Global (Q)SARs for skin sensitisation: assessment against OECD principles

Skin sensitization in silico protocol

The assessment of skin sensitization has evolved over the past few years to include in vitro assessments of key events along the adverse outcome pathway and opportunistically capitalize on the strengths of in silico methods to support a weight of evidence assessment without conducting a test in animals. While in silico methods vary greatly in their purpose and format; there is a need to standardize the underlying principles on which such models are developed and to make transparent the implications for the uncertainty in the overall assessment. In this contribution, the relationship between skin sensitization relevant effects, mechanisms, and endpoints are built into a hazard assessment framework. Based on the relevance of the mechanisms and effects as well as the strengths and limitations of the experimental systems used to identify them, rules and principles are defined for deriving skin sensitization in silico assessments. Further, the assignments of reliability and confidence scores that reflect the overall strength of the assessment are discussed. This skin sensitization protocol supports the implementation and acceptance of in silico approaches for the prediction of skin sensitization.

An Integrated Decision-tree Testing Strategy for Skin Sensitisation with Respect to the Requirements of the EU REACH Legislation

This report presents some of the results of a joint research project, sponsored by Defra and conducted by FRAME and Liverpool John Moores University, on the status of alternatives to animal testing with regard to the European Union REACH (Registration, Evaluation and Authorisation of Chemicals) system for the safety testing and risk assessment of chemicals. The project covered all the main toxicity endpoints associated with the REACH system. This report focuses on the use of alternative (non-animal) methods (both in vitro and in silico) for skin sensitisation testing. The manuscript reviews in vitro tests based on protein-ligand binding, dendritic/Langerhans cells and T-lymphocyte activation, and also the QSAR models and expert systems available for this endpoint. These tests are then incorporated into an integrated, decision-tree testing strategy, which also includes the Local Lymph Node Assay (in its original and new reduced protocols) and the traditional guinea-pig tests (which should only be used as a last resort). The aim of the strategy is to minimise the use of animals in testing for skin sensitisation, while satisfying the scientific and logistical demands of the EU REACH legislation.

A review of the electrophilic reaction chemistry involved in covalent DNA binding

The need to assess the ability of a chemical to act as a mutagen or a genotoxic carcinogen (collectively termed genotoxicity) is one of the primary requirements in regulatory toxicology. Several pieces of legislation have led to an increased interest in the use of in silico methods, specifically the formation of chemical categories for the assessment of toxicological endpoints. A key step in the development of chemical categories for genotoxicity is defining the organic chemistry associated with the formation of a covalent bond between DNA and an exogenous chemical. This organic chemistry is typically defined as structural alerts. To this end, this article has reviewed the literature defining the structural alerts associated with covalent DNA binding. Importantly, this review article also details the mechanistic organic chemistry associated with each of the structural alerts. This information is extremely important in terms of meeting regulatory requirements for the acceptance of the chemical category approach. The structural alerts and associated mechanistic chemistry have been incorporated into the Organisation for Economic Co-operation and Development (OECD) (Q)SAR Application Toolbox.

Characterisation, Evaluation and Possible Validation of In Silico Models for Toxicity: Determining if a Prediction is Valid

This chapter describes the process whereby a (Q)SAR may be described, evaluated and, where possible, validated. The emphasis here is not to develop models, but to characterise them according to the guidance supplied by the Organisation for Economic Co-operation and Development (OECD) and the European Chemicals Agency (EChA). The backbone to this process are the OECD Principles for the Validation of (Q)SARs. Three case studies illustrating how to approach the OECD Principles are supplied.

Electrophilic reaction chemistry of low molecular weight respiratory sensitizers

Certain types of low molecular weight chemicals have the ability to cause respiratory sensitization via haptenation of carrier proteins. It has been suggested that such chemicals must contain multiple "reactive" functional groups to elicit an immune response. In contrast to the well-developed electrophilic reaction chemistry ideas detailing the initial haptenation event for skin sensitization, no detailed mechanistic chemistry analysis has been performed for respiratory sensitization. The aim of this study, therefore, was to perform an electrophilic reaction chemistry analysis to explain the differing respiratory sensitizing potentials of 16 chemicals containing both single and multiple functional groups. The analysis has been supported by quantum chemical calculations probing the electrophilicities of the reactive chemicals. These calculations suggest that within each mechanistic category differing "reactivity thresholds" exist that must be passed for respiratory sensitization to occur. In addition, this study highlights how such mechanistically driven category formation could be used as an in silico hazard identification tool.

