TIMES-SS - Recent refinements resulting from an industrial skin sensitisation consortium

The TImes MEtabolism Simulator platform for predicting Skin Sensitisation (TIMES-SS) is a hybrid expert system, first developed at Bourgas University using funding and data from a consortium of industry and regulators. TIMES-SS encodes structure-toxicity and structure-skin metabolism relationships t...

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Bibliographic Details
Published in:SAR and QSAR in environmental research 2014-01, Vol.25 (5), p.367-391
Main Authors: Patlewicz, G., Kuseva, C., Mehmed, A., Popova, Y., Dimitrova, G., Ellis, G., Hunziker, R., Kern, P., Low, L., Ringeissen, S., Roberts, D.W., Mekenyan, O.
Format: Article
Language:English
Subjects:
(Q)SAR
Animal Testing Alternatives - methods
Animals
Dermatitis, Contact - metabolism
expert system
Expert Systems
Guinea Pigs
Local Lymph Node Assay
Quantitative Structure-Activity Relationship
Risk Assessment - methods
Skin - metabolism
skin sensitisation
Skin Tests
TIMES-SS
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Summary:The TImes MEtabolism Simulator platform for predicting Skin Sensitisation (TIMES-SS) is a hybrid expert system, first developed at Bourgas University using funding and data from a consortium of industry and regulators. TIMES-SS encodes structure-toxicity and structure-skin metabolism relationships through a number of transformations, some of which are underpinned by mechanistic 3D QSARs. The model estimates semi-quantitative skin sensitisation potency classes and has been developed with the aim of minimising animal testing, and also to be scientifically valid in accordance with the OECD principles for (Q)SAR validation. In 2007 an external validation exercise was undertaken to fully address these principles. In 2010, a new industry consortium was established to coordinate research efforts in three specific areas: refinement of abiotic reactions in the skin (namely autoxidation) in the skin, refinement of the manner in which chemical reactivity was captured in terms of structure-toxicity rules (inclusion of alert reliability parameters) and defining the domain based on the underlying experimental data (study of discrepancies between local lymph node assay Local Lymph Node Assay (LLNA) and Guinea Pig Maximisation Test (GPMT)). The present paper summarises the progress of these activities and explains how the insights derived have been translated into refinements, resulting in increased confidence and transparency in the robustness of the TIMES-SS predictions.
ISSN:1062-936X
1029-046X
DOI:10.1080/1062936X.2014.900520