New ideas for non-animal approaches to predict repeated-dose systemic toxicity: Report from an EPAA Blue Sky Workshop

In vitro protein digestibility to replace in vivo digestibility for purposes of nutrient content claim substantiation in North America's context

The reliance by North American regulatory authorities on in vivo rodent bioassays-Protein Correct-Amino Acid Score (PDCAAS) in the U.S. and Protein Efficiency Ratio (PER) in Canada-to measure the protein quality for protein content claim substantiation represents a major barrier for innovation in the development and marketing of protein foods. Although FAO in 2013 proposed a new method (Digestible Indispensable Amino Acid Score, DIAAS), it is still not used for protein content claim substantiation in any jurisdiction. Together with public health efforts to increase the consumption of plant-based foods, removing hurdles is key to incentivizing the food industry to measure protein digestibility in making food formulation decisions as well as in claiming protein content on product labels. To address this issue, a pathway has been proposed to position alternative methods for in vitro protein digestibility in collaborative studies to generate the data necessary for method approval by a certifying body. The latter is critical to the potential recognition of these methods by both Health Canada and the US FDA. The purpose of this article is to briefly summarize the state-of-the-art in the field, to inform the research community of next steps, and to describe the path engaging collaborative laboratories in a proficiency test as the first step in moving forward toward acceptance of in vitro digestibility methods. Throughout, a consultative and iterative process will be utilized to ensure the program goals are met. Success will be achieved when the proposed path results in the acceptance of an in vitro methods for protein digestibility used for PDCAAS determinations, which will enable increased protein analyses and improved nutrition labeling of protein foods.

Big Question to Developing Solutions: A Decade of Progress in the Development of Aquatic New Approach Methodologies from 2012 to 2022

In 2012, 20 key questions related to hazard and exposure assessment and environmental and health risks of pharmaceuticals and personal care products in the natural environment were identified. A decade later, this article examines the current level of knowledge around one of the lowest-ranking questions at that time, number 19: "Can nonanimal testing methods be developed that will provide equivalent or better hazard data compared with current in vivo methods?" The inclusion of alternative methods that replace, reduce, or refine animal testing within the regulatory context of risk and hazard assessment of chemicals generally faces many hurdles, although this varies both by organism (human-centric vs. other), sector, and geographical region or country. Focusing on the past 10 years, only works that might reasonably be considered to contribute to advancements in the field of aquatic environmental risk assessment are highlighted. Particular attention is paid to methods of contemporary interest and importance, representing progress in (1) the development of methods which provide equivalent or better data compared with current in vivo methods such as bioaccumulation, (2) weight of evidence, or (3) -omic-based applications. Evolution and convergence of these risk assessment areas offer the basis for fundamental frameshifts in how data are collated and used for the protection of taxa across the breadth of the aquatic environment. Looking to the future, we are at a tipping point, with a need for a global and inclusive approach to establish consensus. Bringing together these methods (both new and old) for regulatory assessment and decision-making will require a concerted effort and orchestration. Environ Toxicol Chem 2024;43:559-574. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Protecting Human and Animal Health: The Road from Animal Models to New Approach Methods

Animals and animal models have been invaluable for our current understanding of human and animal biology, including physiology, pharmacology, biochemistry, and disease pathology. However, there are increasing concerns with continued use of animals in basic biomedical, pharmacological, and regulatory research to provide safety assessments for drugs and chemicals. There are concerns that animals do not provide sufficient information on toxicity and/or efficacy to protect the target population, so scientists are utilizing the principles of replacement, reduction, and refinement (the 3Rs) and increasing the development and application of new approach methods (NAMs). NAMs are any technology, methodology, approach, or assay used to understand the effects and mechanisms of drugs or chemicals, with specific focus on applying the 3Rs. Although progress has been made in several areas with NAMs, complete replacement of animal models with NAMs is not yet attainable. The road to NAMs requires additional development, increased use, and, for regulatory decision making, usually formal validation. Moreover, it is likely that replacement of animal models with NAMs will require multiple assays to ensure sufficient biologic coverage. The purpose of this manuscript is to provide a balanced view of the current state of the use of animal models and NAMs as approaches to development, safety, efficacy, and toxicity testing of drugs and chemicals. Animals do not provide all needed information nor do NAMs, but each can elucidate key pieces of the puzzle of human and animal biology and contribute to the goal of protecting human and animal health. SIGNIFICANCE STATEMENT: Data from traditional animal studies have predominantly been used to inform human health safety and efficacy. Although it is unlikely that all animal studies will be able to be replaced, with the continued advancement in new approach methods (NAMs), it is possible that sometime in the future, NAMs will likely be an important component by which the discovery, efficacy, and toxicity testing of drugs and chemicals is conducted and regulatory decisions are made.

