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|Title:||Evaluation of SARs for the Prediction of Eye Irritation/corrosion Potential - Structural Inclusion Rules in the BfR Decision Support System|
|Authors:||TSAKOVSKA Ivanka; GALLEGOS SALINER Ana; NETZEVA TATIANA; PAVAN MANUELA; WORTH ANDREW|
|Citation:||SAR AND QSAR IN ENVIRONMENTAL RESEARCH vol. 18 no. 3-4 p. 221-235|
|Publisher:||TAYLOR & FRANCIS LTD|
|Type:||Articles in periodicals and books|
|Abstract:||The proposed REACH regulation within the European Union (EU) aims to minimise the number of laboratory animals used for human hazard and risk assessment while ensuring adequate protection of human health and the environment. One way to achieve this goal is to develop non-testing methods, such as (quantitative) structure -activity relationships, suitable for identifying toxicological hazard from chemical structure and physicochemical properties alone. A database containing data submitted within the EU New Chemicals Notification procedure was compiled by the German Bundesinstitut für Risikobewertung (BfR). On the basis of these data, the BfR built a decision support system (DSS) for the prediction of several toxicological endpoints. For the prediction of eye irritation and corrosion potential, the DSS contains 31 physicochemical exclusion rules evaluated previously by the European Chemicals Bureau (ECB), and 27 inclusion rules that define structural alerts potentially responsible for eye irritation and/or corrosion. This work summarises the results of a study carried out by the ECB (Eurpoean Chemical Bureau) to assess the performance of the BfR structural rulebase. The assessment included: a) evaluation of the structural alerts by using the training set of 1341 substances with experimental data for eye irritation and corrosion; and b) external validation by using an independent test set of 199 chemicals. Recommendations are made for the further development of the structural rules in order to increase the overall predictivity of the DSS.|
|JRC Institute:||Institute for Health and Consumer Protection Historical Collection|
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