A C. elegans Screening Platform for the Rapid Assessment of Chemical Disruption of Germline Function

Background: Despite the developmental impact of chromosome segregation errors, we lack the tools to assess environmental effects on the integrity of the germline in animals. Objectives: We developed an assay in Caenorhabditis elegans that fluorescently marks aneuploid embryos after chemical exposure. Methods: We qualified the predictive value of the assay against chemotherapeutic agents as well as environmental compounds from the ToxCast Phase I library by comparing results from the C. elegans assay with the comprehensive mammalian in vivo end point data from the ToxRef database. Results: The assay was highly predictive of mammalian reproductive toxicities, with a 69% maximum balanced accuracy. We confirmed the effect of select compounds on germline integrity by monitoring germline apoptosis and meiotic progression. Conclusions: This C. elegans assay provides a comprehensive strategy for assessing environmental effects on germline function

Disruption of VEGFR signaling leading to developmental defects

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QSAR models of human data can enrich or replace LLNA testing for human skin sensitization

An example of structural transformation of human skin sensitizers into various non-sensitizers based on interpretation of QSAR models

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation

DESENVOLVIMENTO DE MÉTODOS COMPUTACIONAIS COMO ALTERNATIVA AO USO DE ANIMAIS PARA AVALIAÇÃO DA SENSIBILIZAÇÃO DA PELE

Introdução e objetivos: Métodos computacionais têm ganhado crescente destaque nas últimas décadas devido ao sucesso na avaliação de substancias que carecem de dados experimentais.1 O objetivo deste trabalho é desenvolver um método computacional capaz de predizer corretamente o potencial sensibilizador de compostos químicos na pele humana, como método alternativo ao uso de animais. Metodologia: Foi compilado e preparado o maior conjunto de dados publicamente disponível para sensibilização de pele humana e murina, contendo 135 compostos. A dose por unidade de área que induz 5% de resposta positiva (DSA05) em pele humana foi comparada com a concentração capaz de estimular em três vezes a proliferação de linfócitos nos linfonodos de camundongos (EC3). Modelos de relação quantitativa entre estrutura e atividade (QSAR) para pele humana foram gerados usando-se vários descritores moleculares e algorítmo SVM. Resultados e discussões: A concordância entre os dados de pele humana e de camundongos é de apenas 62%. Modelos de consenso que integram os modelos individuais de QSAR mostraram cobertura de até 75% e acurácia balanceada externa de até 70%. A triagem virtual de uma quimioteca de compostos comumente usados em cosméticos (COSMOS DB) identificou 175 possíveis compostos sensibilizadores. A análise de agrupamentos hierárquicos e interpretação dos modelos através dos descritores mais significativos revelou grupamentos moleculares responsáveis pela sensibilização da pele. Conclusões: A análise da sobreposição de dados revelou que o modelo animal considerado padrão-ouro falha em casos específicos para predição da toxicidade dérmica em seres humanos. Os modelos de QSAR gerados se mostraram superiores na predição de sensibilizadores em pele humana, quando comparados ao ensaio in vivo “padrão-ouro”, possibilitando seu uso em estratégias integradas de teste, contribuindo para redução do uso de animais em laboratório. Agradecimentos: Fundação de Amparo à Pesquisa do Estado de Goiás, Conselho Nacional de Pesquisa e Desenvolvimento, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior.Palavras-Chave: sensibilização da pele; QSAR; toxicidade; triagem virtual

Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R2=0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q2ext = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential

Environmental Impact on Vascular Development Predicted by High-Throughput Screening

Background: Understanding health risks to embryonic development from exposure to environmental chemicals is a significant challenge given the diverse chemical landscape and paucity of data for most of these compounds. High-throughput screening (HTS) in the U.S. Environmental Protection Agency (EPA) ToxCast™ project provides vast data on an expanding chemical library currently consisting of > 1,000 unique compounds across > 500 in vitro assays in phase I (complete) and Phase II (under way). This public data set can be used to evaluate concentration-dependent effects on many diverse biological targets and build predictive models of prototypical toxicity pathways that can aid decision making for assessments of human developmental health and disease

Current ecotoxicity testing needs among selected U.S. federal agencies

U.S. regulatory and research agencies use ecotoxicity test data to assess the hazards associated with substances that may be released into the environment, including but not limited to industrial chemicals, pharmaceuticals, pesticides, food additives, and color additives. These data are used to conduct hazard assessments and evaluate potential risks to aquatic life (e.g., invertebrates, fish), birds, wildlife species, or the environment. To identify opportunities for regulatory uses of non-animal replacements for ecotoxicity tests, the needs and uses for data from tests utilizing animals must first be clarified. Accordingly, the objective of this review was to identify the ecotoxicity test data relied upon by U.S. federal agencies. The standards, test guidelines, guidance documents, and/or endpoints that are used to address each of the agencies’ regulatory and research needs regarding ecotoxicity testing are described in the context of their application to decision-making. Testing and information use, needs, and/or requirements relevant to the regulatory or programmatic mandates of the agencies taking part in the Interagency Coordinating Committee on the Validation of Alternative Methods Ecotoxicology Workgroup are captured. This information will be useful for coordinating efforts to develop and implement alternative test methods to reduce, refine, or replace animal use in chemical safety evaluations

t4 Workshop Report: Integrated Testing Strategies (ITS) for Safety Assessment

Integrated testing strategies (ITS), as opposed to single definitive tests or fixed batteries of tests, are expected to efficiently combine different information sources in a quantifiable fashion to satisfy an information need, in this case for regulatory safety assessments. With increasing awareness of the limitations of each individual tool and the development of highly targeted tests and predictions, the need for combining pieces of evidence increases. The discussions that took place during this workshop, which brought together a group of experts coming from different related areas, illustrate the current state of the art of ITS, as well as promising developments and identifiable challenges. The case of skin sensitization was taken as an example to understand how possible ITS can be constructed, optimized and validated. This will require embracing and developing new concepts such as adverse outcome pathways (AOP), advanced statistical learning algorithms and machine learning, mechanistic validation and “Good ITS Practices”.JRC.I.5-Systems Toxicolog