Analysis of health concerns not addressed by REACH for low tonnage chemicals and opportunities for new approach methodology

In Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) the criterion for deciding the studies that must be performed is the annual tonnage of the chemical manufactured or imported into the EU. The annual tonnage may be considered as a surrogate for levels of human exposure but this does not take into account the physico-chemical properties and use patterns that determine exposure. Chemicals are classified using data from REACH under areas of health concern covering effects on the skin and eye; sensitisation; acute, repeated and prolonged systemic exposure; effects on genetic material; carcinogenicity; and reproduction and development. We analysed the mandated study lists under REACH for each annual tonnage band in terms of the information they provide on each of the areas of health concern. Using the European Chemicals Agency (ECHA) REACH Registration data base of over 20,000 registered substances, we found that only 19% of registered substances have datasets on all areas of health concern. Information limited to acute exposure, sensitisation and genotoxicity was found for 62%. The analysis highlighted the shortfall of information mandated for substances in the lower tonnage bands. Deploying New Approach Methodologies (NAMs) at this lower tonnage band to assess health concerns which are currently not covered by REACH, such as repeat and extended exposure and carcinogenicity, would provide additional information and would be a way for registrants and regulators to gain experience in the use of NAMs. There are currently projects in Europe aiming to develop NAM-based assessment frameworks and they could find their first use in assessing low tonnage chemicals once confidence has been gained by their evaluation with data rich chemicals.

Integrating distribution kinetics and toxicodynamics to assess repeat dose neurotoxicity in vitro using human BrainSpheres: a case study on amiodarone

For ethical, economical, and scientific reasons, animal experimentation, used to evaluate the potential neurotoxicity of chemicals before their release in the market, needs to be replaced by new approach methodologies. To illustrate the use of new approach methodologies, the human induced pluripotent stem cell-derived 3D model BrainSpheres was acutely (48 h) or repeatedly (7 days) exposed to amiodarone (0.625-15 µM), a lipophilic antiarrhythmic drug reported to have deleterious effects on the nervous system. Neurotoxicity was assessed using transcriptomics, the immunohistochemistry of cell type-specific markers, and real-time reverse transcription-polymerase chain reaction for various genes involved in the lipid metabolism. By integrating distribution kinetics modeling with neurotoxicity readouts, we show that the observed time- and concentration-dependent increase in the neurotoxic effects of amiodarone is driven by the cellular accumulation of amiodarone after repeated dosing. The development of a compartmental in vitro distribution kinetics model allowed us to predict the change in cell-associated concentrations in BrainSpheres with time and for different exposure scenarios. The results suggest that human cells are intrinsically more sensitive to amiodarone than rodent cells. Amiodarone-induced regulation of lipid metabolism genes was observed in brain cells for the first time. Astrocytes appeared to be the most sensitive human brain cell type in vitro. In conclusion, assessing readouts at different molecular levels after the repeat dosing of human induced pluripotent stem cell-derived BrainSpheres in combination with the compartmental modeling of in vitro kinetics provides a mechanistic means to assess neurotoxicity pathways and refine chemical safety assessment for humans.

Advancing the use of new approach methodologies for assessing teratogenicity: Building a tiered approach

Many New Approach Methodologies (NAMs) have been developed for the safety assessment of new ingredients. Research into reproductive toxicity and teratogenicity is a particularly high priority, especially given their mechanistic complexity. Forty-six non-teratogenic and 39 teratogenic chemicals were screened for teratogenic potential using the in silico DART model from the OECD QSAR Toolbox; the devTox quickPredict™ (devTox assay) test and the Zebrafish Embryotoxicity Test (ZET). The sensitivity and specificity were 94.7% and 84.1%, respectively, for the DART tree (83 chemicals), 86.1% and 35.6% for the devTox (81 chemicals) and 77.8% and 76.7% for the ZET (57 chemicals). Fifty-three chemicals were tested in all three assays and when results were combined and based on a "2 out of 3 rule", the sensitivity and specificity were 96.0% and 71.4%, respectively. The specificity of the devTox assay for a sub-set of 43 chemicals was increased from 26.1% to 82.6% by incorporating human plasma concentrations into the assay interpretation. When all 85 chemicals were assessed in a decision tree approach, there was an excellent predictivity and assay robustness of 90%. In conclusion, all three models exhibited a good sensitivity and specificity, especially when outcomes from all three were combined or used in "2 out of 3" or a tiered decision tree approach. The latter is an interesting predictive approach for evaluating the teratogenic potential of new chemicals. Future investigations will extend the number of chemicals tested, as well as explore ways to refine the results and obtain a robust Integrated Testing Strategy to evaluate teratogenic potential.

