determine if the addition of TENS to physical therapy (PT) reduces pain, increases PT adherence, and helps achieve functional goals with less drug use. This study will address the critical need for strategies to implement effective nonpharmacologic treatments for FM. Successful completion of this trial will provide generalizable effectiveness data for referring providers, physical therapists, and insurers and will inform future pragmatic trials of nonpharmacologic treatments conducted in PT practices.

NOFO Title: PHS 2018-02 Omnibus Solicitation of the NIH, CDC, and FDA for Small Business Innovation Research Grant Applications (Parent SBIR [R43/R44] Clinical Trial Not Allowed)
NOFO Number: PA-18-574
Summary:

 Quell Therapeutics uses the Optopatch platform for making all-optical electrophysiology measurements in neurons at a throughput sufficient for phenotypic screening. Using engineered optogenetic proteins, blue and red light can be used to stimulate and record neuronal activity, respectively. Custom microscopes enable electrophysiology recordings from 100’s of individual neurons in parallel with high sensitivity and temporal resolution, a capability currently not available with any other platform screening technology. Here, researchers combine the Optopatch platform with an in vitro model of chronic pain, where dorsal root ganglion (DRG) sensory neurons are bathed in a mixture of inflammatory mediators found in the joints of osteoarthritis patients. The neurons treated with the inflammatory mixture become hyperexcitable, mimicking the anticipated cellular pain response. Investigators calculate the functional phenotype of arthritis pain, which captures the difference in action potential shape and firing rate in response to diverse stimuli. The team will screen for small molecule compounds that reverse the pain phenotype while minimizing perturbation of neuronal behavior orthogonal to the pain phenotype, the in vitro “side effects.” The highest ranking compounds will be chemically optimized and their pharmacokinetic, drug metabolism, and in vivo efficacy will be characterized. The goal is to advance therapeutic discovery for pain, which may ultimately help relieve the US opioid crisis.

NOFO Title: HEAL Initiative: Translational Development of Devices to Treat Pain (U18 Clinical Trial Not Allowed)
NOFO Number: RFA-EB-18-003
Summary:

Researchers will develop a novel transcranial focused ultrasound (tFUS) device for pain treatment and establish its effectiveness for treating sickle cell disease (SCD) pain in humanized mice. The tFUS will target the specific cortical regions involved in SCD pain using a novel non-invasive electrophysiological source imaging technique. The project’s goals have several aims. Aim 1: Develop tFUS devices for pain treatment. The mouse-scale system will be designed to validate the therapeutic effect of stimulating the anticipated cortical targets. This will inform development of the simpler human-scale system, which will use models of the skull to select cost-effective transducers to reach the targets. Aim 2: Evaluate tFUS effectiveness and optimize stimulation parameters in an SCD mice model. Researchers will determine effective tFUS parameters to chronically reduce SCD pain in mice and validate this using behavioral measures. Aim 3: Use electrophysiological source imaging to target and trigger closed-loop tFUS in animal models. This aim also includes performing safety studies to prepare for human trials. The project will develop a transformative, noninvasive tFUS device to effectively and safely treat pain in SCD. 

NOFO Title: HEAL Initiative: Translational Development of Devices to Treat Pain (U18 Clinical Trial Not Allowed)
NOFO Number: RFA-EB-18-003
Summary:

For patients with neuropathic pain refractory to therapy using small molecules, modulation of specific neural structures in the central or peripheral nervous system can provide effective alternative treatments. While current Food and Drug Administration–approved devices for dorsal root ganglion (DRG) stimulation are safe and effective, there have been an unfortunate number of adverse events associated with pulse generator infections and lead migration. The research team will develop a wireless, millimeter-sized nerve stimulator that can be delivered through the vasculature and stimulate the DRG to alleviate symptoms of neuropathic pain and the associated minimally invasive delivery method. This endovascular nerve stimulation (EVNS) system depends on development and integration of key novel technologies into an endovascular stent. The magnetoelectric transducers and electronic circuits will convert wireless power and data into stimulus patterns that can trigger neural activity in the DRG via miniature electrodes. After chronic demonstration of safety and functionality in large animal models, the team will prepare for regulatory discussions with the FDA. If successful, the EVNS will provide a technology platform for treating other neuropathic pain syndromes. 

NOFO Title: HEAL Initiative: Translational Development of Devices to Treat Pain (U18 Clinical Trial Not Allowed)
NOFO Number: RFA-EB-18-003
Summary:

This project aims to develop a next-generation noninvasive neuromodulation system for non-addictive pain treatments. The research team will build an integrated system that uses magnetic resonance image-guided focused ultrasound (MRgFUS) stimulation to target pain regions and circuits in the brain with high precision. The system will use MR imaging to locate three pain targets commonly used in clinical pain treatments, to stimulate those targets with ultrasound, and to monitor responses of nociceptive pain circuits using a functional MRI readout. Three collaborating laboratories will tackle the goals of this project: (Aim 1) Develop focused ultrasound technology for neuromodulation in humans, compatible with the high magnetic fields in an MRI scanner. (Aim 2) Develop MRI technology to find neuromodulation targets, compatible with focused ultrasound transducers. (Aim 3) Validate the complete MRgFUS neuromodulation system in brain pain regions in nonhuman primates. By the end of the project, the research team will have a fully developed and validated MRgFUS system that is ready for pilot clinical trials in pain management.