Accelerating Adverse Outcome Pathway Development Using Publicly Available Data Sources

Curr Environ Health Rep. 2016 Mar;3(1):53-63. doi: 10.1007/s40572-016-0079-y.


The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity (HTT) testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledge base; however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way. Computational tools for mining large datasets provide the means for extracting and organizing the information captured in these public data sources. Using cpAOPs as a starting point for expert-derived AOPs should accelerate AOP development. Coupling this with tools to coordinate and facilitate the expert development efforts will increase the number and quality of AOPs produced, which should play a key role in advancing the adoption of HTT testing, thereby reducing the use of animals in toxicity testing and greatly increasing the number of chemicals that can be tested.

Keywords: Adverse outcome pathways (AOPs); Computationally predicted AOPs (cpAOPs); Data mining; Risk assessment; Toxicity pathways.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review

MeSH terms

  • Computer Simulation
  • Ecotoxicology / methods*
  • Humans
  • Information Management / methods*
  • Risk Assessment / methods
  • Toxicity Tests*