New approach methodologies in human regulatory toxicology - Not if, but how and when!

The predominantly animal-centric approach of chemical safety assessment has increasingly come under pressure. Society is questioning overall performance, sustainability, continued relevance for human health risk assessment and ethics of this system, demanding a change of paradigm. At the same time, the scientific toolbox used for risk assessment is continuously enriched by the development of "New Approach Methodologies" (NAMs). While this term does not define the age or the state of readiness of the innovation, it covers a wide range of methods, including quantitative structure-activity relationship (QSAR) predictions, high-throughput screening (HTS) bioassays, omics applications, cell cultures, organoids, microphysiological systems (MPS), machine learning models and artificial intelligence (AI). In addition to promising faster and more efficient toxicity testing, NAMs have the potential to fundamentally transform today's regulatory work by allowing more human-relevant decision-making in terms of both hazard and exposure assessment. Yet, several obstacles hamper a broader application of NAMs in current regulatory risk assessment. Constraints in addressing repeated-dose toxicity, with particular reference to the chronic toxicity, and hesitance from relevant stakeholders, are major challenges for the implementation of NAMs in a broader context. Moreover, issues regarding predictivity, reproducibility and quantification need to be addressed and regulatory and legislative frameworks need to be adapted to NAMs. The conceptual perspective presented here has its focus on hazard assessment and is grounded on the main findings and conclusions from a symposium and workshop held in Berlin in November 2021. It intends to provide further insights into how NAMs can be gradually integrated into chemical risk assessment aimed at protection of human health, until eventually the current paradigm is replaced by an animal-free "Next Generation Risk Assessment" (NGRA).

Molecular and Functional Characterization of Different BrainSphere Models for Use in Neurotoxicity Testing on Microelectrode Arrays

The currently accepted methods for neurotoxicity (NT) testing rely on animal studies. However, high costs and low testing throughput hinder their application for large numbers of chemicals. To overcome these limitations, in vitro methods are currently being developed based on human-induced pluripotent stem cells (hiPSC) that allow higher testing throughput at lower costs. We applied six different protocols to generate 3D BrainSphere models for acute NT evaluation. These include three different media for 2D neural induction and two media for subsequent 3D differentiation resulting in self-organized, organotypic neuron/astrocyte microtissues. All induction protocols yielded nearly 100% NESTIN-positive hiPSC-derived neural progenitor cells (hiNPCs), though with different gene expression profiles concerning regional patterning. Moreover, gene expression and immunocytochemistry analyses revealed that the choice of media determines neural differentiation patterns. On the functional level, BrainSpheres exhibited different levels of electrical activity on microelectrode arrays (MEA). Spike sorting allowed BrainSphere functional characterization with the mixed cultures consisting of GABAergic, glutamatergic, dopaminergic, serotonergic, and cholinergic neurons. A test method for acute NT testing, the human multi-neurotransmitter receptor (hMNR) assay, was proposed to apply such MEA-based spike sorting. These models are promising tools not only in toxicology but also for drug development and disease modeling.

Making in silico predictive models for toxicology FAIR

In silico predictive models for toxicology include quantitative structure-activity relationship (QSAR) and physiologically based kinetic (PBK) approaches to predict physico-chemical and ADME properties, toxicological effects and internal exposure. Such models are used to fill data gaps as part of chemical risk assessment. There is a growing need to ensure in silico predictive models for toxicology are available for use and reproducible. This paper describes how the FAIR (Findable, Accessible, Interoperable, Reusable) principles, developed for data sharing, have been applied to in silico predictive models. In particular, this investigation has focussed on how the FAIR principles could be applied to improved regulatory acceptance of predictions from such models. Eighteen principles have been developed that cover all aspects of FAIR. It is intended that FAIRification of in silico predictive models for toxicology will increase their use and acceptance.

Performance assessment and economic analysis of a human Liver-Chip for predictive toxicology

BACKGROUND

Conventional preclinical models often miss drug toxicities, meaning the harm these drugs pose to humans is only realized in clinical trials or when they make it to market. This has caused the pharmaceutical industry to waste considerable time and resources developing drugs destined to fail. Organ-on-a-Chip technology has the potential improve success in drug development pipelines, as it can recapitulate organ-level pathophysiology and clinical responses; however, systematic and quantitative evaluations of Organ-Chips' predictive value have not yet been reported.

