Has Toxicity Testing Moved into the 21st Century? A Survey and Analysis of Perceptions in the Field of Toxicology

Public views of animal testing and alternatives in chemical risk assessment

Next-Generation Risk Assessment (NGRA) aims to implement New Approach Methodologies (NAMs) into risk assessment and to rely on new in vivo testing in animals only as a last resort. However, various technical and regulatory hurdles impede their regulatory implementation. Assumptions about the public's expectations could act as barriers to the acceptance of NAMs. This study aimed at investigating public views of animal testing and potential alternatives, namely in vitro and in silico testing. An online survey was conducted (N = 965). The results suggest that people make trade-offs, as they experience negative affect regarding in vivo testing, which partly might explain their openness regarding certain alternatives. In vitro tests were attributed the highest ability to determine harmful effects of chemicals for different endpoints, followed by in vivo and in silico tests. Our results further showed that many people accept chemicals to be only tested with alternatives, with highest acceptance for household consumer products, food contact material or building materials and less accepting for medicines and foods. This article addresses potential challenges that might arise from public perceptions and thus, contributes to the bottom-up initiatives to overcome the hurdles to the implementation of NAMs in regulatory risk assessment.

Analyzing high-throughput assay data to advance the rapid screening of environmental chemicals for human reproductive toxicity

While high-throughput (HTP) assays have been proposed as platforms to rapidly assess reproductive toxicity, there is currently a lack of established assays that specifically address germline development/function and fertility. We assessed the applicability domains of yeast (S. cerevisiae) and nematode (C. elegans) HTP assays in toxicity screening of 124 environmental chemicals, determining their agreement in identifying toxicants and their concordance with reproductive toxicity in vivo. We integrated data generated in the two models and compared results using a streamlined, semi-automated benchmark dose (BMD) modeling approach. We then extracted and modeled relevant mammalian in vivo data available for the matching chemicals included in the Toxicological Reference Database (ToxRefDB). We ranked potencies of common compounds using the BMD and evaluated correlation between the datasets using Pearson and Spearman correlation coefficients. We found moderate to good correlation across the three data sets, with r = 0.48 (95% CI: 0.28-1.00, p<0.001) and rs = 0.40 (p=0.002) for the parametric and rank order correlations between the HTP BMDs; r = 0.95 (95% CI: 0.76-1.00, p=0.0005) and rs = 0.89 (p=0.006) between the yeast assay and ToxRefDB BMDs; and r = 0.81 (95% CI: 0.28-1.00, p=0.014) and rs = 0.75 (p=0.033) between the worm assay and ToxRefDB BMDs. Our findings underscore the potential of these HTP assays to identify environmental chemicals that exhibit reproductive toxicity. Integrating these HTP datasets into mammalian in vivo prediction models using machine learning methods could further enhance the predictive value of these assays in future rapid screening efforts.

Intuitive toxicology in the 21st century-Bridging the perspectives of the public and risk assessors in Europe

Three decades ago, several articles on the subjectivity in chemical risk judgments (i.e., labeled "intuitive toxicology") measured the divide between the public and toxicologists with different backgrounds regarding the validity of predicting health effects based on in vivo studies. Similar divides with impacts on societal discourse and chemical risk assessment practices might exist concerning alternative toxicity testing methods (i.e., in vitro and in silico). However, studies to date have focused either on the public's views of in vivo or stem cell testing or on experts' views of in vivo testing and potential alternatives (i.e., toxicologists and medical students), which do not allow for a direct investigation of potential divides. To fill this knowledge gap, we conducted two online surveys, involving members of the German-speaking public in Switzerland and European human health risk assessors, respectively. This article presents the results of these two surveys regarding the divide in the public's and risk assessors' perspectives on risk assessment based on in vivo, in vitro, and in silico testing. Particularly, the survey with the risk assessors highlights that, beyond scientific and regulatory barriers, alternatives to in vivo testing may encounter individual hurdles, such as higher uncertainty associated with them. Understanding and addressing these hurdles will be crucial to facilitate the integration of new approach methodologies into chemical risk assessment practices as well as a successful transition toward next-generation risk assessment, bringing us closer to a fit-for-purpose and more efficient regulatory landscape.

