TKPlate 1.0: An Open-access platform for toxicokinetic and toxicodynamic modelling of chemicals to implement new approach methodologies in chemical risk assessment.

This publication is linked to the following EFSA Supporting Publications articles: http://onlinelibrary.wiley.com/doi/10.

Scientific opinion on the renewal of the authorisation of Fumokomp (SF-009) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product Fumokomp (SF-009), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003 (in the renewal application the Primary Product is reported as 'Fumokomp Conc.'). This opinion refers to an assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product.

Scientific opinion on the renewal of the authorisation of Scansmoke SEF7525 (SF-004) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product Scansmoke SEF7525 (SF-004), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. Scansmoke SEF7525 is obtained from a tar produced from a mixture of red oak, white oak, maple, beech and hickory.

Machine learning - based q-RASAR modeling to predict acute contact toxicity of binary organic pesticide mixtures in honey bees.

We have reported here a quantitative read-across structure-activity relationship (q-RASAR) model for the prediction of binary mixture toxicity (acute contact toxicity) in honey bees. Both the quantitative structure-activity relationship (QSAR) and the similarity-based read-across algorithms are used simultaneously for enhancing the predictability of the model. Several similarity and error-based parameters, obtained from the read-across prediction tool, have been put together with the structural and physicochemical descriptors to develop the final q-RASAR model.

The VEGA Tool to Check the Applicability Domain Gives Greater Confidence in the Prediction of In Silico Models.

A sound assessment of in silico models and their applicability domain can support the use of new approach methodologies (NAMs) in chemical risk assessment and requires increasing the users' confidence in this approach. Several approaches have been proposed to evaluate the applicability domain of such models, but their prediction power still needs a thorough assessment. In this context, the VEGA tool capable of assessing the applicability domain of in silico models is examined for a range of toxicological endpoints.

OECD harmonised template 201: Structuring and reporting mechanistic information to foster the integration of new approach methodologies for hazard and risk assessment of chemicals.

In the European Union, the Chemicals Strategy for Sustainability (CSS) highlights the need to enhance the identification and assessment of substances of concern while reducing animal testing, thus fostering the development and use of New Approach Methodologies (NAMs) such as in silico, in vitro and in chemico. In the United States, the Tox21 strategy aims at shifting toxicological assessments away from traditional animal studies towards target-specific, mechanism-based and biological observations mainly obtained by using NAMs. Many other jurisdictions around the world are also increasing the use of NAMs.

The use of new approach methodologies for the environmental risk assessment of food and feed chemicals.

New Approach Methodologies (NAMs) provide tools for supporting both human and environmental risk assessment (HRA and ERA). This short review provides recent insights regarding the use of NAMs in ERA of food and feed chemicals. We highlight the usefulness of tiered methods supporting weight-of-evidence approaches in relation to problem formulation (i.

Lethal, sublethal, and combined effects of pesticides on bees: A meta-analysis and new risk assessment tools.

Multiple stressors threaten bee health, a major one being pesticides. Bees are simultaneously exposed to multiple pesticides that can cause both lethal and sublethal effects. Risk assessment and most research on bee health, however, focus on lethal individual effects.

A regression-based QSAR-model to predict acute toxicity of aromatic chemicals in tadpoles of the Japanese brown frog (Rana japonica): Calibration, validation, and future developments to support risk assessment of chemicals in amphibians.

Amphibian populations are undergoing a global decline worldwide. Such decline has been attributed to their unique physiology, ecology, and exposure to multiple stressors including chemicals, temperature, and biological hazards such as fungi of the Batrachochytrium genus, viruses such as Ranavirus, and habitat reduction. There are limited toxicity data for chemicals available for amphibians and few quantitative structure-activity relationship (QSAR) models have been developed and are publicly available.

In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives.

This chapter aims to introduce the reader to the basic principles of environmental risk assessment of chemicals and highlights the usefulness of tiered approaches within weight of evidence approaches in relation to problem formulation i.e., data availability, time and resource availability.

QSAR models for soil ecotoxicity: Development and validation of models to predict reproductive toxicity of organic chemicals in the collembola Folsomia candida.