METHODS

870 Liver-Chips were analyzed to determine their ability to predict drug-induced liver injury caused by small molecules identified as benchmarks by the Innovation and Quality consortium, who has published guidelines defining criteria for qualifying preclinical models. An economic analysis was also performed to measure the value Liver-Chips could offer if they were broadly adopted in supporting toxicity-related decisions as part of preclinical development workflows.

RESULTS

Here, we show that the Liver-Chip met the qualification guidelines across a blinded set of 27 known hepatotoxic and non-toxic drugs with a sensitivity of 87% and a specificity of 100%. We also show that this level of performance could generate over $3 billion annually for the pharmaceutical industry through increased small-molecule R&D productivity.

CONCLUSIONS

The results of this study show how incorporating predictive Organ-Chips into drug development workflows could substantially improve drug discovery and development, allowing manufacturers to bring safer, more effective medicines to market in less time and at lower costs.

EU’s next generation risk assessment: hurdles and opportunities for new approach methodologies

The EU’s decision to ban animal testing for toxicity testing, has positively influenced the pace of developing New Approach Methodologies (NAMs). This development also supports replacing animal methods in other forms of risk assessment (RA), such as for oral-toxicity testing. This study aims to identify the hurdles and opportunities for validation and implementation of NAMs in the current EU’s chemical RA. Through conducting semi-structured interviews with 14 stakeholders, experiences and perspectives about the validation and implementation of NAMs in RA for orally ingested chemicals were analyzed. Stakeholders considered the use of NAMs for RA processes both a cultural and generational issue. Both were perceived as hurdles for reaching the next generation RA approach. The differing views on NAMs originated from experience and stakeholder positions, but communication and collaboration on developing future RA approaches could support overcoming this skepticism. Irrespectively of their background, all interviewees were generally optimistic that NAMs will support the development of more accurate and sustainable RA. This research highlights the need for the EU to adjust legislation and guidance documents to shift in testing requirements from the traditional overexposure approach to more predictive, mechanistic testing in RA, which will take time. This study, however, shows that—when all stakeholders engage in communication and confidence building—NAMs can already play an important role in reducing and refining animal testing.

Using high throughput screens to predict miscarriages with placental stem cells and long-term stress effects with embryonic stem cells

A problem in developmental toxicology is the massive loss of life from fertilization through gastrulation, and the surprising lack of knowledge of causes of miscarriage. Half to two-thirds of embryos are lost, and environmental and genetic causes are nearly equal. Simply put, it can be inferred that this is a difficult period for normal embryos, but that environmental stresses may cause homeostatic responses that move from adaptive to maladaptive with increasing exposures. At the lower 50% estimate, miscarriage causes greater loss-of-life than all cancers combined or of all cardio- and cerebral-vascular accidents combined. Surprisingly, we do not know if miscarriage rates are increasing or decreasing. Overshadowed by the magnitude of miscarriages, are insufficient data on teratogenic or epigenetic imbalances in surviving embryos and their stem cells. Superimposed on the difficult normal trajectory for peri-gastrulation embryos are added malnutrition, hormonal, and environmental stresses. An overarching hypothesis is that high throughput screens (HTS) using cultured viable reporter embryonic and placental stem cells (e.g., embryonic stem cells [ESC] and trophoblast stem cells [TSC] that report status using fluorescent reporters in living cells) from the pre-gastrulation embryo will most rapidly test a range of hormonal, environmental, nutritional, drug, and diet supplement stresses that decrease stem cell proliferation and imbalance stemness/differentiation. A second hypothesis is that TSC respond with greater sensitivity in magnitude to stress that would cause miscarriage, but ESC are stress-resistant to irreversible stemness loss and are best used to predict long-term health defects. DevTox testing needs more ESC and TSC HTS to model environmental stresses leading to miscarriage or teratogenesis and more research on epidemiology of stress and miscarriage. This endeavor also requires a shift in emphasis on pre- and early gastrulation events during the difficult period of maximum loss by miscarriage.

Comparison of toxicological effects and exposure levels between triclosan and its structurally similar chemicals using in vitro tests for read-across case study

Read-across based on structural and biological similarities is expected to be a promising alternative method for assessing systemic toxicity. A concrete strategy for quantitative chemical risk assessment would be to stack read-across case studies and extract key considerations from them. Thus, we developed a read-across case study by comparing the toxicological effects based on adverse outcome pathways and exposure levels of different structurally similar chemicals for a target organ. In this study, we selected the hepatotoxicity of triclosan and its structurally similar chemicals including diclosan and 1-chloro-3-(4-chlorophenoxy)benzene. The results of in vitro toxicogenomics showed that disorders of cholesterol synthesis were commonly detected with both triclosan and diclosan. The decrease in hepatocellular cholesterol levels was similar in the cells treated with triclosan and diclosan. Furthermore, the exposure levels of triclosan and diclosan for the liver were similar. Collectively, these results suggest that triclosan and diclosan show similar toxicological effects and severity of hepatotoxicity. Considering the existing repeated dose toxicity data, our prediction results are reasonable regarding the toxicological effect and its severity. Thus, the present study demonstrated the usability of comparing toxicological effects and exposure levels using read-across for quantitative chemical risk assessment.

