# Leveraging data-science for discovery in chronic TBI

> **NIH VA I01** · VETERANS AFFAIRS MED CTR SAN FRANCISCO · 2020 · —

## Abstract

Chronic traumatic brain injury (TBI) is one of the most prevalent neurological disorders in both military and
civilian populations, impacting up to 5.3 million people in the US and costing $76 billion in healthcare and loss-
of-productivity. Yet relatively little is known about the precise neurobiological features of chronic TBI leading to
dysfunction and disability. This lack of knowledge limits the reliability of therapeutic development in animal
models and limits translation across species and into human patients. Part of the problem is that chronic TBI is
intrinsically complex, involving heterogeneous damage to the most complex organ system. This results in a
multifaceted syndrome spanning across heterogeneous data sources and multiple scales of analysis. This
multi-scale heterogeneity makes chronic TBI difficult to understand using traditional analytical approaches that
focus on a single endpoint for testing therapeutic efficacy. Single endpoints reflect a small portion of a
complex system of changes that describe the holistic syndrome of chronic TBI. In this sense, complex chronic
TBI is fundamentally a ‘big-data’ problem requiring pooled information and analytics to evaluate reproducibility
in basic discovery and cross-species translation. The proposed project will develop novel applications of
cutting edge multidimensional analytics to integrate preclinical chronic TBI data on a large scale. The goal of
the proposed project is to develop an integrated workflow for preclinical discovery, reproducibility testing, and
translational discovery both within and across chronic TBI types. The project team is well-positioned to execute
this project given that with prior federal funding it built one of the largest multicenter, multispecies repositories
of neurotrauma data to-date, housing detailed multidimensional outcome data on nearly 4000 mice, rats, pigs,
and monkeys. The proposed VA merit award will expand these data with new data-donations collected from 5
preclinical TBI research laboratories across the US, including chronic (>1 month) TBI models of penetrating
injury, closed head injuries, repeated mild injuries, acceleration/ deceleration, lateral fluid percussion, and blast
injuries. The project will harmonize these existing data resources into a single data pool, enabling application
of recent innovations from data science to render complex multidimensional endpoint data into robust
syndromic patterns that can be visualized and explored by researchers in a user-friendly manner. The project
will accelerate data-driven-discovery, scientific reproducibility, hypothesis-generation, and ultimately precision
medicine for chronic TBI.

## Key facts

- **NIH application ID:** 10066267
- **Project number:** 5I01RX002787-03
- **Recipient organization:** VETERANS AFFAIRS MED CTR SAN FRANCISCO
- **Principal Investigator:** ADAM R FERGUSON
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2018-10-01 → 2022-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10066267

## Citation

> US National Institutes of Health, RePORTER application 10066267, Leveraging data-science for discovery in chronic TBI (5I01RX002787-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10066267. Licensed CC0.

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