TR 109 – High information content technologies in support of read-across in chemical risk assessment
TR 109 : High information content technologies in support of read-across in chemical risk assessment | December 2010
Read-across exploits information on structurally related (similar) analogues to derive hypotheses about the activity of the new chemical and hence predict its toxicity without experimental testing. Large existing databases on traditional toxicological endpoints and mechanisms of action are available that can be searched by data mining and cheminformatics tools (a selection is presented in the report). In addition, high-information-content techniques such as 'omics (toxicogenomics and metabolomics in particular) can be utilised to generate and test these hypotheses, notably about the mechanism of action. Examples are given in the report for phthalates, oestrogens and skin sensitisers.
There is scope for improvement of the heuristics of analogue identification and hypothesis generation. Furthermore, real examples of using high-information-content data are needed to support read-across, e.g. to provide a biology based rationale for chemical grouping.