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ICCVAM Biennial Report 2018-2019

ICCVAM Biennial Report 2018-2019
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https://ntp.niehs.nih.gov/go/884019

Prediction of Differential Responses to Toxicity from Genetically Diverse Cell Lines

To gain a deeper understanding of the biological effects of chemical exposures, AFRL has developed a cell-based toxicity analysis system based on the Clarity Bioanalytics software platform. In the lab, cells are exposed to chemical or biological agents and imaged using high-content, high-resolution microscopy. These images are processed through an analytics pipeline using DoD supercomputing resources. The Clarity Bioanalytics system studies the changes in cells after exposure, identifies the level of toxicity of different compounds, and discovers genetic elements (e.g., SNPs, genes, pathways) that could affect the cellular risk to certain exposures. This software platform represents a central analytics tool for exposure toxicology research within AFRL. It allows unbiased phenotyping of the toxic effects of a variety of chemical and biological agents, and genotype-phenotype analyses for personalized response assessment and prediction. Initial experiments on this system were performed using B-lymphocytes in suspension, but ideally the system must be able to analyze images from a wide variety of cell types with the best possible accuracy. Current efforts have established machine learning methods to allow identification of any cell type and extract feature/phenotype information from cells, allowing expanded capabilities for comparative, unbiased phenotyping.

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