Impact/Purpose:

Research in this area concentrates on understanding risk from mixtures of chemicals with similar or dissimilar modes of action. This includes identifying biomarkers of exposure and bioindicators of effect, as well as the development of data-driven statistical models for cumulative risk assessments. The objective of this research is to examine interactions resulting from exposures to multiple pesticides. This research will result in state-of-the-science tools for characterizing cumulative risks from exposure to pesticides. Results may be applied by OPP to identify and prioritize risks associated with cumulative exposure to pesticides, thereby reducing uncertainty in risk assessment.

Description:

SUMMARY: The Agency’s default assumption for the cumulative assessment of the risk of mixtures is additivity based on either single-chemical potency (dose addition) or single-chemical effects (effect addition). NTD is developing models to accurately predict effects of complex mixtures on human neurological health. A key step in this endeavor has been the development of statistical models that efficiently detect departures from additivity. These models demonstrated the importance of dose spacing in the regions of flexure in the dose-effect curve to optimize the power of detecting departures from additivity. NTD currently is evaluating pesticides with either similar modes of action (cholinesterase-inhibiting insecticides) or those for which a common mode of action has yet to be established (type I and II pyrethoids). NTD has demonstrated both additive and nonadditive effects depending on the endpoint and composition of the mixture. Where deviations from additivity occur, they likely involve both kinetic and dynamic interactions, demonstrating the need for integrated pharmacokinetic/ pharmacodynamic (PK/PD) models. NTD's development of such integrated models provides a foundation for advanced computational methods to predict the effects of complex exposures on human neurological health. APPROACH: The goal of this work is to develop abilities to assess the potential for interaction of representative cholinesterase-inhibiting pesticides in adult animals using biochemical and physiological endpoints. The data will include levels of erythrocyte, plasma, and brain cholinesterase inhibition, measures of thermoregulation, and central processing of visual and/or auditory information. Tissue levels of the pesticides and their metabolites may be analyzed and used in validation of pharmacokinetic models and evaluation of metabolic interactions. The outputs of this work will help the agency define efficient experimental designs and data analysis techniques for performing mixture studies. The data will provide the agency with information regarding possible interactions between prototypical cholinesterase-inhibiting pesticides, how the interaction may change between different ratios of the pesticides, and if any interactions can be explained on the basis of altered pharmacokinetics of the individual pesticides. The data will also provide relationships between levels of central and peripheral cholinesterase inhibition and changes in physiological function. Together, the results of this project will increase the Agency's ability to perform scientifically-based risk assessment of pesticide mixtures.

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