Chemical Categories and Read Across

This report aims to outline and summarise some of the practical experiences from the major Regulatory agencies as well as the guidance so far developed by the OECD. Definitions for some of the common terms such as read across and chemical categories are provided. Recommendations for further work are highlighted. Regulatory use of read across/chemical category is still quite limited. A clear need, to promote greater uptake of these types of these approach, is the development of practical guidance.JRC.I.3-Toxicology and chemical substance

A Compendium of Case Studies that Helped to Shape the REACH Guidance on Chemical Categories and Read Across

This document pulls together the compendium of case studies that were conducted as part of the REACH project charged with developing technical guidance on the use and formation of chemical grouping approaches (chemical categories/read-across). The lessons and insights from each of these case studies helped to shape the technical content captured in the resulting guidance. The case studies are presented in their original form. They are grouped into two themes for ease of reference: current and prospective experiences in the formation and/or use of category approaches.JRC.I.3-Toxicology and chemical substance

A Similarity Based Approach for Chemical Category Classification

This report aims to describe the main outcomes of an IHCP Exploratory Research Project carried out during 2005 by the European Chemicals Bureau (Computational Toxicology Action). The original aim of this project was to develop a computational method to facilitate the classification of chemicals into similarity-based chemical categories, which would be both useful for building (Q)SAR models (research application) and for defining chemical category proposals (regulatory application).JRC.I-Institute for Health and Consumer Protection (Ispra

Skin Sensitisation (Q)SARs/Expert Systems: from Past, Present to Future

This review describes the state of the art of available (Q)SARs/expert systems for skin sensitisation and evaluates their utility for potential regulatory use. There is a strong mechanistic understanding with respect to skin sensitisation which has facilitated the development of different models. Most existing models fall into one of two main categories either they are local in nature, usually specific to a chemical class or reaction chemical mechanism or else they are global in form, derived empirically using statistical methods. Some of the published global QSARs available have been recently characterised and evaluated elsewhere in accordance with the OECD principles. An overview of expert systems capable of predicting skin sensitisation is also provided. Recently, a new perspective regarding the development of mechanistic skin sensitisation QSARs so-called Quantitative Mechanistic Modelling (QMM) has been proposed, where reactivity and hydrophobicity, are used as the key parameters in mathematically modelling skin sensitisation. Whilst hydrophobicity can be conveniently modelled using log P, the octanol-water partition coefficient; reactivity is less readily determined from chemical structure. Initiatives are in progress to generate reactivity data for reactions relevant to skin sensitisation but more resources are required to realise a comprehensive set of reactivity data. This is a fundamental and necessary requirement for the future assessment of skin sensitisation.JRC.I.3-Toxicology and chemical substance

The Use of Computational Methods in the Grouping and Assessment of Chemicals - Preliminary Investigations

This document presents a perspective of how computational approaches could potentially be used in the grouping and assessment of chemicals, and especially in the application of read-across and the development of chemical categories. The perspective is based on experience gained by the authors during 2006 and 2007, when the Joint Research Centre's European Chemicals Bureau was directly involved in the drafting of technical guidance on the applicability of computational methods under REACH. Some of the experience gained and ideas developed resulted from a number of research-based case studies conducted in-house during 2006 and the first half of 2007. The case studies were performed to explore the possible applications of computational methods in the assessment of chemicals and to contribute to the development of technical guidance. Not all of the methods explored and ideas developed are explicitly included in the final guidance documentation for REACH. Many of the methods are novel, and are still being refined and assessed by the scientific community. At present, many of the methods have not been tried and tested in the regulatory context. The authors therefore hope that the perspective and case studies compiled in this document, whilst not intended to serve as guidance, will nevertheless provide an input to further research efforts aimed at developing computational methods, and at exploring their potential applicability in regulatory assessment of chemicals.JRC.I.3-Toxicology and chemical substance

Chemical Similarity and Threshold of Toxicological Concern (TTC) Approaches: Report of an ECB Workshop held in Ispra, November 2005

There are many national, regional and international programmes – either regulatory or voluntary – to assess the hazards or risks of chemical substances to humans and the environment. The first step in making a hazard assessment of a chemical is to ensure that there is adequate information on each of the endpoints. If adequate information is not available then additional data is needed to complete the dataset for this substance. For reasons of resources and animal welfare, it is important to limit the number of tests that have to be conducted, where this is scientifically justifiable. One approach is to consider closely related chemicals as a group, or chemical category, rather than as individual chemicals. In a category approach, data for chemicals and endpoints that have been already tested are used to estimate the hazard for untested chemicals and endpoints. Categories of chemicals are selected on the basis of similarities in biological activity which is associated with a common underlying mechanism of action. A homologous series of chemicals exhibiting a coherent trend in biological activity can be rationalised on the basis of a constant change in structure. This type of grouping is relatively straightforward. The challenge lies in identifying the relevant chemical structural and physicochemical characteristics that enable more sophisticated groupings to be made on the basis of similarity in biological activity and hence purported mechanism of action. Linking two chemicals together and rationalising their similarity with reference to one or more endpoints has been very much carried out on an ad hoc basis. Even with larger groups, the process and approach is ad hoc and based on expert judgement. There still appears to be very little guidance about the tools and approaches for grouping chemicals systematically. In November 2005, the ECB Workshop on Chemical Similarity and Thresholds of Toxicological Concern (TTC) Approaches was convened to identify the available approaches that currently exist to encode similarity and how these can be used to facilitate the grouping of chemicals. This report aims to capture the main themes that were discussed. In particular, it outlines a number of different approaches that can facilitate the formation of chemical groupings in terms of the context under consideration and the likely information that would be required. Grouping methods were divided into one of four classes – knowledge-based, analogue-based, unsupervised, and supervised. A flowchart was constructed to attempt to capture a possible work flow to highlight where and how these approaches might be best applied.JRC.I.3-Toxicology and chemical substance