Biocidal products: Opportunities in risk assessment, management, and communication

In the coronavirus disease 2019 era, biocidal products are increasingly used for controlling harmful organisms, including microorganisms. However, assuring safety against adverse health effects is a critical issue from a public health standpoint. This study aimed to provide an overview of key aspects of risk assessment, management, and communication that ensure the safety of biocidal active ingredients and products. The inherent characteristics of biocidal products make them effective against pests and pathogens; however, they also possess potential toxicities. Therefore, public awareness regarding both the beneficial and potential adverse effects of biocidal products needs to be increased. Biocidal active ingredients and products are regulated under specific laws: the Federal Insecticide, Fungicide, and Rodenticide Act for the United States; the European Union (EU) Biocidal Products Regulation for the EU; and the Consumer Chemical Products and Biocide Safety Management Act for the Republic of Korea. Risk management also needs to consider the evidence of enhanced sensitivity to toxicities in individuals with chronic diseases, given the increased prevalence of these conditions in the population. This is particularly important for post-marketing safety assessments of biocidal products. Risk communication conveys information, including potential risks and risk-reduction measures, aimed at managing or controlling health or environmental risks. Taken together, the collaborative effort of stakeholders in risk assessment, management, and communication strategies is critical to ensuring the safety of biocidal products sold in the market as these strategies are constantly evolving.

Toxicoepigenetics for Risk Assessment: Bridging the Gap Between Basic and Regulatory Science

Toxicoepigenetics examines the health effects of environmental exposure associated with, or mediated by, changes in the epigenome. Despite high expectations, toxicoepigenomic data and methods have yet to become significantly utilized in chemical risk assessment. This article draws on a social science framework to highlight hitherto overlooked structural barriers to the incorporation of toxicoepigenetics in risk assessment and to propose ways forward. The present barriers stem not only from the lack of maturity of the field but also from differences in constraints and standards between the data produced by toxicoepigenetics and the regulatory science data that risk assessment processes require. Criteria and strategies that frame the validation of knowledge used for regulatory purposes limit the application of basic research in toxicoepigenetics toward risk assessment. First, the need in regulatory toxicology for standardized methods that form a consensus between regulatory agencies, basic research, and the industry conflicts with the wealth of heterogeneous data in toxicoepigenetics. Second, molecular epigenetic data do not readily translate into typical toxicological endpoints. Third, toxicoepigenetics investigates new forms of toxicity, in particular low-dose and long-term effects, that do not align well with the traditional framework of regulatory toxicology. We propose that increasing the usefulness of epigenetic data for risk assessment will require deliberate efforts on the part of the toxicoepigenetics community in 4 areas: fostering the understanding of epigenetics among risk assessors, developing knowledge infrastructure to demonstrate applicability, facilitating the normalization and exchange of data, and opening the field to other stakeholders.

Towards better prediction of xenobiotic genotoxicity: CometChip technology coupled with a 3D model of HepaRG human liver cells

Toxicology is facing a major change in the way toxicity testing is conducted by moving away from animal experimentation towards animal-free methods. To improve the in vitro genotoxicity assessment of chemical and physical compounds, there is an urgent need to accelerate the development of 3D cell models in high-throughput DNA damage detection platforms. Among the alternative methods, hepatic cell lines are a relevant in vitro model for studying the functions of the liver. 3D HepaRG spheroids show improved hepatocyte differentiation, longevity, and functionality compared with 2D HepaRG cultures and are therefore a relevant model for predicting in vivo responses. Recently, the comet assay was developed on 3D HepaRG cells. However, this approach is still low throughput and does not meet the challenge of evaluating the toxicity and risk to humans of tens of thousands of compounds. In this study, we evaluated the performance of the high-throughput in vitro CometChip assay on 2D and 3D HepaRG cells. HepaRG cells were exposed for 48 h to several compounds (methyl methanesulfonate, etoposide, benzo[a]pyrene, cyclophosphamide, 7,12-dimethylbenz[a]anthracene, 2-acetylaminofluorene, and acrylamide) known to have different genotoxic modes of action. The resulting dose responses were quantified using benchmark dose modelling. DNA damage was observed for all compounds except 2-AAF in 2D HepaRG cells and etoposide in 3D HepaRG cells. Results indicate that the platform is capable of reliably identifying genotoxicants in 3D HepaRG cells, and provide further insights regarding specific responses of 2D and 3D models.