Studying metabolism with multi-organ chips: new tools for disease modelling, pharmacokinetics and pharmacodynamics

Non-clinical models to study metabolism including animal models and cell assays are often limited in terms of species translatability and predictability of human biology. This field urgently requires a push towards more physiologically accurate recapitulations of drug interactions and disease progression in the body. Organ-on-chip systems, specifically multi-organ chips (MOCs), are an emerging technology that is well suited to providing a species-specific platform to study the various types of metabolism (glucose, lipid, protein and drug) by recreating organ-level function. This review provides a resource for scientists aiming to study human metabolism by providing an overview of MOCs recapitulating aspects of metabolism, by addressing the technical aspects of MOC development and by providing guidelines for correlation with in silico models. The current state and challenges are presented for two application areas: (i) disease modelling and (ii) pharmacokinetics/pharmacodynamics. Additionally, the guidelines to integrate the MOC data into in silico models could strengthen the predictive power of the technology. Finally, the translational aspects of metabolizing MOCs are addressed, including adoption for personalized medicine and prospects for the clinic. Predictive MOCs could enable a significantly reduced dependence on animal models and open doors towards economical non-clinical testing and understanding of disease mechanisms.

The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity

There exists consensus that the traditional means by which safety of chemicals is assessed-namely through reliance upon apical outcomes obtained following in vivo testing-is increasingly unfit for purpose. Whilst efforts in development of suitable alternatives continue, few have achieved levels of robustness required for regulatory acceptance. An array of "new approach methodologies" (NAM) for determining toxic effect, spanning in vitro and in silico spheres, have by now emerged. It has been suggested, intuitively, that combining data obtained from across these sources might serve to enhance overall confidence in derived judgment. This concept may be formalised in the "tiered assessment" approach, whereby evidence gathered through a sequential NAM testing strategy is exploited so to infer the properties of a compound of interest. Our intention has been to provide an illustration of how such a scheme might be developed and applied within a practical setting-adopting for this purpose the endpoint of rat acute oral lethality. Bayesian statistical inference is drawn upon to enable quantification of degree of confidence that a substance might ultimately belong to one of five LD50-associated toxicity categories. Informing this is evidence acquired both from existing in silico and in vitro resources, alongside a purposely-constructed random forest model and structural alert set. Results indicate that the combination of in silico methodologies provides moderately conservative estimations of hazard, conducive for application in safety assessment, and for which levels of certainty are defined. Accordingly, scope for potential extension of approach to further toxicological endpoints is demonstrated.

Subchronic toxicity and genotoxicity studies of Hericium erinaceus β-glucan extract preparation

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β-Glucan from Hericium erinaceus was investigated for subchronic toxicity and mutagenicity.

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In the subchronic study, The No-Observed-Adverse-Effect Level (NOAEL) for Hericium erinaceus β-glucan was 2000 mg/kg bw/day.

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In mutagenicity studies, Hericium erinaceus β-glucan did not reveal genotoxic effects.

The medicinal effects of Hericium erinaceus have been long documented in scientific studies of Eastern traditional medicine. It is widely consumed, because of its nutritional qualities and perceived health benefits. Also, it is rich in β-glucans, which has been shown to have immunomodulating and antitumor effects. The objective of the present study was to investigate adverse effects, if any, of β-glucan extract preparation from H. erinaceus in subchronic toxicity and genotoxicity studies. The conduct of these studies was in compliance with Good Laboratory Practice (GLP) and test guidelines established by the Organization for Economic Cooperation and Development (OECD). In the subchronic toxicity study, Sprague Dawley rats (12/sex/group) were administered (gavage) H. erinaceus β-glucan extract preparation at dose levels of 0, 500, 1000 and 2000 mg/kg body weight (bw)/day for 90 days. Treatment with H. erinaceus β-glucan extract preparation did not result in any toxicologically significant treatment-related changes in clinical observations, ophthalmic examinations, body weights, body weight gains, feed consumption, and organ weights. Clinical pathology including hematology, serum chemistry, urinalysisand terminal necropsy (gross or histopathology findings) did not reveal any treatment-related adverse effects. The results of genotoxicity studies as evaluated by gene mutations in Salmonella typhimurium, in vitro chromosome aberrations and in vivo micronucleus test in mice did not reveal any genotoxicity of H. erinaceus β-glucan extract preparation. Based on the subchronic study, the no observed-adverse-effect level (NOAEL) for H. erinaceus β-glucan extract preparation was determined as 2000 mg/kg bw/day, the highest dose tested.

