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Use of high-throughput and in vivo data to support read-across predictions
Citation:
Nelms, M. AND S. Edwards. Use of high-throughput and in vivo data to support read-across predictions. Intelligent Systems for Molecular Biology (ISMB), Orlando, FL, July 08 - 12, 2016.
Impact/Purpose:
Adverse Outcome Pathways (AOPs) can inform risk assessment involving chemical mixtures by providing a structured description of the mechanisms underlying the chemical toxicity. In the short term, this information can provide additional confidence in decisions regarding whether a dose addition or independent action assumption should be made. In the longer term, the AOP can be used to identify intermediate key events as surrogates for the adverse outcome in cases where independent action is required. The AOP can also be used to identify key events that could be used to evaluate dose addition assumptions where the confidence in that choice is not sufficient for the decision context. This poster represents preliminary work on using ToxCast data and AOP information to form chemical groups for testing and assessment.
Description:
Disrupting normal function of mitochondria can culminate in a variety of organ-level toxicities. A number of mechanisms - such as uncoupling of oxidative phosphorylation and inhibition of the electron transport chain - have been implicated in mitochondrial toxicity. The presence of mitochondrial toxicity has led to a number of drugs being withdrawn from the market highlighting the need to identify potential mitochondrial toxicants within the environment. High-throughput screening (HTS) assays provide a means of rapidly gathering toxicity data for a large number of chemicals; however, information as to the associated in vivo effect is typically unknown. The Adverse Outcome Pathway (AOP) concept provides a valuable scaffold onto which mechanistic data from different levels of biological organisation can be arranged.Information pertaining to mitochondrial toxicity from the U.S. EPA’s ToxCast program were integrated with rodent in vivo data from U.S. EPA’s ToxRefDB to connect the high throughput ToxCast assay results with potential adverse outcome data. Previously developed structural alerts were utilized to profile the chemicals with both in vitro mitochondrial toxicity and in vivo rodent data. Structural similarity guided by the toxicity profile as measured in the ToxCast assay battery was then used to group those chemicals which either were not tested in a mitochondrial toxicity assay or were not considered a “hit” and read-across was performed. Subsequently, the available literature was investigated to verify the read-across predictions. These results provide additional confidence in results from high-throughput toxicity testing by adding additional support for the ability of the assay to predict in vivo toxicity. In addition, these results provide a mechanism for predicting toxicity for chemicals based on structural similarity alone prior to HTS toxicity testing.