Allergic contact dermatitis: is the reactive chemistry of skin sensitizers the whole story?

Basketter, David A.; Kimber, Ian

doi:10.1111/cod.12052

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…However, as there are also chemicals that are reactive towards proteins and do not elicit skin sensitization, it is generally difficult to deduce skin sensitization potential directly from protein reactivity. The reactive chemistry as an absolute requirement for skin sensitization elicitation is doubted by experts [4]. In the case of AS in pesticides, protein reactivity alerts did not necessarily correlate with skin sensitization.…”

Section: Discussionmentioning

confidence: 98%

“…Inside the skin the chemicals might react with proteins (KE1). However, this is not a mandatory requirement [4]. The actual allergen that is not necessarily identical to the sensitizing chemical interacts CONTACT M. Peiser matthias.peiser@bfr.bund.de Supplementary material for this article can be accessed at: https://doi.org/10.1080/1062936X.2018.1518261 with keratinocytes, epidermal Langerhans cells and dermal dendritic cells.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation and improvement of QSAR predictions of skin sensitization for pesticides

Braeuning

Braeuning²,

Mielke

et al. 2018

SAR and QSAR in Environmental Research

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In vivo skin sensitization assays have to be provided by applicants to the competent authorities in the European Union for the approval of active substances (AS) in pesticides. This study aimed to test the practicability of in silico predictions for AS by freely available (Q)SAR tools to evaluate their use as a time-and costeffective alternative to animal testing in the context of the 3R concept. Predictions of skin sensitization for 48 selected sensitizing and non-sensitizing AS by the software programs CAESAR, Toxtree, OECD (Q)SAR Toolbox, CASE Ultra, Leadscope and SciQSAR were collected and compared. Different data evaluation methodologies (score definition, mean, weighted mean, threshold score definition) were applied to optimize the predictions. The calculation methods were internally cross-validated and further validated with an additional validation set of 80 AS. Although the presented calculation methodologies are not suitable as a stand-alone method, this study has shown weaknesses and strengths of some prominent (Q)SAR programs and diverse combinatorial options in the prediction of skin sensitization by pesticidal AS. The present study will help to foster discussions on in silico alternatives to animal testing in the pesticide area.

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Section: Discussionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Evaluation and improvement of QSAR predictions of skin sensitization for pesticides

Braeuning

Braeuning²,

Mielke

et al. 2018

SAR and QSAR in Environmental Research

View full text Add to dashboard Cite

show abstract

“…In their commentary (1), Basketter and Kimber address two themes. The first may be summarized as ‘What are we to make of clinical reports of allergic contact dermatitis caused by chemicals that do not seem to be reactive in any way?’ and the second as ‘the relationship between protein reactivity and relative skin potency – why do we need kinetics?’ My response is structured similarly.…”

mentioning

confidence: 99%