# Decision Science Core

> **NIH NIH P42** · TEXAS A&M UNIVERSITY · 2020 · $198,238

## Abstract

Decision Science Core ABSTRACT
The Texas A&M University Superfund Research Center will investigate the impacts of environmental
emergency-related contamination events across the source-to-outcome continuum, including fate and
transport, human health hazard, and mitigation of contamination and toxicity. In order to achieve the Center's
ultimate goal of improving decision-making after an environmental emergency, the conclusions drawn from
these projects will need to be interpretable to first responders, impacted communities, and government bodies
involved in site management and cleanup. Therefore, the entire Center will be supported by a Decision
Science Core, which has expertise in synthesizing relevant scientific data and conclusions for use by those
involved in decisions related to risk management. The overall objective of the Decision Science Core is to
provide novel modeling services for supporting the cohesion, relevance, and implementation of project findings
in the context of environmental decision-making. Directed by Dr. Weihsueh Chiu at Texas A&M University and
in collaboration with Dr. Gregory Characklis at the University of North Carolina at Chapel Hill, the Core will
provide numerous methods and services to the Center researchers under three specific aims will facilitate
interaction among Center projects, while also serving as a bridge to the Community Engagement Core and
Research Translation Core. Key services provided will include toxicokinetic modeling (Aim 1), human health
risk modeling (Aim 2), and economic modeling (Aim 3). In Aim 1, toxicokinetic modeling services will be
provided to the projects to extrapolate between exposure doses and internal concentrations in cells or tissues,
taking into account chemical absorption, distribution, metabolism, and excretion. Toxicokinetic modeling is an
essential part of moving towards a new paradigm in evaluating hazard and risk using in vitro assays. In Aim 2,
human health risk modeling will be used to make inferences about hazard or risk in the human population
based on experimental or observational data, serving as an essential bridge between scientific data and
environmental policy decisions. In the context of Superfund, human health risk modeling is used to
demonstrate that exposure standards or environmental remediation decisions both protect human health and
reduce toxicity or risk. In Aim 3, economic modeling of costs and benefits will be provided as a key input into
environmental policy decisions, from planning and priority setting to establishing environmental remediation or
exposure standards. The delivery of cost-effective environmental solutions is of keen interest not only to
government agencies, but also to affected communities and stakeholders, many of whom will bear at least
some of the cost, either directly or indirectly. As a whole, these modeling services will support the Center's
overall goal by helping to interpret and translate research project findings into informati...

## Key facts

- **NIH application ID:** 9903365
- **Project number:** 5P42ES027704-04
- **Recipient organization:** TEXAS A&M UNIVERSITY
- **Principal Investigator:** Weihsueh A Chiu
- **Activity code:** P42 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $198,238
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9903365

## Citation

> US National Institutes of Health, RePORTER application 9903365, Decision Science Core (5P42ES027704-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9903365. Licensed CC0.

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