Machine Learning in Predictive Toxicology: Recent Applications and Future Directions for Classification Models

In recent times, machine learning has become increasingly prominent in predictive toxicology as it has shifted from in vivo studies toward in silico studies. Currently, in vitro methods together with other computational methods such as quantitative structure-activity relationship modeling and absorption, distribution, metabolism, and excretion calculations are being used. An overview of machine learning and its applications in predictive toxicology is presented here, including support vector machines (SVMs), random forest (RF) and decision trees (DTs), neural networks, regression models, naïve Bayes, k-nearest neighbors, and ensemble learning. The recent successes of these machine learning methods in predictive toxicology are summarized, and a comparison of some models used in predictive toxicology is presented. In predictive toxicology, SVMs, RF, and DTs are the dominant machine learning methods due to the characteristics of the data available. Lastly, this review describes the current challenges facing the use of machine learning in predictive toxicology and offers insights into the possible areas of improvement in the field.

Drivers of and Obstacles to the Adoption of Toxicogenomics for Chemical Risk Assessment: Insights from Social Science Perspectives

BACKGROUND

Some 20 y ago, scientific and regulatory communities identified the potential of omics sciences (genomics, transcriptomics, proteomics, metabolomics) to improve chemical risk assessment through development of toxicogenomics. Recognizing that regulators adopt new scientific methods cautiously given accountability to diverse stakeholders, the scope and pace of adoption of toxicogenomics tools and data have nonetheless not met the ambitious, early expectations of omics proponents.

OBJECTIVE

Our objective was, therefore, to inventory, investigate, and derive insights into drivers of and obstacles to adoption of toxicogenomics in chemical risk assessment. By invoking established social science frameworks conceptualizing innovation adoption, we also aimed to develop recommendations for proponents of toxicogenomics and other new approach methodologies (NAMs).

METHODS

We report findings from an analysis of 56 scientific and regulatory publications from 1998 through 2017 that address the adoption of toxicogenomics for chemical risk assessment. From this purposeful sample of toxicogenomics discourse, we identified major categories of drivers of and obstacles to adoption of toxicogenomics tools and data sets. We then mapped these categories onto social science frameworks for conceptualizing innovation adoption to generate actionable insights for proponents of toxicogenomics.

DISCUSSION

We identify the most salient drivers and obstacles. From 1998 through 2017, adoption of toxicogenomics was understood to be helped by drivers such as those we labeled Superior scientific understanding, New applications, and Reduced cost & increased efficiency but hindered by obstacles such as those we labeled Insufficient validation, Complexity of interpretation, and Lack of standardization. Leveraging social science frameworks, we find that arguments for adoption that draw on the most salient drivers, which emphasize superior and novel functionality of omics as rationales, overlook potential adopters' key concerns: simplicity of use and compatibility with existing practices. We also identify two perspectives-innovation-centric and adopter-centric-on omics adoption and explain how overreliance on the former may be undermining efforts to promote toxicogenomics. https://doi.org/10.1289/EHP6500.

Predicting PBT and CMR properties of substances of very high concern (SVHCs) using QSAR models, and application for K-REACH

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BIOWIN is effective for predicting persistence and bioaccumulation.

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Toxtree is effective for predicting carcinogenicity and mutagenicity.

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WoE approach enhances the sensitivity.

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It is recommended to set a conservative criteria of log Kow more than 4.5 in K-REACH.

Quantitative structure-activity relationship (QSAR) models have been applied to predict a variety of toxicity endpoints. Their performance needs to be validated, in a variety of cases, to increase their applicability to chemical regulation. Using the data set of substances of very high concern (SVHCs), the performance of QSAR models were evaluated to predict the persistence and bioaccumulation of PBT, and the carcinogenicity and mutagenicity of CMR. BIOWIN and Toxtree showed higher sensitivity than other QSAR models – the former for persistence and bioaccumulation, the latter for carcinogenicity. In terms of mutagenicity, the sensitivities of QSAR models were underestimated, Toxtree was more accurate and specific than lazy structure–activity relationships (LAZARs) and Computer Assisted Evaluation of industrial chemical Substances According to Regulations (CAESAR). Using the weight of evidence (WoE) approach, which integrates results of individual QSAR models, enhanced the sensitivity of each toxicity endpoint. On the basis of obtained results, in particular the prediction of persistence and bioaccumulation by KOWWIN, a conservative criterion is recommended of log Kow greater than 4.5 in K-REACH, without an upper limit. This study suggests that reliable production of toxicity data by QSAR models is facilitated by a better understanding of the performance of these models.

