Abstract
Abstract In vitro and in silico methods continue to be evaluated for their potential to inform chemical toxicology evaluation. The research arm of the Environmental Protection Agency has been one of many research bodies evaluating the potential of such methods as part of their ToxCast initiative. We set out to advance the ongoing discussion of improving toxicity testing by exploring whether or not ToxCast physiochemical properties and high-throughput assay data could be used as covariates in predictive models to accurately classify chemicals that either do not or do induce hepatocarcinogenesis in vivo. ToxCast physiochemical and high-throughput assay data were evaluated against known chemicals and in vivo endpoints from the ToxRef curated data set. Hepatocarcinogen-causing chemicals were found to be larger and more lipophilic and complex in shape than control group chemicals. Adjusted logistic regression models using physiochemical properties as covariates accurately classified 71% of the chemicals into t...
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