# SPRINT: Signature for Pain Recovery IN Teens

> **NIH NIH R33** · STANFORD UNIVERSITY · 2023 · $2,126,713

## Abstract

PROJECT SUMMARY
Up to 5% of adolescents (~3.5 million in the US alone) suffer from high impact chronic musculoskeletal (MSK)
pain, affecting all life domains and posing a significant economic burden. Current treatments for chronic MSK
pain are suboptimal and have been tied to the opioid crisis. Only ~50% of adolescents with chronic MSK pain
who present for multidisciplinary pain treatment recover, as measured by clinical endpoints of pain severity and
functional disability. Discovery of robust markers of the recovery vs. persistence of pain and disability is
essential to develop more resourceful and patient-specific treatment strategies and to conceive novel
approaches that benefit patients who are refractory. Given that chronic pain is a biopsychosocial process, the
discovery and validation of a prognostic and robust signature for pain recovery vs. persistence requires
measurements across multiple dimensions in the same patient cohort in combination with a suitable ‘big data’
computational analysis pipeline for the extraction of reliable and cross-validated results from a multilayered and
complex dataset. We are well positioned to execute the study aims with: (1) A highly skilled and experienced
team of scientists and clinicians from Stanford University, University of Toronto/Hospital for Sick Children, and
Cincinnati Children’s Hospital Medical Center; (2) A standardized specimen collection, processing, storage, and
distribution system, leveraging Stanford Biobank’s platform, BioCatalyst, to aggregate the sample inventory with
clinical annotations for an accessible, virtual biobank, within the Signature of Pain Recovery IN Teens (SPRINT)
Biobank and Analysis Core (SBAC); (3) Cutting-edge preliminary data implicating novel candidates for
neuroimaging, immune, quantitative sensory, and psychological markers for discovery; and (4) Expertise in
machine learning approaches to extract reliable and prognostic bio-signatures from a large and complex data
set. We expect that the results from this project will facilitate risk stratification in patients with chronic MSK, a
more resourceful selection of patients who are likely to respond for undergoing current multidisciplinary pain
treatment approaches, and new insight into biological and behavioral processes that may be exploited to develop
novel strategies profiting those who are refractory. For the R61/Discovery Phase Aim individuals will be
thoroughly characterized via biological (i.e. brain structure and function, immune, sensory profiles), psychological
state, and clinical endpoint (i.e., pain intensity, disability) data. Unbiased machine learning algorithms will identify
a multivariate model comprised of the most prognostic biological, psychological, and clinical endpoints. The
model will classify adolescents with and without resolving chronic MSK pain after a state-of-the art
multidisciplinary pain treatment intervention. R33/Validation Phase Aim will validate the biological signature
derived in t...

## Key facts

- **NIH application ID:** 10709409
- **Project number:** 4R33NS114926-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** LAURA E SIMONS
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $2,126,713
- **Award type:** 4N
- **Project period:** 2019-09-30 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10709409

## Citation

> US National Institutes of Health, RePORTER application 10709409, SPRINT: Signature for Pain Recovery IN Teens (4R33NS114926-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10709409. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*