A framework for chemical safety assessment incorporating new approach methodologies within REACH

The long-term investment in new approach methodologies (NAMs) within the EU and other parts of the world is beginning to result in an emerging consensus of how to use information from in silico, in vitro and targeted in vivo sources to assess the safety of chemicals. However, this methodology is being adopted very slowly for regulatory purposes. Here, we have developed a framework incorporating in silico, in vitro and in vivo methods designed to meet the requirements of REACH in which both hazard and exposure can be assessed using a tiered approach. The outputs from each tier are classification categories, safe doses, and risk assessments, and progress through the tiers depends on the output from previous tiers. We have exemplified the use of the framework with three examples. The outputs were the same or more conservative than parallel assessments based on conventional studies. The framework allows a transparent and phased introduction of NAMs in chemical safety assessment and enables science-based safety decisions which provide the same level of public health protection using fewer animals, taking less time, and using less financial and expert resource. Furthermore, it would also allow new methods to be incorporated as they develop through continuous selective evolution rather than periodic revolution.

Probabilistic modelling of developmental neurotoxicity based on a simplified adverse outcome pathway network

In a century where toxicology and chemical risk assessment are embracing alternative methods to animal testing, there is an opportunity to understand the causal factors of neurodevelopmental disorders such as learning and memory disabilities in children, as a foundation to predict adverse effects. New testing paradigms, along with the advances in probabilistic modelling, can help with the formulation of mechanistically-driven hypotheses on how exposure to environmental chemicals could potentially lead to developmental neurotoxicity (DNT). This investigation aimed to develop a Bayesian hierarchical model of a simplified AOP network for DNT. The model predicted the probability that a compound induces each of three selected common key events (CKEs) of the simplified AOP network and the adverse outcome (AO) of DNT, taking into account correlations and causal relations informed by the key event relationships (KERs). A dataset of 88 compounds representing pharmaceuticals, industrial chemicals and pesticides was compiled including physicochemical properties as well as in silico and in vitro information. The Bayesian model was able to predict DNT potential with an accuracy of 76%, classifying the compounds into low, medium or high probability classes. The modelling workflow achieved three further goals: it dealt with missing values; accommodated unbalanced and correlated data; and followed the structure of a directed acyclic graph (DAG) to simulate the simplified AOP network. Overall, the model demonstrated the utility of Bayesian hierarchical modelling for the development of quantitative AOP (qAOP) models and for informing the use of new approach methodologies (NAMs) in chemical risk assessment.

A matter of trust: Learning lessons about causality will make qAOPs credible

Toxicology in the 21st Century has seen a shift from chemical risk assessment based on traditional animal tests, identifying apical endpoints and doses that are "safe", to the prospect of Next Generation Risk Assessment based on non-animal methods. Increasingly, large and high throughput in vitro datasets are being generated and exploited to develop computational models. This is accompanied by an increased use of machine learning approaches in the model building process. A potential problem, however, is that such models, while robust and predictive, may still lack credibility from the perspective of the end-user. In this commentary, we argue that the science of causal inference and reasoning, as proposed by Judea Pearl, will facilitate the development, use and acceptance of quantitative AOP models. Our hope is that by importing established concepts of causality from outside the field of toxicology, we can be "constructively disruptive" to the current toxicological paradigm, using the "Causal Revolution" to bring about a "Toxicological Revolution" more rapidly.

In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity

Hepatotoxicity is one of the most frequently observed adverse effects resulting from exposure to a xenobiotic. For example, in pharmaceutical research and development it is one of the major reasons for drug withdrawals, clinical failures, and discontinuation of drug candidates. The development of faster and cheaper methods to assess hepatotoxicity that are both more sustainable and more informative is critically needed. The biological mechanisms and processes underpinning hepatotoxicity are summarized and experimental approaches to support the prediction of hepatotoxicity are described, including toxicokinetic considerations. The paper describes the increasingly important role of in silico approaches and highlights challenges to the adoption of these methods including the lack of a commonly agreed upon protocol for performing such an assessment and the need for in silico solutions that take dose into consideration. A proposed framework for the integration of in silico and experimental information is provided along with a case study describing how computational methods have been used to successfully respond to a regulatory question concerning non-genotoxic impurities in chemically synthesized pharmaceuticals.

