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Adverse Outcome Pathways – Tailoring Development to Support Use
Citation:
Edwards, S. Adverse Outcome Pathways – Tailoring Development to Support Use. Beyond Science and Decisions Workshop IX, Cincinnati, OH, June 09 - 10, 2015.
Impact/Purpose:
This presentation will highlight our efforts to streamline AOP discovery and development by creating computationally-predicted AOPS through data mining. It should increase awareness of this work and provide us feedback on best practices we should consider while pursuing this research.
Description:
Adverse Outcome Pathways (AOPs) represent an ideal framework for connecting high-throughput screening (HTS) data and other toxicity testing results to adverse outcomes of regulatory importance. The AOP Knowledgebase (AOP-KB) captures AOP information to facilitate the development, evaluation, and use of new AOPs. The AOP-KB is designed to structure information to facilitate computational modeling efforts while also capturing free-text descriptions to provide additional information important for regulatory decision-making. Fully describing an AOP can be labor intensive and requires a broad range of expertise, so the AOP-KB is specifically designed to encourage crowd-sourcing and expert review of the AOP development effort. In particular, the key events within the AOP are shared across all AOPs in the system, so that no one has to repeat information that has been previously entered and so all information for a key event is captured in a single location. The AOP-KB consists of four main components: AOP-Wiki, Effectopedia, AOP-Xplorer, and Intermediate Effects DB. This talk will describe the current capabilities of the AOP-KB with an emphasis on the AOP-Wiki component, which is currently the primary location for AOPs developed under the OECD AOP Development Programme. To generate more AOPs within the KB, we have developed data mining approaches to expedite the inclusion of computationally-predicted AOPs (cpAOPs) that include biological pathways containing ToxCast assay targets. A variety of input data sources have been used including large-scale toxicogenomics data such as the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) and public annotation databases such as the Comparative Toxicogenomics Database (CTD). By combining AOPs with exposure and absorption, distribution, metabolism, and excretion (ADME) predictions developed in a similar manner, we can recapitulate the mode of action for a given chemical from reusable components, allowing more extensive use of AOPs in hazard characterization and risk assessment.The views expressed in this abstract are those of the author and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.