Prediction of skin sensitization potential using D-optimal design and GA-kNN classification methods

Modelling of skin sensitization data of 255 diverse compounds and 450 calculated descriptors was performed to develop global predictive classification models that are applicable to whole chemical space. With this aim, we employed two automated procedures, (a) D-optimal design to select optimal members of the training and test sets and (b) k-Nearest Neighbour classification (kNN) method along with Genetic Algorithms (GA-kNN Classification) to select significant and independent descriptors in order to build the models. This methodology helped us to derive multiple models, M1-M5, that are stable and robust. The best among them, model M1 (CCR(train) = 84.3%, CCR(test) = 87.2% and CCR(ext) = 80.4%), is based on six neighbours and nine descriptors and further suggests that: (a) it is stable and robust and performs better than the reported models in literature, and (b) the combination of D-optimal design and GA-kNN classification approach is a very promising approach. Consensus prediction based on the models M1-M5 improved the CCR of training, test and external validation datasets by 3.8%, 4.45% and 3.85%, respectively, over M1. From the analysis of the physical meaning of the selected descriptors, it is inferred that the skin sensitization potential of small organic compounds can be accurately predicted using calculated descriptors that code for the following fundamental properties: (i) lipophilicity, (ii) atomic polarizability, (iii) shape, (iii) electrostatic interactions, and (iv) chemical reactivity.

The use of Mechanisms and Modes of Toxic Action in Integrated Testing Strategies: The Report and Recommendations of a Workshop held as part of the European Union OSIRIS Integrated Project

This report on The Potential of Mode of Action (MoA) Information Derived from Non-testing and Screening Methodologies to Support Informed Hazard Assessment, resulted from a workshop organised within OSIRIS (Optimised Strategies for Risk Assessment of Industrial Chemicals through Integration of Non-test and Test Information), a project partly funded by the EU Commission within the Sixth Framework Programme. The workshop was held in Liverpool, UK, on 30 October 2008, with 35 attendees. The goal of the OSIRIS project is to develop integrated testing strategies (ITS) fit for use in the REACH system, that would enable a significant increase in the use of non-testing information for regulatory decision making, and thus minimise the need for animal testing. One way to improve the evaluation of chemicals may be through categorisation by way of mechanisms or modes of toxic action. Defining such groups can enhance read-across possibilities and priority settings for certain toxic modes or chemical structures responsible for these toxic modes. Overall, this may result in a reduction of in vivo testing on organisms, through combining available data on mode of action and a focus on the potentially most-toxic groups. In this report, the possibilities of a mechanistic approach to assist in and guide ITS are explored, and the differences between human health and environmental areas are summarised.

Assuring Consumer Safety without Animal Testing: A Feasibility Case Study for Skin Sensitisation

Allergic Contact Dermatitis (ACD; chemical-induced skin sensitisation) represents a key consumer safety endpoint for the cosmetics industry. At present, animal tests (predominantly the mouse Local Lymph Node Assay) are used to generate skin sensitisation hazard data for use in consumer safety risk assessments. An animal testing ban on chemicals to be used in cosmetics will come into effect in the European Union (EU) from March 2009. This animal testing ban is also linked to an EU marketing ban on products containing any ingredients that have been subsequently tested in animals, from March 2009 or March 2013, depending on the toxicological endpoint of concern. Consequently, the testing of cosmetic ingredients in animals for their potential to induce skin sensitisation will be subject to an EU marketing ban, from March 2013 onwards. Our conceptual framework and strategy to deliver a non-animal approach to consumer safety risk assessment can be summarised as an evaluation of new technologies (e.g. ‘omics’, informatics), leading to the development of new non-animal ( in silico and in vitro) predictive models for the generation and interpretation of new forms of hazard characterisation data, followed by the development of new risk assessment approaches to integrate these new forms of data and information in the context of human exposure. Following the principles of the conceptual framework, we have been investigating existing and developing new technologies, models and approaches, in order to explore the feasibility of delivering consumer safety risk assessment decisions in the absence of new animal data. We present here our progress in implementing this conceptual framework, with the skin sensitisation endpoint used as a case study.

An Integrated Decision-tree Testing Strategy for Skin Sensitisation with Respect to the Requirements of the EU REACH Legislation

This report presents some of the results of a joint research project, sponsored by Defra and conducted by FRAME and Liverpool John Moores University, on the status of alternatives to animal testing with regard to the European Union REACH (Registration, Evaluation and Authorisation of Chemicals) system for the safety testing and risk assessment of chemicals. The project covered all the main toxicity end-points associated with the REACH system. This report focuses on the use of alternative (non-animal) methods (both in vitro and in silico) for skin sensitisation testing. The manuscript reviews in vitro tests based on protein-ligand binding, dendritic/Langerhans cells and T-lymphocyte activation, and also the QSAR models and expert systems available for this endpoint. These tests are then incorporated into an integrated, decision-tree testing strategy, which also includes the Local Lymph Node Assay (in its original and new reduced protocols) and the traditional guinea-pig tests (which should only be used as a last resort). The aim of the strategy is to minimise the use of animals in testing for skin sensitisation, while satisfying the scientific and logistical demands of the EU REACH legislation.