Refining Procedures within Regulatory Toxicology Studies: Improving Animal Welfare and Data

Simple Summary

Before any new medicine can be administered to humans, or new chemical marketed, some tests using animals such as fish, mice, rats, rabbits, dogs, or monkeys are performed in order to satisfy the legal requirements of international regulatory and government agencies. These assess the potential for harmful side effects in humans or species found in the environment and to explore how the compound is processed within the body. The housing conditions and procedures performed (such as dosing of compounds and removal of small blood samples) are designed to minimize any pain, suffering, distress, or lasting harm that may be experienced by the animals. These refinements improve animal welfare but can also improve the data quality. Examples of new processes, technologies, or equipment that have been introduced within some UK facilities are shared in this article and provide opportunities to benefit many more animals undergoing testing across the world in the future.

Abstract

During the development of potential new medicines or agrochemicals, an assessment of the safety profile to humans and environmental species is conducted using a range of different in silico and in vitro techniques in conjunction with metabolism and toxicity studies using animals. The required studies are outlined within international regulatory guidelines which acknowledge and support the application of the 3Rs to reduce the number of animals used or to refine the procedures performed when these studies are deemed to be necessary. The continued development of new technologies and adoption of best-practice approaches to laboratory animal housing and study procedures has generated a series of refinements that can be incorporated into animal studies throughout the package. These refinements benefit the welfare of fish, mice, rats, rabbits, dogs, minipigs, and non-human primates (NHPs) whilst maintaining or improving data quality within general toxicology, metabolism, and other studies and can also bring efficiencies to processes that benefit study costs and timings. Examples are shared which cover the following topics: social housing of dogs and NHPs, surgical refinements in the rat bile duct cannulation model for collection of data for metabolism studies, whether fasting is really required prior to clinical pathology sampling, and the use of microsampling for toxicokinetics.

Derivation, characterisation and analysis of an adverse outcome pathway network for human hepatotoxicity

Adverse outcome pathways (AOPs) and their networks are important tools for the development of mechanistically based non-animal testing approaches, such as in vitro and/or in silico assays, to assess toxicity induced by chemicals. In the present study, an AOP network connecting 14 linear AOPs related to human hepatotoxicity, currently available in the AOP-Wiki, was derived according to established criteria. The derived AOP network was characterised and analysed with regard to its structure and topological features. In-depth analysis of the AOP network showed that cell injury/death, oxidative stress, mitochondrial dysfunction and accumulation of fatty acids are the most highly connected and central key events. Consequently, these key events may be considered as the rational and mechanistically anchored basis for selecting, developing and/optimising in vitro and/or in silico assays to predict hepatotoxicity induced by chemicals in view of animal-free hazard identification.

Safer chemicals using less animals: kick-off of the European ONTOX project

The 3Rs concept, calling for replacement, reduction and refinement of animal experimentation, is receiving increasing attention around the world, and has found its way to legislation, in particular in the European Union. This is aligned by continuing high-level efforts of the European Commission to support development and implementation of 3Rs methods. In this respect, the European project called "ONTOX: ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment" was recently initiated with the goal to provide a functional and sustainable solution for advancing human risk assessment of chemicals without the use of animals in line with the principles of 21^st century toxicity testing and next generation risk assessment. ONTOX will deliver a generic strategy to create new approach methodologies (NAMs) in order to predict systemic repeated dose toxicity effects that, upon combination with tailored exposure assessment, will enable human risk assessment. For proof-of-concept purposes, focus is put on NAMs addressing adversities in the liver, kidneys and developing brain induced by a variety of chemicals. The NAMs each consist of a computational system based on artificial intelligence and are fed by biological, toxicological, chemical and kinetic data. Data are consecutively integrated in physiological maps, quantitative adverse outcome pathway networks and ontology frameworks. Supported by artificial intelligence, data gaps are identified and are filled by targeted in vitro and in silico testing. ONTOX is anticipated to have a deep and long-lasting impact at many levels, in particular by consolidating Europe's world-leading position regarding the development, exploitation, regulation and application of animal-free methods for human risk assessment of chemicals.

