The U.S. Environmental Protection Agency (EPA) is faced with the challenge of efficiently and credibly evaluating chemical safety often with limited or no available toxicity data. The expanding number of chemicals found in commerce and the environment, coupled with time and resource requirements for traditional toxicity testing and exposure characterization, continue to underscore the need for new approaches. In 2005, EPA charted a new course to address this challenge by embracing computational toxicology (CompTox) and investing in the technologies and capabilities to push the field forward. The return on this investment has been demonstrated through results and applications across a range of human and environmental health problems, as well as initial application to regulatory decision-making within programs such as the EPA’s Endocrine Disruptor Screening Program. The CompTox initiative at EPA is more than a decade old. This manuscript presents a blueprint to guide the strategic and operational direction over the next 5 years. The primary goal is to obtain broader acceptance of the CompTox approaches for application to higher tier regulatory decisions, such as chemical assessments. To achieve this goal, the blueprint expands and refines the use of high-throughput and computational modeling approaches to transform the components in chemical risk assessment, while systematically addressing key challenges that have hindered progress. In addition, the blueprint outlines additional investments in cross-cutting efforts to characterize uncertainty and variability, develop software and information technology tools, provide outreach and training, and establish scientific confidence for application to different public health and environmental regulatory decisions.

Pyrethroids are pesticides with high selectivity for insects. In order to identify strengths and gaps in the database for pyrethroid neurobehavioral toxicology, we have critically analyzed the data from peer-reviewed literature. This review includes dose-response data that have been recently generated demonstrating consistent findings for low-dose, acute, oral exposure to pyrethroids in small rodents. All pyrethroids tested (i.e., about twenty compounds), regardless of structure, produce a decrease in motor activity in a variety of test protocols. The range of relative potencies varies more than two orders of magnitude, and thresholds for motor activity were found well below doses that produce overt signs of poisoning. Six compounds (allethrin, permethrin, cis-permethrin, deltamethrin, cypermethrin, and fenvalerate) impair schedule-controlled operant responding, seven compounds (pyrethrum, bifenthrin, S-bioallethrin, permethrin, beta-cyfluthrin, cypermethrin, and deltamethrin) decrease grip strength, and two compounds (deltamethrin and alpha-cypermethrin) produce incoordination using the rotarod. In addition, while compounds lacking an alpha-cyano group (e.g., cismethrin, permethrin, bifenthrin) induce an increase in acoustic-evoked startle response amplitude, cyano compounds (e.g., deltamethrin, cypermethrin, cyfluthrin) produce the opposite outcome. Other endpoints (e.g., tremor intensity, sensory response) have been only occasionally explored. A synthesis of the neurobehavioral evidence relating to the action of pyrethroids indicates that some differences in the experimental findings across compounds are also present in the low-effective dose range. For risk assessment purposes, a strategy that takes into account data from an array of neurobehavioral endpoints is needed to capture the heterogeneity of pyrethroid-induced adverse effects and accurately inform policy decisions.

New approach methodologies (NAMs) that efficiently provide information about chemical hazard without using whole animals are needed to accelerate the pace of chemical risk assessments. Technological advancements in gene expression assays have made in vitro high-throughput transcriptomics (HTTr) a feasible option for NAMs-based hazard characterization of environmental chemicals. In this study, we evaluated the Templated Oligo with Sequencing Readout (TempO-Seq) assay for HTTr concentration-response screening of a small set of chemicals in the human-derived MCF7 cell model. Our experimental design included a variety of reference samples and reference chemical treatments in order to objectively evaluate TempO-Seq assay performance. To facilitate analysis of these data, we developed a robust and scalable bioinformatics pipeline using open-source tools. We also developed a novel gene expression signature-based concentration-response modeling approach and compared the results to a previously implemented workflow for concentration-response analysis of transcriptomics data using BMDExpress. Analysis of reference samples and reference chemical treatments demonstrated highly reproducible differential gene expression signatures. In addition, we found that aggregating signals from individual genes into gene signatures prior to concentration-response modeling yielded in vitro transcriptional biological pathway altering concentrations (BPACs) that were closely aligned with previous ToxCast high-throughput screening assays. Often these identified signatures were associated with the known molecular target of the chemicals in our test set as the most sensitive components of the overall transcriptional response. This work has resulted in a novel and scalable in vitro HTTr workflow that is suitable for high-throughput hazard evaluation of environmental chemicals.