Review of QSAR Models and Software Tools for Predicting of Genotoxicity and Carcinogenicity

This review of QSARs for genotoxicity and carcinogenicity was performed in a broad sense, considering both models available in software tools and models that are published in the literature. The review considered the potential applicability of diverse models to pesticides as well as to other types of regulated chemicals and pharmaceuticals. The availability of models and information on their applicability is summarised in tables, and a range of illustrative or informative examples are described in more detail in the text. In many cases, promising models were identified but they are still at the research stage. For routine application in a regulatory setting, further efforts will be needed to explore the applicability of such models for specific purposes, and to implement them in a practically useful form (i.e. user-friendly software). It is also noted that a range of software tools are research tools suitable for model development, and these require more specialised expertise than other tools that are aimed primarily at end-users such as risk assessors. It is concluded that the most useful models are those which are implemented in software tools and associated with transparent documentation on the model development and validation process. However, it is emphasised that the assessment of model predictions requires a reasonable amount of QSAR knowledge, even if it is not necessary to be a QSAR practitioner.JRC.DG.I.6-Systems toxicolog

The Applicability of Software Tools for Genotoxicity and Carcinogenicity Prediction: Case Studies relevant to the Assessment of Pesticides

This report presents research results obtained in the framework of a project on the Applicability of Quantitative Structure-Activity Relationship (QSAR) analysis in the evaluation of the toxicological relevance of metabolites and degradates of pesticide active substances. During this project, which was funded by the European Food Safety Authority (EFSA), the Joint Research Centre (JRC) performed several investigations to evaluate the comparative performance of selected software tools for genotoxicity and carcinogenicity prediction, and to develop a number of case studies to illustrate the opportunities and difficulties arising in the computational assessment of pesticides. This exercise also included an investigation of the chemical space of several pesticides datasets. The results indicate that different software tools have different advantages and disadvantages, depending on the specific requirements of the user / risk assessor. It is concluded that further work is needed to develop acceptance criteria for specific regulatory applications (e.g. evaluation of pesticide metabolites) and to develop batteries of models fulfilling such criteria.JRC.DG.I.6-Systems toxicolog

A Framework for assessing in silico Toxicity Predictions: Case Studies with selected Pesticides

In the regulatory assessment of chemicals, the use of in silico prediction methods such as (quantitative) structure-activity relationship models ([Q]SARs), is increasingly required or encouraged, in order to increase the efficiency and effectiveness of the risk assessment process, and to minimise the reliance on animal testing. The main question for the assessor concerns the usefulness of the prediction approach, which can be broken down into the practical applicability of the method and the adequacy of the predictions. A framework for assessing and documenting (Q)SAR models and their predictions has been established at the European and international levels. Exactly how the framework is applied in practice will depend on the provisions of the specific legislation and the context in which the non-testing data are being used. This report describes the current framework for documenting (Q)SAR models and their predictions, and discuses how it might be built upon to provide more detailed guidance on the use of (Q)SAR predictions in regulatory decision making. The proposed framework is illustrated by using selected pesticide active compounds as examples.JRC.DG.I.6-Systems toxicolog

The Use of Computational Methods in the Toxicological Assessment of Chemicals in Food: Current Status and Future Prospects

A wide range of chemicals are intentionally added to, or unintentially found in, food products, often in very small amounts. Depending on the situation, the experimental data needed to complete a dietary risk assessment, which is the scientific basis for protecting human health, may not be available or obtainable, for reasons of cost, time and animal welfare. For example, toxicity data are often lacking for the metabolites and degradation products of pesticide active ingredients. There is therefore an interest in the development and application of efficient and effective non-animal methods for assessing chemical toxicity, including Quantitative Structure-Activity Relationship (QSAR) models and related computational methods. This report gives an overview of how computational methods are currently used in the field of food safety by national regulatory bodies, international advisory organisations and the food industry. On the basis of an international survey, a comprehensive literature review and a detailed QSAR analysis, a range of recommendations are made with the long-term aim of promoting the judicious use of suitable QSAR methods. The current status of QSAR methods is reviewed not only for toxicological endpoints relevant to dietary risk assessment, but also for Absorption, Distribution, Metabolism and Excretion (ADME) properties, which are often important in discriminating between the toxicological profiles of parent compounds and their reaction products. By referring to the concept of the Threshold of Toxicological Concern (TTC), the risk assessment context in which QSAR methods can be expected to be used is also discussed. This Joint Research Centre (JRC) Reference Report provides a summary and update of the findings obtained in a study carried out by the JRC under the terms of a contract awarded by the European Food Safety Authority (EFSA).JRC.DG.I.6-Systems toxicolog

Testing the thresholds of toxicological concern values using a new database for food-related substances.

