IATA-Bayesian Network Model for Skin Sensitization Data
2017
since the publication of the adverse outcome pathway aop for skin sensitization there have been many efforts to develop systematic approaches to integrate the information generated from different key events for decision making the types of information characterizing key events in an aop can be generated from in silico in chemico in vitro or in vivo approaches integration of this information and interpretation for decision making are known as integrated approaches to testing and assessment or iata one such iata that has been developed was published by jaworska et al 2013 which describes a bayesian network model known as its 2 the current work evaluated the performance of its 2 using a stratified cross validation approach we also characterized the impact of refinements to the network by replacing the most significant component the output from a commercial expert system times ss with structural alert information readily generated from the freely available oecd qsar toolbox lack of any structural alert flags or times ss predictions yielded a sensitization potential prediction of 79 3 4 if the times ss prediction was replaced by an indicator for the presence of a structural alert the network predictivity increased to 84 2 4 which was only slightly less than found for the original network 89 html_removed 2 the local applicability domain of the original its 2 network was also evaluated using reaction mechanistic domains to better understand what types of chemicals its 2 was able to make the best predictions for html_removed i e a local validity domain analysis we ultimately found that the original network was successful at predicting which chemicals would be sensitizers but not at predicting their relative potency this dataset is associated with the following publication fitzpatrick j and g patlewicz sar and qsar in environmental research application of iata a case study in evaluating the global and local performance of a bayesian network model for skin sensitization sar and qsar in environmental research taylor html_removed francis inc philadelphia pa usa 28 4 297 310 2017