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New Approaches for Incorporating Genetic Diversity into Toxicity Testing

Our study aims to combine state-of-the art advances in microfluidics, computer vision, laboratory automation, and a massively curated genetically diverse nematode species to produce a new screening approach capable of testing thousands of chemicals relevant to agriculture, nutraceutical and biotech markets.



Most laboratory-based toxicology studies rely on the use of a limited number of rodent strains or other models to characterize dose-response relationships for generating hazard information or safe-exposure limits for chemicals. Although the use of a limited number of inbred rodent strains has the advantage of reducing experimental variability due to genetics and can enhance the reproducibility of studies for specific toxicants, these approaches do not capture the potential variability in responses in the human population. The National Academies of Sciences, Engineering, and Medicine held a workshop in 2015 on “Interindividual Variability: New Ways to Study and Implications for Decision Making” that focused on sources of inter-individual responses to chemical exposure, including genetic variability (https://www.nap.edu/catalog/23413/interindividual-variability-new-ways-to-study-and-implications-for-decisio). Developing new methods to capture human variability in response to chemical exposures can help to identify and protect sensitive populations that respond differently to drugs and to generate threshold limit values to protect workers from adverse effects of occupational exposures.


Therefore, there is a need for cost-effective approaches to model variation in response to toxicants in human populations for hazard identification, particularly to identify adverse effects that occur in genetically susceptible individuals. Characterizing differences in susceptibility based on genetic variation can further be applied to understanding mechanism or mode of action for toxicity, e.g., through additional molecular, biochemical, or histopathology analyses.


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