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Risk Assessment Specialty Section (RASS)
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Overview of an Uncertainty Analysis Tool to Increase Transparency and
Communication of Uncertainty in Chemical Risk Assessment
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Jennifer E. Foreman, PhD, DABT
Exxon Biomedical Sciences Inc.
Annandale, NJ

Abstract
A systematic risk assessment (RA) is a time consuming and very detailed process that can often contain hundreds of pages and in depth discussion of scientific details. What are often brought forward from these assessments for decision making/communication are single point estimates, while the assumptions and uncertainties of the assessment are lost, which may therefore provide a false sense of precision. Many factors can influence the final point of departure (PoD) including experimental variability, quality of data, and underlying regulatory tenets (e.g. precautionary principle). All of these influencing factors and many others encompass the underlying uncertainty of the RA, which is not reflected in the PoD. Though this uncertainty is often articulated within a RA, and the importance is clearly recognized, the approach to account for uncertainty and communicate the level of uncertainty that exists in a given assessment is something with which the RA community continually grapples. New methods of uncertainty analysis are under development.

Having a clear and understandable manner to communicate the uncertainty in a RA is a necessity for transparency. Without an understanding of the uncertainty incorporated into a RA any decision makers, risk managers, or the public are unable to make judgments of how to use the information provided. Additionally, clear documentation of the uncertainty that was accounted for in an assessment allows for scientific dialogue and better understanding of what data could be generated to improve the precision of the assessment. Clear uncertainty analysis tools offer promise as an improved means of communicating and conveying uncertainty to regulatory decision makers, risk managers, and the public. One tool for uncertainty analysis with a visual depiction of results is highlighted here. Current explorations for making an accessible version of the tool will be discussed. Uncertainty analysis is an important component of transparency, which is critical for scientific dialogue and progress.
 

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Past Webinars

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Webinar February 14, 2018: Exposure Assessment for Chemical and Non-chemical Exposures for Urban Epidemiology

Webinar January 10, 2018: Assessing the Health Impact of Diverse Mixtures in the Environment

Webinar December 13, 2017: A Liver-centric Multiscale Modeling Framework for Xenobiotics

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Webinar June 10, 2015: Quantitative Evidence Integration to Facilitate the Use of Tox21 Data for Rapid Risk Screening

Webinar April 8, 2015: Adverse Outcome Pathways

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Webinar September 10, 2014: Toxicology for Breast Cancer Prevention

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Webinar April 10, 2013: Interface of Health Effects Caused by the CardioMetabolic Syndrome and Exposures to Air Pollutant Mixtures

Webinar February 13, 2013: Roundtable Panel Discussion: Should Journals Require the Release of Supporting Data As a Condition for Publication?

Webinar January 9, 2013: Mode of Action Research, Multispecies Pharmokinetic Modeling, and Risk Assessment for the Carcinogenesis of Hexavalent Chromium in the Small Intestine

Webinar December 12, 2012: Deming and Statistical Strategies to Make Observational Studies More Reliable

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Webinar April 25, 2012: Introduction to the New WHO/IPCS Guidelines for Immunotoxicity Risk Assessment for Chemicals

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Teleconference December 8, 2010: Selected Silver Book Highlights and Update on Related Activities

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Teleconference November 12, 2008: Pb NAAQS Human Health Risk Assessment—Overview of Design and Implementation

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Model Averaging: Beyond Model Uncertainty in Risk Analysis—Matthew W. Wheeler

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Framework for Inorganic Metals Risk Assessment—Anne Fairbrother, Randy Wentsel, Bill Wood, Keith Sappington, and Pam Noyes Office of Research and Development

The Application of Genomic Dose-Response Data in Risk Assessment—Harvey Clewell and Rusty Thomas CIIT Centers for Health Research

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A Biologically-Based Model for Low-Dose Extrapolation of Cancer Risk from Ionizing Radiation—Doug Crawford-Brown

Dosimetry Can Change Mechanistic Models: The Challenge of Scrutinizing the Source before Gathering and Analyzing the Data—Owen R. Moss

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HESI Project Committee on Dose-Dependent Transitions in Mechanisms of Toxicity Teleconference: Part 1 of 3

HESI Project Committee on Dose-Dependent Transitions in Mechanisms of Toxicity Teleconference: Part 2 of 3

HESI Project Committee on Dose-Dependent Transitions in Mechanisms of Toxicity Teleconference: Part 3 of 3

Identifying Research Needs for Risk Assessment of US Food Supply Security—Bruce Hope

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RASS Reception HESI Panel

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Assessing the Real Risk in Complex Diseases—Michael N. Liebman