Integrating Knowledge Of Carcinogenicity Adverse Outcome Pathways (AOPs) With Experimental Data
Presented at EUSAAT 2018 by Dr Steven Kane, Scientist at Lhasa Limited.
The assessment of carcinogenicity and related toxicity endpoints is a principal area of research in the development of in silico prediction systems. In recent years, these systems have become embedded in regulatory guidance, where they may be used to replace or augment other testing methods.
Previously, we have described how knowledge relating to the carcinogenicity endpoint contained in the expert rule-based prediction system Derek Nexus was rearranged to generate a network of adverse outcome pathways that share common key events and which can be interrogated at different levels.
In this work we outline how this network can provide the basis for carcinogenicity predictions for individual compounds and that presenting knowledge in this way will allow the user to more intelligently combine in vitro and in vivo data with hypotheses for a predicted mode of action.
It is hoped that this approach will allow the user to build a weight of evidence (WOE) to predict the carcinogenicity of a query compound and determine the most appropriate next steps in the testing of a hypothesis. Where the WOE is strong enough, animal testing may be avoided completely.