Quantitative structure‐activity relationships for predicting skin and eye irritation

Patlewicz, Grace; Rodford, Rosemary; Walker, John D.

doi:10.1897/01-439

Cited by 23 publications

(15 citation statements)

References 35 publications

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“…They include skin and eye corrosion/irritation, where an accepted and validated tool is available (Gallegos Saliner et al 2006;Gerner et al 2005;Hulzebos et al 2003Hulzebos et al , 2005Walker et al 2005), skin sensitization where tools are under development (Patlewicz et al 2003), and bacterial mutagenicity (Ames test) where tools are available with defined domains of applicability (Benigni 2005). For these endpoints, there is a large database on test results that can be used, and it seems possible to develop general prediction systems.…”

Section: Future Prospectsmentioning

confidence: 99%

The Use of (Q)SAR Methods in the Context of REACH

Lahl¹,

Gundert‐Remy²

2008

Toxicology Mechanisms and Methods

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The new European REACH (Registration, Evaluation, Authorisation of Chemicals) legislation requires new information on chemicals, which is tiered according to production volume. The need for data promotes the use of (quantitative) structure-activity relationships ([Q]SARs) in order to meet the European political goal to protect the lives of animals. Within the preparation for REACH, the EU Commission set up REACH implementation projects (RIPs). They are aimed at giving guidance to industry and regulators on how to interpret the legislation. Within the framework of REACH, (Q)SARs are expected to have specific applications in several fields such as raising concerns for chemicals with low production volume for which no (eco)toxicological data have to be submitted, supporting the grouping of chemicals (family approach), and supporting the classification of chemicals as PBT (persistent/bioaccumulative/toxic) or vPvB (very persistent, very bioaccumulative) substances. Currently, the use of (Q)SARs in European regulatory decision making is limited. However, a new European tool (Toxtree) will be made available along with training courses to promote the use of (Q)SAR approaches under REACH. It is expected that the experimental data, to be submitted by industry and made publicly available under REACH, will provide opportunities to improve existing prediction tools and to develop new approaches for (Q)SAR analysis. In the political perspective, the tools will provide support as a rational basis for the intelligent design of new chemicals with sustainable (eco)toxicological properties.

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Section: Future Prospectsmentioning

confidence: 99%

The Use of (Q)SAR Methods in the Context of REACH

Lahl¹,

Gundert‐Remy²

2008

Toxicology Mechanisms and Methods

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“…(i) The prediction of eye and skin irritation have been reviewed by [37]. Due to the lack of quality in vivo data, the QSAR predictive power is limited in this area.…”

Section: Brief Overview and Application Of Toxicoinformatics Softwaresmentioning

confidence: 99%

Computer-Assisted Methods in Chemical Toxicity Prediction

Mohan

Gandhi²,

Garg³

et al. 2007

MRMC

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In Silico predictive ADME/Tox screening of compounds is one of the hottest areas in drug discovery. To provide predictions of compound drug-like characteristics early in modern drug-discovery decision making, computational technologies have been widely accepted to develop rapid high throughput in silico ADMET analysis. It is widely perceived that the early screening of chemical entities can significantly reduce the expensive costs associated with late stage failures of drugs due to poor ADME/Tox properties. Drug toxic effects are broadly defined to include toxicity, mutagenicity, carcinogenicity, teratogenicity, neurotoxicity and immunotoxicity. Toxicity prediction techniques and structure-activity relationships relies on the accurate estimation and representation of physico-chemical and toxicological properties. This review highlights some of the freely and commercially available softwares for toxicity predictions. The information content can be utilized as a guide for the scientists involved in the drug discovery arena.

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“…Payne and Morley [24] found that SAR rules predicted local corrosion or severe local irritation for highly reactive chemicals, but not for less reactive chemicals, possibly because they did not model partitioning within, and permeability through, the skin. (Q)SARs for predicting skin irritation and percutaneous absorption were recently reviewed by Patlewicz et al [25] and Walker et al [26], respectively.…”

Section: (Q)sars For Predicting Skin Irritation and Corrosionmentioning

confidence: 99%

(Q)SARs for Predicting Skin Irritation and Corrosion: Mechanisms, Transparency and Applicability of Predictions

et al. 2004

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This paper describes previously-developed (quantitative) structure-activity relationships [(Q)SARs]for predicting skin irritation and corrosion, proposes mechanisms of skin irritation and corrosion, and discusses the transparency and applicability of predictions. This paper was written to set the tone for companion papers that describe three applications of skin irritation and corrosion (Q)SARs. The first companion paper describes physicochemical property limits that can be used to develop rules for identifying chemical substances with no skin irritation or corrosion potential. The second companion paper describes structural alerts that can be used to develop rules for identifying chemical substances with skin irritation or corrosion potential. The third companion paper describes the Skin Irritation Corrosion Rules Estimation Tool (SICRET), a user-friendly tool that allows non-(Q)SAR experts to identify chemical substances with skin irritation or corrosion potential based on physicochemical property limits and structural alerts.

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Quantitative structure‐activity relationships for predicting skin and eye irritation

Cited by 23 publications

References 35 publications

The Use of (Q)SAR Methods in the Context of REACH

The Use of (Q)SAR Methods in the Context of REACH

Computer-Assisted Methods in Chemical Toxicity Prediction

(Q)SARs for Predicting Skin Irritation and Corrosion: Mechanisms, Transparency and Applicability of Predictions

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