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

Research Spotlights

Can an inflammatory index predict sickle cell pain?

Traditional pain scale from 0 to 100, visualized with cartoon faces

Overview

The Research Need

Only a small fraction of new pain medications advance from safety testing in humans to approval by the U.S. Food and Drug Administration. One reason is because the research community lacks specific, measurable characteristics, or biomarker signatures, to assess pain objectively in individual patients.

About the Program

The program funds research to identify specific, reproducible characteristics of pain conditions (biomarker signatures) that reflect indicators of a normal or abnormal process, a condition or a disease, or a treatment response. These characteristics can be used to define pain levels objectively as well as to predict the development of chronic pain from injury or various diseases.

Careful selection of research participants for pain clinical studies based on these specific, measurable characteristics (called signatures or phenotypes) can improve the success of clinical trials by reducing variation among participants as well as developing a more precise set of targets. A program goal is to 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).

Because many individuals have more than one type of pain, the research leverages existing clinical studies to follow subsets of participants with two or more chronic overlapping pain conditions and determine relevant features that can serve as markers for development, progression, and treatment response to these conditions. The program also funds exploratory research, including with nonpharmacological treatments for muscles and associated soft tissues (such as fascia, a highly understudied tissue type in many painful conditions).

Past Events

September 1, 2022 - Technical Assistance Webinar
March 28, 2022 - Technical Assistance Webinar

Program Details

To date, through the Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative®, NIH has funded 16 awards for this program, totaling $46.3 million.

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 pain severity and duration
Developing biomarker signatures to diagnose eye pain
Developing patient immune biomarker signatures for sickle cell disease-related pain
Identifying biomarker signatures in both adolescents and adults, to diagnose and monitor treatments for musculoskeletal pain
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
Identifying and refining patient characteristics relevant to chronic overlapping pain conditions
Developing and validating real-world remote data from wearable devices to monitor pain experience and progression, treatment response, and quality of life

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