Literature DB >> 17763048

The application of non-default uncertainty factors in the U.S. EPA's Integrated Risk Information System (IRIS). Part I: UF(L), UF(S), and "other uncertainty factors".

Todd Stedeford1, Q Jay Zhao, Michael L Dourson, Marek Banasik, Ching-Hung Hsu.   

Abstract

The United States Environmental Protection Agency's Integrated Risk Information System (IRIS) includes hazard identification and dose-response assessment values developed by Agency scientists. Uncertainty factors (UFs) are used in the development of IRIS values to address the lack of information in five main areas. The standard UFs account for interspecies uncertainty (UF(A)) and intraspecies variability (UF(H)). The UF(A) addresses uncertainty related to the extrapolation of data from animals to humans, whereas the UF(H) addresses variability amongst individuals (i.e., intrahuman). Additional UFs have been employed to account for database incompleteness, extrapolations from a lowest-observed-adverse-effect level in the absence of a no-observed-adverse-effect level (UF(L)), and subchronic-to-chronic extrapolation (UF(S)). A sixth UF designated as "other uncertainty factors" (UF(O)) has also been applied in place of the UF(L) to account for uncertainty with the adversity of points of departure obtained using benchmark dose modeling. This review will discuss how UF(L), UF(S), and UF(O) have been applied in IRIS assessments, along with the rationale used to describe the choice of UF values that deviate from the standard default of 10.

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Year:  2007        PMID: 17763048     DOI: 10.1080/10590500701569430

Source DB:  PubMed          Journal:  J Environ Sci Health C Environ Carcinog Ecotoxicol Rev        ISSN: 1059-0501            Impact factor:   3.781


  5 in total

1.  Incorporation of the glutathione conjugation pathway in an updated physiologically-based pharmacokinetic model for perchloroethylene in mice.

Authors:  Chimeddulam Dalaijamts; Joseph A Cichocki; Yu-Syuan Luo; Ivan Rusyn; Weihsueh A Chiu
Journal:  Toxicol Appl Pharmacol       Date:  2018-05-29       Impact factor: 4.219

2.  Quantitative Characterization of Population-Wide Tissue- and Metabolite-Specific Variability in Perchloroethylene Toxicokinetics in Male Mice.

Authors:  Chimeddulam Dalaijamts; Joseph A Cichocki; Yu-Syuan Luo; Ivan Rusyn; Weihsueh A Chiu
Journal:  Toxicol Sci       Date:  2021-08-03       Impact factor: 4.849

3.  Physiologically based pharmacokinetic (PBPK) modeling of interstrain variability in trichloroethylene metabolism in the mouse.

Authors:  Weihsueh A Chiu; Jerry L Campbell; Harvey J Clewell; Yi-Hui Zhou; Fred A Wright; Kathryn Z Guyton; Ivan Rusyn
Journal:  Environ Health Perspect       Date:  2014-02-11       Impact factor: 9.031

Review 4.  Incorporating epigenetic data into the risk assessment process for the toxic metals arsenic, cadmium, chromium, lead, and mercury: strategies and challenges.

Authors:  Paul D Ray; Andrew Yosim; Rebecca C Fry
Journal:  Front Genet       Date:  2014-07-16       Impact factor: 4.599

5.  Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products.

Authors:  Patricia Ruiz; Gino Begluitti; Terry Tincher; John Wheeler; Moiz Mumtaz
Journal:  Molecules       Date:  2012-07-27       Impact factor: 4.411

  5 in total

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