Identification of mechanisms of toxic action for skin sensitisation using a SMARTS pattern based approach

Skin sensitisation is a key endpoint under REACH as it is costly and its assessment currently has a high dependency on animal testing. In order to reduce both the cost and the numbers of animals tested, it is likely that (quantitative) structure-activity relationships ((Q)SAR) and read-across methods will be utilised as part of intelligent testing strategies. The majority of skin sensitisers elicit their effect via covalent bond formation with skin proteins. These reactions have been understood in terms of well defined nucleophilic-electrophilic reaction chemistry. Thus, a first step in (Q)SAR analysis is the assignment of a chemical's potential mechanism of action enabling it to be placed in an appropriate reactivity domain. The aim of this study was to design a series of SMARTS patterns capable of defining these reactivity domains. This was carried out using a large database of local lymph node assay (LLNA) results that had had potential mechanisms of action assigned to them using expert knowledge. A simple algorithm was written enabling the SMARTS patterns to be used to screen a database of SMILES strings. The SMARTS patterns were then evaluated using a second, smaller, test set of LLNA results which had also had potential mechanisms of action assigned by experts. The results showed that the SMARTS patterns provided an excellent method of identifying potential electrophilic mechanisms. The findings are supported, in part, by molecular orbital calculations which confirm assignment of reactive mechanism of action. The ability to define a chemical's potential reaction mechanism is likely to be of significant benefit to regulators and risk assessors as it enables category formation and subsequent read-across to be performed.

Allergic contact dermatitis--formation, structural requirements, and reactivity of skin sensitizers

Contact allergy is caused by a wide range of chemicals after skin contact. Its clinical manifestation, allergic contact dermatitis (ACD), is developed upon repeated contact with the allergen. This perspective focuses on two areas that have yielded new useful information during the last 20 years: (i) structure-activity relationship (SAR) studies of contact allergy based on the concept of hapten-protein binding and (ii) mechanistic investigations regarding activation of nonsensitizing compounds to contact allergens by air oxidation or skin metabolism. The second area is more thoroughly reviewed since the full picture has previously not been published. Prediction of the sensitizing capacity of a chemical is important to avoid outbreaks of ACD in the population. Much research has been devoted to the development of in vitro and in silico predictive testing methods. Today, no method exists that is sensitive enough to detect weak allergens and that is robust enough to be used for routine screening. To cause sensitization, a chemical must bind to macromolecules (proteins) in the skin. Expert systems containing information about the relationship between the chemical structure and the ability of chemicals to haptenate proteins are available. However, few designed SAR studies based on mechanistic investigations of prohaptens have been published. Many compounds are not allergenic themselves but are activated in the skin (e.g., metabolically) or before skin contact (e.g., via air oxidation) to form skin sensitizers. Thus, more basic research is needed on the chemical reactions involved in the antigen formation and the immunological mechanisms. The clinical importance of air oxidation to activate nonallergenic compounds has been demonstrated. Oxidized fragrance terpenes, in contrast to the pure terpenes, gave positive patch test reactions in consecutive dermatitis patients as frequently as the most common standard allergens. This shows the importance of using compounds to which people are exposed when screening for ACD in dermatology clinics.

An evaluation of selected global (Q)SARs/expert systems for the prediction of skin sensitisation potential

Skin sensitisation potential is an endpoint that needs to be assessed within the framework of existing and forthcoming legislation. At present, skin sensitisation hazard is normally identified using in vivo test methods, the favoured approach being the local lymph node assay (LLNA). This method can also provide a measure of relative skin sensitising potency which is essential for assessing and managing human health risks. One potential alternative approach to skin sensitisation hazard identification is the use of (Quantitative) structure activity relationships ((Q)SARs) coupled with appropriate documentation and performance characteristics. This represents a major challenge. Current thinking is that (Q)SARs might best be employed as part of a battery of approaches that collectively provide information on skin sensitisation hazard. A number of (Q)SARs and expert systems have been developed and are described in the literature. Here we focus on three models (TOPKAT, Derek for Windows and TOPS-MODE), and evaluate their performance against a recently published dataset of 211 chemicals. The current strengths and limitations of one of these models is highlighted, together with modifications that could be made to improve its performance. Of the models/expert systems evaluated, none performed sufficiently well to act as a standalone tool for hazard identification.