# An automated AI/ML platform for multi-researcher collaborations for a NIH BACPAC funded Spine Phenome Project

> **NIH NIH UH3** · OHIO STATE UNIVERSITY · 2022 · $292,717

## Abstract

Project Summary/Abstract
Chronic Low Back Pain (cLBP) is a debilitating condition that affects millions of people globally. Despite
increased utilization of interventions and rising medical costs, cLBP prevalence has continued to increase. This
problem arises because cLBP is complex, heterogeneous and current diagnostics and treatments rely primarily
on subjective metrics and do not target all the multidimensional biopsychosocial mechanisms associated with
cLBP. Specifically, most diagnostics do not quantitively consider patient functional measures. To address this
problem, our parent grant is focused on developing and validating a digital health platform to provide
meaningful data-driven metrics that enables an integrated approach to clinical evaluation and treatment of
cLBP. However, it does not directly address the operational and quality management challenges associated
with performing AI/ML analyses at scale with multiple research partners. While the original grant will support
some manual AI/ML analyses as part of its deliverables, additional effort is needed to achieve AI/ML readiness
and maximize the full potential of the developed dataset for the BACPAC consortium and other NIH
collaborators. The proposed supplementary grant will develop the needed infrastructure and pipeline to support
data sharing in a more AI/ML-friendly way, while also allowing for more intimate collaborations with other
consortium members who are interested in AI/ML. Technology development effort will be done in partnership
with AWS Cloud services. The specific aims are to: 1) develop an AI/ML Computational data access pipeline
for the Digital Health Platform; and 2) develop platform features that will streamline AI/ML workflows. The
outcome of this project will decrease the overhead time spent on constantly reforming datasets so ML
researchers can focus on developing models and identifying actionable findings. Collectively, this effort aligns
with NIH’s strategic goals for data science and has the potential to shift clinical practice paradigms, improve
patient outcomes, enhance care efficiency, and reduce costs.

## Key facts

- **NIH application ID:** 10594295
- **Project number:** 3UH3AR076729-02S2
- **Recipient organization:** OHIO STATE UNIVERSITY
- **Principal Investigator:** Safdar N. Khan
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $292,717
- **Award type:** 3
- **Project period:** 2019-09-26 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10594295

## Citation

> US National Institutes of Health, RePORTER application 10594295, An automated AI/ML platform for multi-researcher collaborations for a NIH BACPAC funded Spine Phenome Project (3UH3AR076729-02S2). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10594295. Licensed CC0.

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