# Leveraging data-science for discovery in chronic TBI

> **NIH VA I01** · VETERANS AFFAIRS MED CTR SAN FRANCISCO · 2023 · —

## 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, often accompanied
by polytrauma to extremities as well as psychological wounds. 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 over 10000 mice, rats, pigs,
monkeys. The proposed VA merit award will expand these data with new data-donations collected from several
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, blast
injuries as well as polytrauma and stress models. 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:** 10641318
- **Project number:** 2I01RX002787-06
- **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:** 2023
- **Award amount:** —
- **Award type:** 2
- **Project period:** 2018-10-01 → 2028-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10641318

## Citation

> US National Institutes of Health, RePORTER application 10641318, Leveraging data-science for discovery in chronic TBI (2I01RX002787-06). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/10641318. Licensed CC0.

---

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