There is an increasingly available sum of in vitro screening data from experimental assays. This embodies a new dimension of experimental knowledge that can help in predicting chemical toxicity along with traditional in silico desrciptors. The iPRIOR platform http://toxcast.ochem.eu was developed based on the Online Modeling Environment  to build quantitative activity relationship models for in vivo toxicity from ToxRefDb� exploiting HTS in vitro responses from ToxCast� phase I data. The platform consists of two integrated subsystems: The database of ToxCast� experimental measurements and the modeling framework. It incorporates in silico descriptor packages from both commercial and academic domains which were utilized to develop the models. We show that hybrid models, which incorporate both in vitro parameters and in silico descriptors, provided higher accuracy for prediction of liver toxicity compared to the separate use of individual descriptors. The in vitro parameters also expand the applicability domain of models.

Combining HTS in vitro assays with in silico descriptors for liver toxicity modeling

244th National Meeting (2012)

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