Over 70% of chronic pain cases are women. Effective treatment of pain has been hampered by an entirely subjective protocol for measuring pain severity, with variation introduced in patient assessments and physician biases. Credit Arocamora, CC BY-SA 4.0
Chronic pain affects millions of people, with women experiencing more severe and frequent pain than men. Over 70% of chronic pain cases involve women. However, measuring and managing pain remains a complex challenge. There is currently no objective method to quantify pain, which makes it difficult to tailor treatments effectively. Additionally, there are significant variations in how patients experience pain and how physicians respond. A new research initiative aims to address these issues.
Tufts University, in collaboration with external partners, has been selected by the Advanced Research Projects Agency for Health (ARPA-H) as an award recipient for the Sprint for Women’s Health. This initiative aims to develop new technologies for quantitatively measuring pain in patients, to improve care and accelerate the development of new treatments. The team will receive $3.03 million in funding over the next two years.
Various factors, such as inflammation, damaged nerves, or conditions like fibromyalgia, can cause chronic pain. Each of these causes may require a different treatment approach. Regardless of its origin, pain is highly subjective and can be influenced by psychological, social, and other factors. While elite athletes and soldiers often train to tolerate high levels of pain, individual reactions to pain can vary significantly among those who experience it.
Standard practice in assessing pain in the clinical setting is entirely subjective—something most of us have experienced if asked to measure it on a chart using smiling to frowning emoticons.
Subjectivity in assessing pain is not just on the patient’s side. Bias also occurs on the treatment side, with some minority groups being undertreated for managing pain compared to the general population.
“Having an objective, quantitative tool to assess pain will help eliminate subjective variables and provide a more rational basis for treatment,” said Sameer Sonkusale, a professor of electrical and computer engineering at the Tufts School of Engineering and the principal investigator on the project. The project includes collaborators from the Uniformed Services University of Health Sciences (USU), The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF), and Northwestern Medicine.
The research team plans to screen more than 30 biomarkers, including stress hormones, inflammation markers, and neurotransmitters in the interstitial fluid that circulates between skin cells. Additionally, they will monitor physiological responses such as fluctuations in heart rate, galvanic skin response, and breathing patterns.
These biomarkers were identified in earlier studies as linked to a patient’s experience of pain, but this is the first effort to create a composite panel of markers to generate a quantitative score for pain.
The biomarker data will be merged with answers to pain questionnaires collected from women at several sites, including the Defense and Veterans Center for Integrative Pain Management and Northwestern Medicine. Shuchin Aeron, an electrical and computer engineering associate professor at Tufts, will apply artificial intelligence and machine learning to combine these factors into an objective and quantitative pain score.
The researchers will narrow the panel to five or more of the most reliable pain-linked biomarkers. These biomarkers can be monitored on a portable, wearable device for clinical site and remote pain assessment. The results would instantly be reported to the physician or the patient on a smartwatch or ring.
The availability of such devices would not only improve pain management. Still, it could also accelerate the development of new drugs and treatments, which could benefit from an objective measure of their effectiveness.
“While pain reporting is subjective and dependent on many extraneous factors, for the same pain level, the measurable physiological markers and signals are expected to be similar from one individual to the next,” said Sonkusale. “Considering an observed gender bias in the prevalence and approach to treatment of chronic pain, this technology addresses a large unmet medical need for women, creating a path to more effective pain management.”
“It has been extremely challenging to objectively quantify nociplastic pain—the type of pain involving nervous system sensitization in conditions like fibromyalgia that are quite common in women. This study could provide a way to objectively quantify pain in a way that will greatly help their treatment,” said Steven P Cohen, Edmond I Eger Professor of Anesthesiology and Pain Medicine at Northwestern Medicine.