Assessing Toxicity with Human Cell-Based In Vitro Methods

In toxicology, there is a strong push towards replacing animal experiments with alternative methods, which include cell-based in vitro methods for the assessment of adverse health effects in humans. High-throughput methods are of central interest due to the large and steadily growing numbers of compounds that require assessment. Tremendous progress has been made during the last decade in developing and applying such methods. Innovative technologies for addressing complex biological interactions include induced pluripotent stem cell- and organoid-based approaches, organotypic coculture systems, and microfluidic 'multiorgan' chips. Combining in vitro methods with bioinformatics and in silico modeling generates new powerful tools for toxicity assessment, and the rapid progress in the field is expected to continue.

EcoToxModules: Custom Gene Sets to Organize and Analyze Toxicogenomics Data from Ecological Species

Traditional results from toxicogenomics studies are complex lists of significantly impacted genes or gene sets, which are challenging to synthesize down to actionable results with a clear interpretation. Here, we defined two sets of 21 custom gene sets, called the functional and statistical EcoToxModules, in fathead minnow (Pimephales promelas) to (1) re-cast predefined molecular pathways into a toxicological framework and (2) provide a data-driven, unsupervised grouping of genes impacted by exposure to environmental contaminants. The functional EcoToxModules were identified by re-organizing KEGG pathways into biological processes that are more relevant to ecotoxicology based on the input from expert scientists and regulators. The statistical EcoToxModules were identified using co-expression analysis of publicly available microarray data (n = 303 profiles) measured in livers of fathead minnows after exposure to 38 different conditions. Potential applications of the EcoToxModules were demonstrated with two case studies that represent exposure to a pure chemical and to environmental wastewater samples. In comparisons to differential expression and gene set analysis, we found that EcoToxModule responses were consistent with these traditional results. Additionally, they were easier to visualize and quantitatively compare across different conditions, which facilitated drawing conclusions about the relative toxicity of the exposures within each case study.

Factors Affecting the Perception of New Approach Methodologies (NAMs) in the Ecotoxicology Community

Given current legislative mandates to assess the safety of thousands of chemicals and the slow pace at which conventional testing proceeds, there is a need to accelerate chemical risk assessment. Governments and businesses are increasingly interested in new approach methodologies (NAMs) that promise to reduce costs and delays. We explore 5 sociological factors within the ecotoxicology community that can influence the perception of NAMs: 1) professional profile (educational cohort, employer), 2) internal science communication within professional forums, 3) concern for "error cost," 4) collaboration across stakeholders, and 5) fundamental beliefs regarding toxicology. We conducted an online survey (n = 171; 2018) asking participants about their experiences and perspectives at events of the Society of Environmental Toxicology and Chemistry (SETAC) to assess 1) how NAMs are discussed compared to conventional testing and 2) how respondents perceive their viability. We developed ordered logistic regression (OLR) models to understand the influence of exploratory variables (cohort, core views on toxicology, frequency of collaboration) on respondents' evaluation of the viability of different NAMs. Our results showed that 1) NAMs were more likely than conventional methods to be challenged in forum discussions, which may be fueled by concerns for error costs in regulatory decision making; 2) perceptions of the viability of NAMs tended to follow a "pattern of familiarity," whereby respondents that were more knowledgeable about a test method tended to find it more viable; 3) respondents who agreed with the Paracelsus maxim had a greater likelihood of finding conventional testing viable; and 4) the more a respondent reported collaborating with industry on alternative testing strategies, the more likely she or he was to report that NAMs were less viable. These results suggest that there are professional and organizational barriers to greater acceptance of NAMs that can be addressed through a social learning process within the professional community. Integr Environ Assess Manag 2020;16:269-281. © 2020 SETAC.