Abstract The Threshold of Toxicological Concern (TTC) concept integrates data on exposure, chemical structure, toxicity and metabolism to identify a safe exposure threshold value for chemicals with insufficient toxicity data for risk assessment. The TTC values were originally derived from a non-cancer dataset of 613 compounds with a potentially small domain of applicability. There is interest to test whether the TTC values are applicable to a broader range of substances, particularly relevant to food safety using EFSA's new OpenFoodTox database. After exclusion of genotoxic compounds, organophosphates or carbamates or those belonging to the TTC exclusion categories, the remaining 329 substances in the EFSA OpenFoodTox database were categorized under the Cramer decision tree, into low (Class I), moderate (II), or high (III) toxicity profile. For Cramer Classes I and III the threshold values were 1000 μg/person per day (90% confidence interval: 187–2190) and 87 μg/person per day (90% confidence interval: 60–153), respectively, compared to the corresponding original threshold values of 1800 and 90 μg/person per day. This confirms the applicability of the TTC values to substances relevant to food safety. Cramer Class II was excluded from our analysis because of containing too few compounds. Comparison with the Globally Harmonized System of classification confirmed that the Cramer classification scheme in the TTC approach is conservative for substances relevant to food safety

Safety assessment of titanium dioxide (E171) as a food additive

Acknowledgements: The Panel wishes to thank the following for the support provided to this scientific output: Ana Campos Fernandes, Laura Ciccolallo, Esraa Elewa, Galvin Eyong, Christina Kyrkou, Irene Munoz, Giorgia Vianello, the members of the SCER Cross-cutting WG nanotechnologies: Jacqueline Castenmiller, Mohammad Chaudhry, Roland Franz, David Gott, Stefan Weigel and the former member of the SCER Cross-cutting WG Genotoxicity Maciej Stepnik. The FAF Panel wishes to acknowledge all European competent institutions, Member State bodies and other organisations that provided data for this scientific output.Peer reviewedPublisher PD

Guidance on the use of the Threshold of Toxicological Concern approach in food safety assessment

Peer reviewedPublisher PD

In silico toxicology protocols

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information

QSAR and Metabolic Assessment Tools in the Assessment of Genotoxicity

In this chapter, a range of computational tools for applying (Q)SAR and grouping/read-across methods are described, and their integrated use in the computational assessment of genotoxicity is illustrated through the application of selected tools to two case-study compounds - 2-amino-9H-pyrido[2,3-b]indole (AaC) and 2-aminoacetophenone (2-AAP). The first case study compound (AaC) is an environment pollutant and a food contaminant that can be formed during the cooking of protein-rich food. The second case study compound (2-AAP) is a naturally occurring compound in certain foods and also proposed for use as a flavouring agent. The overall aim is to describe and illustrate a possible way of combining different information sources and software tools for genotoxicity and metabolism prediction by means of a simple stepwise approach. The chapter is aimed at researchers and assessors who have a basic knowledge of computational toxicology and some familiarity with the practical use of computational tools. The emphasis is on how to evaluate the data generated by multiple tools, rather than the practical use of any specific tool.JRC.I.5-Systems Toxicolog

Guidance document on the impact of water treatment processes on residues of active substances or their metabolites in water abstracted for the production of drinking water

Abstract This guidance document provides a tiered framework for risk assessors and facilitates risk managers in making decisions concerning the approval of active substances (AS) that are chemicals in plant protection products (PPPs) and biocidal products, and authorisation of the products. Based on the approaches presented in this document, a conclusion can be drawn on the impact of water treatment processes on residues of the AS or its metabolites in surface water and/or groundwater abstracted for the production of drinking water, i.e. the formation of transformation products (TPs). This guidance enables the identification of actual public health concerns from exposure to harmful compounds generated during the processing of water for the production of drinking water, and it focuses on water treatment methods commonly used in the European Union (EU). The tiered framework determines whether residues from PPP use or residues from biocidal product use can be present in water at water abstraction locations. Approaches, including experimental methods, are described that can be used to assess whether harmful TPs may form during water treatment and, if so, how to assess the impact of exposure to these water treatment TPs (tTPs) and other residues including environmental TPs (eTPs) on human and domesticated animal health through the consumption of TPs via drinking water. The types of studies or information that would be required are described while avoiding vertebrate testing as much as possible. The framework integrates the use of weight‐of‐evidence and, when possible alternative (new approach) methods to avoid as far as possible the need for additional testing