Implications of a statistical occurrence model for mixture toxicity estimation |
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Authors: | Nur H. Orak Mitchell J. Small |
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Affiliation: | 1. Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA;2. Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA |
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Abstract: | This study provides a method for characterizing the effects of concentration variability and correlation among co-acting compounds on mixture toxicity, considering the implications of missing chemical data. The method is explored by developing a set of multiple occurrence scenarios for mixtures of related chemicals. The calculations are performed for hypothetical mixtures of a group of ten synthetic antibiotics that have been tested on marine bacterium to fit dose-response relationships for long-term bioluminescence inhibition of Vibrio fischeri. Mixture toxicities are computed and compared for the assumptions of independent joint action theory and concentration/dose addition theory. The study results show that higher variability in concentrations is associated with higher effective (average) mixture toxicity, in this application by as much as a factor of ten for mixtures with highly variable component concentrations. Moreover, omitting the most toxic compounds caused mixture toxicities to be underestimated by a factor of approximately two. We recommend a pre-assessment of the effect of different chemical occurrence patterns and variability on mixture toxicity to help prioritize needs for further co-occurrence data and toxicity studies. |
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Keywords: | mixture toxicology risk assessment statistical model chemical mixtures chemical occurrence computational modeling |
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