Exploratory Research Project Report - Application of the Threshold of Toxicological Concern (TTC) concept to Human Health Endpoints

The Threshold of Toxicological Concern (TTC) is a pragmatic risk assessment tool based on the principle of establishing a human exposure threshold value for all chemicals below which there is a very low probability of an appreciable risk to human health. This report outlines the main concepts associated with the TTC, how it has evolved, how it is currently applied in risk assessment, and how it could complement future risk assessments in the context of REACH. The paper begins by describing the traditional approach to risk assessment. It then outlines some of the non testing approaches such as (Q)SAR, read across, chemical categories and how these may fit into a risk assessment framework. Specific focus is made on TTC approaches and applications. Finally, the report describes the outcome of an IHCP Exploratory Research project carried out during 2005 by the European Chemicals Bureau (Computational Toxicology Action) on the subject of the TTC.JRC.I.3-Toxicology and chemical substance

Computational Methods to Predict Drug Safety

This mini review aims to outline some of the non testing approaches that are available for the purposes of predicting and assuring drug safety. Focus will be made on several endpoints of specific such as ADME properties as well as mutagenicity and carcinogenicity. The use of TTC and chemical categories approaches are presented as alternative strategies. Overall there is great potential to apply a battery of different tools in drug discovery from QSARs to TTC and chemical categories. Greater awareness of other initiatives (in parallel industries) coupled with more practical guidance on how to exploit these tools is still required before they become embedded into routine use.JRC.I.3-Toxicology and chemical substance

Mechanistic applicability domains fro non-animal based toxicological endpoints. QSAR analysis of the Schiff base applicability domain for skin sensitization

Several recent (1999 onwards) publications on skin sensitisation to aldehydes and ketones which can sensitise by covalent binding to skin protein via Schiff base formation present QSARs based on the Taft sigma* parameter to model reactivity and log P to model hydrophobicity. Here all of the data are re-analysed together in a stepwise self-consistent way using the parameters log P and sum sigma*, the latter being the sum of sigma* values for the two groups R and R’ in RCOR’. A QSAR is derived: pEC3 = 1.12(±0.07)sum of sigma* + 0.42(±0.04) log P - 0.62(±0.13); n = 16 R2 = 0.952 R2adj = 0.945 s = 0.12 F = 129.6, based on mouse local lymph node assay (LLNA) data for 11 aliphatic aldehydes, one alpha-ketoester and four alpha,beta-diketones. In developing this QSAR, an initial regression equation for a training set of ten aldehydes was found to be well predictive predict a test set consisting of the other six compounds. The QSAR is found to be well predictive for LLNA data on a series of alpha,gamma-diketones and also correctly predicts the non-sensitising properties of simple dialkylketones. It is shown to meet all the criteria of the OECD principles for applicability within regulatory practice. In view of the structural diversity within the sets of compounds considered here, the present findings confirm the view that within the mechanistic applicability domain the differences in sensitisation potential are dependent solely on differences in chemical reactivity and partitioning.JRC.I.3-Toxicology and chemical substance

Electrophilic Chemistry Related to Skin Sensitization. Reaction Mechanistic Applicability Domain Classification for a Published Data Set of 106 Chemicals Tested in the Mouse Local Lymph Node Assay

This paper presents an overview of electrophilic reaction mechanisms relevant to skin sensitization, with reference to a published skin sensitization test data set for 106 chemicals. It is shown that there is a close correspondence in the way differences and similarities in skin sensitization potency of chemicals relate to differences and similarities in their physical organic chemistry. electrophilic reaction mechanistic chemistry. The 106 chemicals are classified into their reaction mechanistic applicability domains and reactivity-sensitization trends are analysed for each domain: the Michael acceptor and pro-Michael acceptor electrophile domain; the SNAr electrophile domain; the SN2 electrophile domain; the Schiff base electrophile domain; the acyl transfer electrophile domain and the non-electrophilic non-pro-electrophilic domain. The last of these domains should be populated mainly by non-sensitizers. Classification of 87 of the 106 compounds, using these domains, was straightforward. In most of the domains and sub-domains where there are sufficient compounds, clear trends can be seen, in conformity with the RAI (Relative Alkylation Index) model, between sensitization potential and reactivity/hydrophobicity. Of the remaining 19 compounds 7 are a-X-methyl-g-lactones, which on the basis of published organic chemistry studies and guinea pig sensitization data can be classed as pro-Michael acceptors by elimination of HX, but which are mostly negative in the LLNA, indicating a difference in bioactivation capabilities between mice and guinea pigs. The other 12 compounds, whose chemistry was not immediately obvious, were found after further analysis and literature research to fit into appropriate mechanistic domains which rationalise their skin sensitizing properties.JRC.I.3-Toxicology and chemical substance