Transcriptomic points-of-departure from short-term exposure studies are protective of chronic effects for fish exposed to estrogenic chemicals

Resource limitations often require risk assessors to extrapolate chronic toxicity from acute tests using assessment factors. Transcriptomic dose-response analysis following short-term exposures may provide a more reliable and biologically-based alternative for estimating chronic toxicity. Here, we demonstrate that transcriptomic dose-response analysis in fish following short-term exposure to endocrine disrupting chemicals (EDCs) provides estimates of chronic toxicity that may be used as protective points-of-departure (POD) for risk assessment. The benchmark dose (BMD) method was used on publicly available datasets (n = 5) to determine transcriptomic PODs in fish exposed to three EDCs (bisphenol A, ethinylestradiol, and diethylstilbestrol). To test for potential bias related to data processing, our analysis compared the effect of different normalization, filtering, and BMD-grouping methods on the transcriptomic PODs. The resulting PODs were then compared to the empirically-derived chronic LOEC of each substance. Normalization and filtering methods had limited impact on the final PODs. However, we found that PODs derived from ontology- or pathway-based gene grouping methods were highly variable, whereas PODs from grouping methods that focused on the most responsive genes were more stable and provided POD estimates that were most similar to the chronic LOEC. Overall, 72% of transcriptomic PODs were within 1 order of magnitude of the chronic LOEC, regardless of data analysis method. When our recommended analysis approach was applied, the concordance improved to 100%. These results suggest that toxicogenomic dose-response analysis has the potential to be a protective decision-support tool for compounds with chronic toxicity, such as EDCs.

2017 Lush Science Prize

Now in its sixth year, the Lush Prize supports animal-free testing by awarding money prizes of up to £350,000 to the most effective projects and individuals who have been working towards the goal of replacing animals in product or ingredient safety testing. Prizes are awarded for developments in five strategic areas: Science; Lobbying; Training; Public Awareness; and Young Researchers. In the event of a major breakthrough leading to the replacement of animal tests in the area of 21st Century Toxicology, a Black Box Prize (equivalent to the entire annual fund) is awarded. The Science Prize is awarded to the researchers whose work the judging panel believe has made the most significant contribution to the replacement of animal testing in the preceding year. This Background Paper outlines the research projects that were shortlisted and presented to the judging panel as potential candidates for the 2017 Lush Science Prize. This process involved reviewing recent work of the relevant scientific institutions and projects in this area, such as the OECD, Human Toxome Project, UK NC3Rs, US Tox21 programme, ToxCast programme and the Human Toxicology Project Consortium. Recent developments in toxicity testing research were also identified by searching for relevant published papers in the literature, and analysing abstracts from conferences focusing on animal replacement in toxicity testing that had been held in the preceding 12 months -- for example, the 2016 EUSAAT-Linz conference and the 2017 Society of Toxicology annual conference.

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

Rethinking developmental toxicity testing: Evolution or revolution?

BACKGROUND

Current developmental toxicity testing adheres largely to protocols suggested in 1966 involving the administration of test compound to pregnant laboratory animals. After more than 50 years of embryo-fetal development testing, are we ready to consider a different approach to human developmental toxicity testing?

METHODS

A workshop was held under the auspices of the Developmental and Reproductive Toxicology Technical Committee of the ILSI Health and Environmental Sciences Institute to consider how we might design developmental toxicity testing if we started over with 21st century knowledge and techniques (revolution). We first consider what changes to the current protocols might be recommended to make them more predictive for human risk (evolution).

RESULTS

The evolutionary approach includes modifications of existing protocols and can include humanized models, disease models, more accurate assessment and testing of metabolites, and informed approaches to dose selection. The revolution could start with hypothesis-driven testing where we take what we know about a compound or close analog and answer specific questions using targeted experimental techniques rather than a one-protocol-fits-all approach. Central to the idea of hypothesis-driven testing is the concept that testing can be done at the level of mode of action. It might be feasible to identify a small number of key events at a molecular or cellular level that predict an adverse outcome and for which testing could be performed in vitro or in silico or, rarely, using limited in vivo models. Techniques for evaluating these key events exist today or are in development.

DISCUSSION

Opportunities exist for refining and then replacing current developmental toxicity testing protocols using techniques that have already been developed or are within reach.