# A Network Science Approach to Conflicts of Interest: Metrics, Policies, and Communication Design

> **NIH NIH R01** · UNIVERSITY OF TEXAS AT AUSTIN · 2022 · $208,172

## Abstract

The primary purpose of this project is to develop new metrics and mechanisms for the evaluation of
conflicts of interest (COI) risks in the biomedical research enterprise. The innovation in COI risk
evaluation and communication will draw on a shift away from the conceptualization of COI as a problem
of individual researchers toward an understanding of COI as network phenomena. The pressing problems
of COI and the bias it inculcates stem not from individuals but from the aggregation of COI across
networks of researchers and funders. The research team will leverage machine-learning and high
performance computing to (1) track the circulation of COI within biomedical decision networks, and (2)
evaluate the extent to which certain conflict network profiles predict increased risks of patient harm. The
team will test candidate COI metrics with U.S. Food and Drug Administration's Adverse Events
Reporting System drug safety data. Using these data as a foundation, this project will also (3) develop and
evaluate strategies for communicating COI risks of bias designed to safeguard against the perverse
outcomes in current disclosure practices. The results of this research will underwrite novel evidence-based
recommendations for COI policies in biomedical research as well as recommendations for more effective
disclosure practices. To achieve these aims, this project will leverage machine-learning to identify systemic
COI networks within the biomedical research enterprises for specific drug products. The research team will
then evaluate to what extent network metrics predict relative increases in adverse event rates and severity
for identified products.

## Key facts

- **NIH application ID:** 10307626
- **Project number:** 5R01GM141476-02
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Joshua Ben Barbour
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $208,172
- **Award type:** 5
- **Project period:** 2020-12-01 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10307626

## Citation

> US National Institutes of Health, RePORTER application 10307626, A Network Science Approach to Conflicts of Interest: Metrics, Policies, and Communication Design (5R01GM141476-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10307626. Licensed CC0.

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