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Improving the applicability of (Q)SARs for percutaneous penetration in regulatory risk assessment.

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Author: Bouwman, T. · Cronin, M.T. · Bessems, J.G. · Sandt, J.J. van de
Type:article
Date:2008
Institution: TNO Kwaliteit van Leven
Source:Human & experimental toxicology, 4, 27, 269-276
Identifier: 240735
doi: doi:10.1177/0960327107085829
Keywords: Health · xenobiotic agent · article · biological model · chemistry · drug effect · European Union · government regulation · human · legal aspect · physiology · prediction and forecasting · quantitative structure activity relation · risk assessment · skin absorption · European Union · Government Regulation · Humans · Models, Biological · Predictive Value of Tests · Quantitative Structure-Activity Relationship · Risk Assessment · Skin Absorption · Xenobiotics

Abstract

The new regulatory framework REACH (Registration, Evaluation, and Authorisation of Chemicals) foresees the use of non-testing approaches, such as read-across, chemical categories, structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs). Although information on skin absorption data are not a formal requirement under REACH, data on dermal absorption are an integral part of risk assessment of substances/products to which man is predominantly exposed via the dermal route. In this study, we assess the present applicability of publicly available QSARs on skin absorption for risk assessment purposes. We explicitly did not aim to give scientific judgments on individual QSARs. A total of 33 QSARs selected from the public domain were evaluated using the OECD (Organisation for Economic Co-operation and Development) Principles for the Validation of (Q)SAR Models. Additionally, several pragmatic criteria were formulated to select QSARs that are most suitable for their use in regulatory risk assessment. Based on these criteria, four QSARs were selected. The predictivity of these QSARs was evaluated by comparing their outcomes with experimentally derived skin absorption data (for 62 compounds). The predictivity was low for three of four QSARs, whereas one model gave reasonable predictions. Several suggestions are made to increase the applicability of QSARs for skin absorption for risk assessment purposes.