FutureTox IV Workshop Summary: Predictive Toxicology for Healthy Children

FutureTox IV, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in November 2018. Building upon FutureTox I, II, and III, this conference focused on the latest science and technology for in vitro profiling and in silico modeling as it relates to predictive developmental and reproductive toxicity (DART). Publicly available high-throughput screening data sets are now available for broad in vitro profiling of bioactivities across large inventories of chemicals. Coupling this vast amount of mechanistic data with a deeper understanding of molecular embryology and post-natal development lays the groundwork for using new approach methodologies (NAMs) to evaluate chemical toxicity, drug efficacy, and safety assessment for embryo-fetal development. NAM is a term recently adopted in reference to any technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment to avoid the use of intact animals (U.S. Environmental Protection Agency [EPA], Strategic plan to promote the development and implementation of alternative test methods within the tsca program, 2018, https://www.epa.gov/sites/production/files/2018-06/documents/epa_alt_strat_plan_6-20-18_clean_final.pdf). There are challenges to implementing NAMs to evaluate chemicals for developmental toxicity compared with adult toxicity. This forum article reviews the 2018 workshop activities, highlighting challenges and opportunities for applying NAMs for adverse pregnancy outcomes (eg, preterm labor, malformations, low birth weight) as well as disorders manifesting postnatally (eg, neurodevelopmental impairment, breast cancer, cardiovascular disease, fertility). DART is an important concern for different regulatory statutes and test guidelines. Leveraging advancements in such approaches and the accompanying efficiencies to detecting potential hazards to human development are the unifying concepts toward implementing NAMs in DART testing. Although use of NAMs for higher level regulatory decision making is still on the horizon, the conference highlighted novel testing platforms and computational models that cover multiple levels of biological organization, with the unique temporal dynamics of embryonic development, and novel approaches for estimating toxicokinetic parameters essential in supporting in vitro to in vivo extrapolation.

Grouping of chemicals based on the potential mechanisms of hepatotoxicity of naphthalene and structurally similar chemicals using in vitro testing for read-across and its validation

Integrated Approaches to Testing and Assessment provides a framework to improve the reliability of read-across for chemical risk assessment of systemic toxicity without animal testing. However, the availability of only a few case studies hinders the use of this concept for regulatory purposes. Thus, we compared the biological similarity of structurally similar chemicals using in vitro testing to demonstrate the validity of this concept for grouping chemicals and to extract key considerations in read-across. We analyzed the hepatotoxicity of naphthalene and three chemicals structurally similar to naphthalene (2,7-naphthalenediol, 1,5-naphthalenediol, and 1-naphthol) for which 90-day repeated dose toxicity data are available. To elucidate and compare their potential mechanisms, we conducted in vitro microarray analysis using rat primary hepatocytes and validated the results using a biomarker and metabolic activation analysis. We observed that 2,7-naphthalenediol, 1,5-naphthalenediol, and 1-naphthol had similar potential mechanisms, namely, induction of oxidative stress by their metabolic activation. Conversely, naphthalene did not show a similar toxicity effect. The existing in vivo data confirmed our grouping of chemicals based on this potential mechanism. Thus, our findings suggest that in vitro toxicogenomics and related biochemical assays are useful for comparing biological similarities and grouping chemicals based on their toxicodynamics for read-across.

Computational Biology and in silico Toxicodynamics

New approach methodologies (NAMs) refer to any non-animal technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. A spectrum of in silico models is needed for the integrated analysis of various domains in toxicology to improve predictivity and reduce animal testing. This review focuses on in silico approaches, computer models, and computational intelligence for developmental and reproductive toxicity (predictive DART), providing a means to measure toxicodynamics in simulated systems for quantitative prediction of adverse outcomes phenotypes.

A Review of In Silico Tools as Alternatives to Animal Testing: Principles, Resources and Applications

Across the spectrum of industrial sectors, including pharmaceuticals, chemicals, personal care products, food additives and their associated regulatory agencies, there is a need to develop robust and reliable methods to reduce or replace animal testing. It is generally recognised that no single alternative method will be able to provide a one-to-one replacement for assays based on more complex toxicological endpoints. Hence, information from a combination of techniques is required. A greater understanding of the time and concentration-dependent mechanisms, underlying the interactions between chemicals and biological systems, and the sequence of events that can lead to apical effects, will help to move forward the science of reducing and replacing animal experiments. In silico modelling, in vitro assays, high-throughput screening, organ-on-a-chip technology, omics and mathematical biology, can provide complementary information to develop a complete picture of the potential response of an organism to a chemical stressor. Adverse outcome pathways (AOPs) and systems biology frameworks enable relevant information from diverse sources to be logically integrated. While individual researchers do not need to be experts across all disciplines, it is useful to have a fundamental understanding of what other areas of science have to offer, and how knowledge can be integrated with other disciplines. The purpose of this review is to provide those who are unfamiliar with predictive in silico tools, with a fundamental understanding of the underlying theory. Current applications, software, barriers to acceptance, new developments and the use of integrated approaches are all discussed, with additional resources being signposted for each of the topics.