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Combining Toxicological and Chemical Characterization of Complex Mixtures to Understand the Impact of the Unknown Fraction
Citation:
Simmons, Jane Ellen, R. Hertzberg, AND G. Rice. Combining Toxicological and Chemical Characterization of Complex Mixtures to Understand the Impact of the Unknown Fraction. Society of Toxicology, New Orleans, LA, March 13 - 17, 2016.
Impact/Purpose:
This abstract is prepared for an invited presentation at the annual meeting of the Society of Toxicology, March 13-17, 2016, New Orleans, LA. The session in which this presentation will be presented is titled ‘Unknown, Unknowns: Exploring the Unidentified of Complex Mixtures’, chaired by Drs. Cynthia Rider, NIEHS/NTP and Dr. Bethany Hannas, Dow Chemical Company.
Description:
Toxicological assessment of adverse health outcomes associated with exposure to complex mixtures provides an integrated response of the organism (or in vitro test system) that accounts for additivity among the components (both dose and response) as well as any greater than or less than additive interactions. However, toxicological information alone is often inadequate for extrapolation to other mixtures within the same class, such as mixtures formed during oxidant disinfection of water, or those formed during fuel combustion. Examples from combined chemical and toxicological characterization of a variety of complex chemical mixtures, including hazardous wastes, disinfection byproducts (DBPs), chemicals of emerging concern in surface and treated water, and air pollution mixtures will be used to illustrate how failure to account for the unidentified fraction potentially results in inaccurate toxic potency estimates. Risk remediation efforts benefit from an understanding of the mixture components that contribute most to the toxicity of the mixture. Two recently developed methods that require both concentration and toxicity data, the expected component contribution score (ECC) and a method based on regression modeling techniques, are illustrated with complex (DBP) and defined (DBP, carbamate) mixtures. The ECC requires knowledge of the concentrations and the relative toxic potencies of the component chemicals. The regression modeling approach requires dose-response, concentration and toxicity data. Additionally, a data intensive assessment strategy for determining the contributions of individual chemicals, additive and nonadditive interactions and the unknown fraction to mixture toxicity will be illustrated. (This abstract does not reflect EPA policy.)