Stratification of Toxicity

Mutagenicity Metabolites react with nucleic acid Metabolites sufficiently stable to cross nuclear membrane 

Pre-clinical and early clinical Toxicity directly related to dose size and intrinsic selectivity. Metabolites react with protein and cause cell death Overstimulation of receptor and others in superfamily. Metabolites not detoxified by glutathione etc. 

Carcinogenicity Metabolites react with nucleic add or hormonal effects Metabolites not detoxified by glutathione etc. Effects on thyroxine etc. leads to pituitary tumours 

Late clinical Metabolites react with protein Protein adduct acts as 

With increasing toxicity data of various kinds, more rehable predictions based on structure-toxicity relationships of toxic endpoints can be attempted [31-36]. Even the Internet can be used as a source for toxicity data, albeit with caution [37]. A number of predictive methods have been compared from a regulatory perspective [35]. Often traditional QSAR approaches using multiple Hnear regression are used [38]. Newer approaches include the use of neural networks in structure-toxicity relationships 

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