Targeted Realtime Assessment of Chronic Pain in Youth

Up to 5% of adolescents (~3.5 million in the US alone) suffer from high-impact chronic musculoskeletal (MSK) pain, affecting quality of life, school attendance, mood, and family function, and posing a significant economic burden of $19.5 billion annually in the US. A substantial proportion of these youths continue to suffer from pain into adulthood. Chronic MSK pain is characterized by a complex biological response, including physiological disturbances in cognition, sleep, and energy levels (fatigue), and is associated with impairments in both physical and emotional function. The chronic pain experience fluctuates over time with intra- and inter-daily variations and the occurrence of pain flares, contributing to unpredictability, uncertainty, and greater impairment.

Current gold standard self-report assessments are burdensome and fail to provide comprehensive, reliable measures of the pain experience due to inherent recall bias. A potential solution lies in the widespread adoption of digital health technologies, particularly wearable devices, which offer continuous monitoring of physiological, sleep, and physical activity data. This approach can yield unprecedented insights into individual health, informing diagnosis, prevention, monitoring, and treatment.

Through artificial intelligence (AI) and machine learning (ML), several groundbreaking digital biosignatures of human health have been developed by the research team, including those for glucose variability, preterm birth, panic attacks, fall risk, and surgical recovery. This real-time, personalized approach not only empowers patients but also enables healthcare providers to make more informed decisions, optimizing treatment strategies and improving outcomes. Despite these advancements, less than half of adolescents with chronic MSK pain who undergo pain treatment experience meaningful improvement.

The scientific rationale of this proposal is to overcome the limitations of self-report by integrating precise physiological, sleep, and physical activity measures from wearable devices with AI/ML to develop and validate a monitoring digital biosignature of the individual pain experience in youth with MSK pain. This biosignature will monitor the pain experience, track its progression, assess responses to interventions, and evaluate impacts on quality of life.

The research team is well positioned to execute these aims with: (1) a diverse, highly skilled team with expertise in digital technology, AI/ML, digital endpoint development, and clinical trials, alongside clinical expertise in chronic pain in youth and lived experience from patients, caregivers, and pain advocacy groups; (2) a secure, scalable, centralized, and standardized digital data collection, processing, and storage system; and (3) cutting-edge preliminary data supporting the capability to develop this digital health biosignature.

UG3/Discovery Phase: The research team will enroll up to 500 youth (ages 14-24) with chronic MSK pain, capturing continuous physiological (heart, respiratory), sleep, and physical (activity level, mobility, gait) activity metrics via wearables. Repeated intra-daily self-reports of the pain experience (pain interference, pain intensity, fatigue, mood, stress, pain flares) will be collected over 12 weeks. For a subset, data from physical and social stress tasks will also be gathered. The aim is to assess feasibility and relevance, develop a digital biosignature of the pain experience, and prepare for the UH3 phase through outreach and collaboration. Consultations with individuals with lived experience, those experiencing health disparities, and the FDA will ensure the relevance and acceptability of the biosignature and promote recruitment of underrepresented youth, coupled with scalability for clinical use.

UH3/Validation Phase: The research team will enroll up to 400 diverse youth with chronic MSK pain, capturing wearable and self-reported pain experience metrics over 12 weeks: a 4-week baseline followed by 8 weeks of abnormal reading-triggered alerts. The aim of this phase is to clinically validate the digital biosignature of the pain experience, and evaluate the accuracy and potential of an enhanced wellness alert system.

Significance and Clinical Impact: The successful development and validation of digital endpoints for the pain experience are crucial for advancing pain management. These endpoints promise to improve therapeutic development by providing robust, objective measures of treatment response. The outcomes of this study will be foundational for seeking regulatory approval for the commercialization of the associated software or for disseminating open-source analysis packages for future clinical trials.