In:
QSAR & Combinatorial Science, Wiley, Vol. 27, No. 1 ( 2008-01), p. 60-76
Abstract:
This minireview describes the state‐of‐the‐art of available (Q)SARs/expert systems for skin sensitization and evaluates their utility for potential regulatory use. It is one of a series of minireviews in this journal and is based on an in‐depth review performed by the European Chemicals Bureau (ECB) of the European Commission's Joint Research Centre (JRC) in support of the development of technical guidance for the implementation of the Registration, Evaluation, and Authorization of CHemicals (REACH) legislation. Most existing models fall into one of two main categories: either they are local in nature, usually specific to a chemical class or reaction chemical mechanism or else they are global in form, derived empirically using statistical methods. Some global QSARs have been recently characterized in accordance with the OECD validation principles and shown to be of limited use for regulatory applications. These have been evaluated in more detail elsewhere. Expert systems capable of predicting skin sensitization are discussed briefly. The strong mechanistic understanding of skin sensitization has facilitated the development of relative alkylation index (RAI) models. The RAI approach, relying on reactivity and hydrophobicity as the key parameters, actually appears to be the most promising means of deriving robust and mechanistically interpretable models which can be applied in a regulatory context. These are now referred to as Quantitative Mechanistic Models (QMM). Whilst hydrophobicity is conveniently modelled using log P , reactivity is often not easily determined from chemical structure. Initiatives are in progress to generate the necessary reactivity data for reactions relevant to skin sensitization but more resources are still required. A strategy of how information from using the RAI approach can be used in the evaluation of skin sensitization potential is described. This is the subject of on‐going and future work.
Type of Medium:
Online Resource
ISSN:
1611-020X
,
1611-0218
DOI:
10.1002/qsar.200710067
Language:
English
Publisher:
Wiley
Publication Date:
2008
detail.hit.zdb_id:
2537668-8
detail.hit.zdb_id:
2010584-8
SSG:
12
SSG:
15,3
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