Chemical categories for health hazard identification: a feasibility study

Open Source Tools for Read-Across and Category Formation

In this chapter, the requirements and challenges for computational tools to support category formation and read-across are summarised. A brief overview of the open source, open data and open standards approaches in chemoinformatics are presented. The opportunities offered by these kinds of “openness” are highlighted, with emphasis on open source applications specifically developed to address challenges posed by the REACH regulation. Structural similarity assessment is currently a common practice in forming categories and applying read-across, and in developing and validating (Q)SARs. The Toxmatch software provides several endpoint-specific similarity measures, with descriptors selected using a training set in combination with data mining methods. The Toxtree software implements several classification schemes for predicting various endpoints and relies primarily on chemical structure, metabolic pathways, physico-chemical properties and descriptors, calculated from chemical structure. In addition to making predictions for individual chemicals, Toxtree can be used to profile the toxicological hazard or mechanistic group of a set of chemicals. Ambit is anopen source software for chemoinformatics data management, which allows storage of a large number of chemical structures and toxicological data and provides a flexible means for exploration of structural and similarity spaces. Several examples of the application of read-across, initiated by an expert-defined search strategy and supported by Ambit search functionalities are described.

How can structural similarity analysis help in category formation?

Chemical category is a regulatory concept facilitating filling safety data gaps. Practically, all chemical management programs like the OECD HPV Program, EU REACH, or the Canadian DSL Categorization are planning to use or are already using categorization approaches to reduce resources including animal testing. The aim of the study was to discuss the feasibility to apply computational structural similarity methods to augment formation of a category. The article discusses also how this understanding can be translated into computer readable format, an ultimate need for practical, broad scope applications. We conclude that for the skin sensitization endpoint, used as a working example, mechanistic understanding expressed as chemical reactivity can be exploited by computational structural similarity methods to augment category formation process. We propose a novel method, atom environments ranking (AER), to assess similarity to a reference training set representing a common mechanism of action, as a potential method for grouping chemicals into reactivity domains.

Review of the toxicity of chemical mixtures: Theory, policy, and regulatory practice

An analysis of current mixture theory, policy, and practice was conducted by examining standard reference texts, regulatory guidance documents, and journal articles. Although this literature contains useful theoretical concepts, clear definitions of most terminology, and well developed protocols for study design and statistical analysis, no general theoretical basis for the mechanisms and interactions of mixture toxicity could be discerned. There is also a poor understanding of the relationship between exposure-based and internal received dose metrics. This confounds data interpretation and limits reliable determinations of the nature and extent of additivity. The absence of any generally accepted classification scheme for either modes/mechanisms of toxic action or of mechanisms of toxicity interactions is problematic as it produces a cycle in which research and policy are interdependent and mutually limiting. Current regulatory guidance depends heavily on determination of toxicological similarity concluded from the presence of a few prominent constituents, assumed from a common toxicological effect, or presumed from an alleged similar toxic mode/mechanism. Additivity, or the lack of it, is largely based on extrapolation of existing knowledge for single chemicals in this context. Thus, regulatory risk assessment protocols lack authoritative theoretical underpinnings, creating substantial uncertainty. Development of comprehensive classification schemes for modes/mechanisms of toxic action and mechanisms of interaction is needed to ensure a sound theoretical foundation for mixture-related regulatory activity and provide a firm basis for iterative hypothesis development and experimental testing.

A paradigm for determining the relevance of short-term assays: application to oxidative mutagenesis

A simple substructure-based approach was developed to determine whether a short-term assay under development is related mechanistically to the endpoint it seeks to predict. Thus, substructures associated with mutagenicity in Salmonella are also present in carcinogens and agents active in other mutagenicity and genotoxicity assays. When applied to test results obtained with an Escherichia coli strain designed to identify oxidative mutagens, there was no significant association with either carcinogens or mutagens and genotoxicants detected by other systems. There was, however, a significant association between alerts for oxidative mutagenesis and chemicals capable of inducing allergic contact dermatitis (ACD) in humans.