Soil pollution is a critical environmental challenge: the substances released in the soil can adversely affect humans and the ecosystem. Several bioassays were developed to investigate the soil ecotoxicity of chemicals with soil microbes, plants, invertebrates and vertebrates. The 28-day collembolan reproduction test with the springtail Folsomia candida is a recently introduced bioassay described by OECD guideline 232.

Integrating QSAR models predicting acute contact toxicity and mode of action profiling in honey bees (A. mellifera): Data curation using open source databases, performance testing and validation.

Honey bees (Apis mellifera) provide key ecosystem services as pollinators bridging agriculture, the food chain and ecological communities, thereby ensuring food production and security. Ecological risk assessment of single Plant Protection Products (PPPs) requires an understanding of the exposure and toxicity. In silico tools such as QSAR models can play a major role for the prediction of structural, physico-chemical and pharmacokinetic properties of chemicals as well as toxicity of single and multiple chemicals.

Pesticides, cosmetics, drugs: identical and opposite influences of various molecular features as measures of endpoints similarity and dissimilarity.

The similarity is an important category in natural sciences. A measure of similarity for a group of various biochemical endpoints is suggested. The list of examined endpoints contains (1) toxicity of pesticides towards rainbow trout; (2) human skin sensitization; (3) mutagenicity; (4) toxicity of psychotropic drugs; and (5) anti HIV activity.

The using of the Index of Ideality of Correlation (IIC) to improve predictive potential of models of water solubility for pesticides.

Models for water solubility of pesticides suggested in this manuscript are important data from point of view of ecologic engineering. The Index of Ideality of Correlation (IIC) of groups of quantitative structure-property relationships (QSPRs) for water solubility of pesticides related to the calibration sets was used to identify good in silico models. This comparison confirmed the high IIC set provides better statistical quality of the model for the validation set.

Exploring QSAR modeling of toxicity of chemicals on earthworm.

Earthworm provides sustainability towards the agroecosystem which can be degraded day by day by the extensive use of pesticides (e.g., fungicides, insecticides and herbicides).

Predicting acute contact toxicity of organic binary mixtures in honey bees (A. mellifera) through innovative QSAR models.

Pollinators such as honey bees are of considerable importance, because of the crucial pollination services they provide for food crops and wild plants. Since bees are exposed to a wide range of multiple chemicals "mixtures" both of anthropogenic (e.g.

First report on a classification-based QSAR model for chemical toxicity to earthworm.

As the use of the pesticides has increased extensively in the farming fields to have a better agricultural production, the negative impacts of such use have also increased exponentially. Hence, the toxic effects of pesticides along with the targeted organisms affect the non-targeted terrestrial organisms such as earthworm. Therefore, in the present work, we have developed a classification-based quantitative structure-activity relationship (QSAR) model using linear discriminant analysis (LDA) to capture the specific information of pesticides / diverse chemicals in order to determine the structural information responsible for toxicity manifestation towards the non-targeted organism, i.

Investigating combined toxicity of binary mixtures in bees: Meta-analysis of laboratory tests, modelling, mechanistic basis and implications for risk assessment.

Bees are exposed to a wide range of multiple chemicals "chemical mixtures" from anthropogenic (e.g. plant protection products or veterinary products) or natural origin (e.

Vector-borne diseases.

After a request from the European Commission, EFSA's Panel on Animal Health and Welfare summarised the main characteristics of 36 vector-borne diseases (VBDs) in https://efsa.maps.arcgis.

Scientific and technical assistance concerning the survival, establishment and spread of (Bsal) in the EU.

A new fungus, (Bsal), was identified in wild populations of salamanders in the Netherlands and Belgium, and in kept salamander populations in Germany and the United Kingdom. EFSA assessed the potential of Bsal to affect the health of wild and kept salamanders in the EU, the effectiveness and feasibility of a movement ban of traded salamanders, the validity, reliability and robustness of available diagnostic methods for Bsal detection, and possible alternative methods and feasible risk mitigation measures to ensure safe international and EU trade of salamanders and their products. Bsal was isolated and characterised in 2013 from a declining fire salamander () population in the Netherlands.