Read‐across to rank skin sensitization potential: subcategories for the Michael acceptor domain

Schultz, T.W.; Rogers, Kathryn; Aptula, Aynur O.

doi:10.1111/j.1600-0536.2008.01473.x

Cited by 55 publications

(42 citation statements)

References 31 publications

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“…This was demonstrated in the glutathione chemoassay where compounds with similar RC50 values were shown to have a 10-fold difference in rate constants (22). The allocation of Michael acceptors into subcategories of the domain (23) demonstrates this structural diversity. Data from the NBT-DNCB reaction shows that it was an outlier (Figure 5b).…”

Section: Discussionmentioning

confidence: 96%

Rapid and Simple Kinetics Screening Assay for Electrophilic Dermal Sensitizers Using Nitrobenzenethiol

Chipinda

Ajibola

Morakinyo

et al. 2010

Chem. Res. Toxicol.

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The need for alternatives to animal based skin sensitization testing has spurred research on the use of in-vitro, in silico and in chemico methods. Glutathione and other select peptides have been used to determine the reactivity of electrophilic allergens to nucleophiles, but these methods are inadequate to accurately measure rapid kinetics observed with many chemical sensitizers. A kinetic spectrophotometric assay involving the reactivity of electrophilic sensitizers to nitrobenzenethiol was evaluated. Stopped flow techniques and conventional UV spectrophotometric measurements enabled determination of reaction rates with half-lives ranging from 0.4 ms (benzoquinone) to 46.2 s (ethyl acrylate). Rate constants were measured for 7 extreme, 5 strong, 7 moderate and 4 weak/non-sensitizers. 17 out of the 23 tested chemicals were pseudo-first order and 3 were second order. In 3 out of the 23 chemicals, deviations from first and second order were apparent where the chemicals exhibited complex kinetics whose rates are mixed order. The reaction rates of the electrophiles correlated positively with their EC3 values within the same mechanistic domain. Nonsensitizers such as benzaldehyde, sodium lauryl sulfate and benzocaine did not react with nitrobenzenethiol. Cyclic anhydrides, diones and aromatic aldehydes proved to be false negatives in this assay. The findings from this simple and rapid absorbance model show that for the same mechanistic domain, skin sensitization is driven mainly by electrophilic reactivity. This simple, rapid and inexpensive absorbance based method has great potential for use as a preliminary screening tool for skin allergens.

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Section: Discussionmentioning

confidence: 96%

Rapid and Simple Kinetics Screening Assay for Electrophilic Dermal Sensitizers Using Nitrobenzenethiol

Chipinda

Ajibola

Morakinyo

et al. 2010

Chem. Res. Toxicol.

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“…Screening point values are also within an order of magnitude for anionic surfactant data from ECO-TOX and for alkyl sulfates (also anionic) from IUCLID and SIDS dossiers. Recently, several publications have discussed various techniques described as read-across approaches to hazard identification [25][26][27]. Goals of read-across approaches may include the use of existing information to provide an ecotoxicological concentration estimate to serve as a screening point value (SPV) for establishment of a safety value, reduce uncertainty surrounding risk management decisions, and allow prioritization of further testing needs.…”

Section: Discussionmentioning

confidence: 99%

Application of chemical toxicity distributions to ecotoxicology data requirements under REACH

Williams

Berninger

Brooks

2011

Environmental Toxicology and Chemistry

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The European Union's REACH regulation has further highlighted the lack of ecotoxicological data for substances in the marketplace. The mandates under REACH (registration, evaluation, authorization, and restriction of chemicals) to produce data and minimize testing on vertebrates present an impetus for advanced hazard assessment techniques using read-across. Research in our group has recently focused on probabilistic ecotoxicological hazard assessment approaches using chemical toxicity distributions (CTDs). Using available data for chemicals with similar modes of action or within a chemical class may allow for selection of a screening point value (SPV) for development of environmental safety values, based on a probabilistic distribution of toxicity values for a specific endpoint in an ecological receptor. Ecotoxicity data for acetylcholinesterase inhibitors and surfactants in Daphnia magna and Pimephales promelas were gathered from several data sources, including the U.S. Environmental Protection Agency's ECOTOX and Pesticides Ecotoxicity databases, the peer-reviewed literature, and the Human and Environmental Risk Assessment (HERA) project. Chemical toxicity distributions were subsequently developed, and the first and fifth centiles were used as SPVs for the development of screening-predicted no-effect concentrations (sPNECs). The first and fifth centiles of these distributions were divided by an assessment factor of 1,000, as recommended by REACH guidance. Use of screening values created using these techniques could support the processes of data dossier development and environmental exposure assessment, allowing for rigorous prioritization in testing and monitoring to fill data gaps.

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“…This, of course, requires that the errors introduced due to assay differences are more than compensated for by building a model on a larger, more diverse dataset. Examples of this approach include modeling studies by Schultz et al who used both LLNA and glutathione binding data to build models for skin sensitization [91]. A similar approach was taken in the TIMES-SS program where three different sources of in vivo data, derived from multiple animals, were used in modeling skin sensitization [92].…”

Section: Importance Of Data Treatmentmentioning

confidence: 98%

The Challenges Involved in Modeling Toxicity Data In Silico: A Review

Gleeson¹,

Modi²,

Bender³

et al. 2012

CPD

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The percentage of failures in late pharmaceutical development due to toxicity has increased dramatically over the last decade or so, resulting in increased demand for new methods to rapidly and reliably predict the toxicity of compounds. In this review we discuss the challenges involved in both the building of in silico models on toxicology endpoints and their practical use in decision making. In particular, we will reflect upon the predictive strength of a number of different in silico models for a range of different endpoints, different approaches used to generate the models or rules, and limitations of the methods and the data used in model generation. Given that there exists no unique definition of a 'good' model, we will furthermore highlight the need to balance model complexity/interpretability with predictability, particularly in light of OECD/REACH guidelines. Special emphasis is put on the data and methods used to generate the in silico toxicology models, and their strengths and weaknesses are discussed. Switching to the applied side, we next review a number of toxicity endpoints, discussing the methods available to predict them and their general level of predictability (which very much depends on the endpoint considered). We conclude that, while in silico toxicology is a valuable tool to drug discovery scientists, much still needs to be done to, firstly, understand more completely the biological mechanisms for toxicity and, secondly, to generate more rapid in vitro models to screen compounds. With this biological understanding, and additional data available, our ability to generate more predictive in silico models should significantly improve in the future.

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Read‐across to rank skin sensitization potential: subcategories for the Michael acceptor domain

Abstract: Background: Eliminating animal testing for skin sensitization is a significant challenge in consumer safety risk assessment. To be able to perform resilient risk assessments in the future, one will need alternative approaches to fill the data gaps.

Cited by 55 publications

References 31 publications

Rapid and Simple Kinetics Screening Assay for Electrophilic Dermal Sensitizers Using Nitrobenzenethiol

Rapid and Simple Kinetics Screening Assay for Electrophilic Dermal Sensitizers Using Nitrobenzenethiol

Application of chemical toxicity distributions to ecotoxicology data requirements under REACH

The Challenges Involved in Modeling Toxicity Data In Silico: A Review

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