Discovery and Validation of Biomarkers, Endpoints, and Signatures for Pain Conditions


The Research Need 

Pain is a major factor in many acute and chronic health conditions. Yet only a small fraction of new pain medications advance from safety testing in humans to approval by the U.S. Food and Drug Administration. 

About the Program 

Careful selection of research participants for pain clinical studies based on specific, measurable characteristics, or phenotypes, can improve the success of clinical trials by reducing variation among participants and developing a more precise set of targets. These characteristics may reflect indicators of a normal or abnormal process, a condition or a disease, or a treatment response. 

This program will fund research to identify specific, reproducible characteristics of pain conditions (biomarker signatures) that can be used to select patients for participation in clinical research to test novel, non-opioid pain treatments. These characteristics can be used to define pain levels objectively as well as to predict the development of chronic pain from either injury or various diseases. To facilitate the testing of non-opioid pain therapies in Phase 2 clinical trials, this research aims to discover and develop validated response-monitoring processes and prediction biomarker signatures for pain.  

The program will also fund exploratory research, including with nonpharmacological treatments, to characterize and test biomarker responses and potential predictive properties for muscles and associated soft tissues (e.g., fascia), a highly understudied tissue type in many painful conditions. 

This program will also develop new, individualized therapies based on specific pain-related characteristics and predictive models. Novel treatments can then be tested through program-funded prospective clinical studies or through the Early Phase Pain Investigation Clinical Network (EPPIC-Net)



Program Details

To date, through the Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative®, NIH has awarded grants to address the discovery of biomarkers, biomarker signatures, and endpoints for pain. Numerous Institutes and Centers across NIH support these grants. The awarded institutions will undertake preclinical research and development as well as initial clinical validation of biomarkers and signatures that could help reduce the extensive and long-term use of opioids in pain management.

Research Examples

Research examples supported by this program include: 

  • Identifying biomarker signatures to predict which patients will develop persistent headaches after a concussion or nerve pain after a spinal cord injury 
  • Using brain signals as signatures to predict the severity and duration of pain 
  • Developing biomarker signatures to diagnose eye pain 
  • Developing patient immune biomarker signatures for sickle cell disease-related pain 
  • Identifying biomarker signatures to diagnose and monitor treatments for musculoskeletal pain in adolescents and adults 
  • Discovering a novel human biomarker signature for prevention and treatment of post-operative pain 
  • Manipulating myofascial tissues to test biomarker responses and potential predictive properties 
  • Identifying pain biomarkers or biosignatures that predict and/or monitor response to pain therapeutics 

  • Beth Israel Deaconess Medical Center – Massachusetts 
  • Cleveland Clinic Lerner College of Medicine, Case Western Reserve University – Ohio 
  • George Mason University – Virginia 
  • Johns Hopkins University – Maryland 
  • Mayo Clinic Arizona – Arizona 
  • Mayo Clinic Rochester – Minnesota 
  • Medical College of Wisconsin – Wisconsin 
  • Stanford University – California 
  • Tufts Medical Center – Massachusetts 
  • University of Maryland, Baltimore – Maryland 
  • University of Pittsburgh – Pennsylvania 
  • University of Texas Health Science Center at Houston – Texas 
  • Washington University – Missouri 

Funded Projects

Multimodal Imaging Biomarkers for Investigating Fascia, Muscle, and Vasculature in Myofascial Pain
Sep 18, 2022
MRI-Based Quantitative Characterization of Impaired Myofascial Interface Properties in Myofascial Pain Syndrome
Sep 18, 2022
Electrophysiological and Ultrasound Quantitative Biomarkers for Myofascial Pain
Sep 18, 2022
Development and Identification of Magnetic Resonance, Electrophysiological, and Fiber-Optic Imaging Biomarkers of Myofascial Pain
Sep 18, 2022
Quantifying and Treating Myofascial Dysfunction in Post Stroke Shoulder Pain
Sep 18, 2022

Closed Funding Opportunities

Discovery of Biomarkers, Biomarker Signatures, and Endpoints for Pain (R61/R33 Clinical Trial Optional)
Sep 25, 2019