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The OSIRIS Weight of Evidence approach: ITS for skin sensitisation
Authors:Emiel Rorije,Tom Aldenberg,Harrie Buist,Dinant Kroese,Gerrit Schü  ü  rmann
Affiliation:1. National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands;2. TNO Innovation for Life, Research Group Quality & Safety, Utrechtseweg 48, 3704 HE Zeist, The Netherlands;3. UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany;4. Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg, Germany
Abstract:Within the EU FP6 project OSIRIS approaches to Integrated Testing Strategies (ITSs) were developed, with the aim to facilitate the use of non-test and non-animal testing information in regulatory risk assessment of chemicals. This paper describes an analytical Weight-of-Evidence (WoE) approach to an ITS for the endpoint of skin sensitisation. It specifically addresses the European chemicals legislation REACH, but the concept is readily applicable to ITS and WoE procedures in other regulatory frameworks, and for other toxicological endpoints. Bayesian statistics are applied to estimate the reliability of a conclusion on the sensitisation potential of a chemical, combining evidence from different information sources such as QSAR model predictions, in vitro and in vivo test results. The methodology allows for adaptation of the weight of individual information sources to account for the different levels of reliability of the individual ITS components. The calculated reliability of the WoE conclusion gives an objective, transparent and reproducible measure to decide if the information requirements for data evaluation are satisfied. Furthermore, in case the WoE is not sufficient, it gives the possibility to evaluate a priori if and how it will be possible to fulfil the information requirements with additional tests and/or model predictions.
Keywords:Integrated Testing Strategy   ITS   REACH   Weight-of-Evidence   WoE   Bayesian inference
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