Systems Modeling of Developmental Vascular Toxicity

Cyclosporin A toxicity on endothelial cells differentiated from induced pluripotent stem cells: Assembling an adverse outcome pathway

Cyclosporin A (CSA) is a potent immunosuppressive agent in pharmacologic studies. However, there is evidence for side effects, specifically regarding vascular dysfunction. Its mode of action inducing endothelial cell toxicity is partially unclear, and a connection with an adverse outcome pathway (AOP) is not established yet. Therefore, we designed this study to get deeper insights into the mechanistic toxicology of CSA on angiogenesis. Stem cells, especially induced pluripotent stem cells (iPSCs) with the ability of differentiation to all organs of the body, are considered a promising in vitro model to reduce animal experimentation. In this study, we differentiated iPSCs to endothelial cells (ECs) as one cell type that in other studies would allow to generate multi-cell type organoids from single donors. Flow cytometry and immunostaining confirmed our scalable differentiation protocol. Then dose and time course experiments assessing CSA cytotoxicity on iPS derived endothelial cells were performed. Transcriptomic data suggested CSA dependent induction of reactive oxygen species (ROS), mitochondrial dysfunction, and impaired angiogenesis via ROS induction which was confirmed by in vitro experiments. In order to put these data into a potential adverse outcome pathway (AOP) context, we performed a literature review for CSA-mediated endothelial cell toxicity and combined our experimental data with the publicly available knowledge. Such an AOP will help to design in vitro test batteries and to model events observed in human toxicity studies, as well in predictive toxicology.

Interlaboratory Study on Zebrafish in Toxicology: Systematic Evaluation of the Application of Zebrafish in Toxicology's (SEAZIT's) Evaluation of Developmental Toxicity

Embryonic zebrafish represent a useful test system to screen substances for their ability to perturb development. The exposure scenarios, endpoints captured, and data analysis vary among the laboratories who conduct screening. A lack of harmonization impedes the comparison of the substance potency and toxicity outcomes across laboratories and may hinder the broader adoption of this model for regulatory use. The Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT) initiative was developed to investigate the sources of variability in toxicity testing. This initiative involved an interlaboratory study to determine whether experimental parameters altered the developmental toxicity of a set of 42 substances (3 tested in duplicate) in three diverse laboratories. An initial dose-range-finding study using in-house protocols was followed by a definitive study using four experimental conditions: chorion-on and chorion-off using both static and static renewal exposures. We observed reasonable agreement across the three laboratories as 33 of 42 test substances (78.6%) had the same activity call. However, the differences in potency seen using variable in-house protocols emphasizes the importance of harmonization of the exposure variables under evaluation in the second phase of this study. The outcome of the Def will facilitate future practical discussions on harmonization within the zebrafish research community.

The ToxCast pipeline: updates to curve-fitting approaches and database structure

Introduction: The US Environmental Protection Agency Toxicity Forecaster (ToxCast) program makes in vitro medium- and high-throughput screening assay data publicly available for prioritization and hazard characterization of thousands of chemicals. The assays employ a variety of technologies to evaluate the effects of chemical exposure on diverse biological targets, from distinct proteins to more complex cellular processes like mitochondrial toxicity, nuclear receptor signaling, immune responses, and developmental toxicity. The ToxCast data pipeline (tcpl) is an open-source R package that stores, manages, curve-fits, and visualizes ToxCast data and populates the linked MySQL Database, invitrodb. Methods: Herein we describe major updates to tcpl and invitrodb to accommodate a new curve-fitting approach. The original tcpl curve-fitting models (constant, Hill, and gain-loss models) have been expanded to include Polynomial 1 (Linear), Polynomial 2 (Quadratic), Power, Exponential 2, Exponential 3, Exponential 4, and Exponential 5 based on BMDExpress and encoded by the R package dependency, tcplfit2. Inclusion of these models impacted invitrodb (beta version v4.0) and tcpl v3 in several ways: (1) long-format storage of generic modeling parameters to permit additional curve-fitting models; (2) updated logic for winning model selection; (3) continuous hit calling logic; and (4) removal of redundant endpoints as a result of bidirectional fitting. Results and discussion: Overall, the hit call and potency estimates were largely consistent between invitrodb v3.5 and 4.0. Tcpl and invitrodb provide a standard for consistent and reproducible curve-fitting and data management for diverse, targeted in vitro assay data with readily available documentation, thus enabling sharing and use of these data in myriad toxicology applications. The software and database updates described herein promote comparability across multiple tiers of data within the US Environmental Protection Agency CompTox Blueprint.

Rethinking agrochemical safety assessment: A perspective

Agrochemical safety assessment has traditionally relied on the use of animals for toxicity testing, based on scientific understanding and test guidelines developed in the 1980s. However, since then, there have been significant advances in the toxicological sciences that have improved our understanding of mechanisms underpinning adverse human health effects. The time is ripe to 'rethink' approaches used for human safety assessments of agrochemicals to ensure they reflect current scientific understanding and increasingly embrace new opportunities to improve human relevance and predictivity, and to reduce the reliance on animals. Although the ultimate aim is to enable a paradigm shift and an overhaul of global regulatory data requirements, there is much that can be done now to ensure new opportunities and approaches are adopted and implemented within the current regulatory frameworks. This commentary reviews current initiatives and emerging opportunities to embrace new approaches to improve agrochemical safety assessment for humans, and considers various endpoints and initiatives (including acute toxicity, repeat dose toxicity studies, carcinogenicity, developmental and reproductive toxicity, exposure-driven approaches, inhalation toxicity, and data modelling). Realistic aspirations to improve safety assessment, incorporate new technologies and reduce reliance on animal testing without compromising protection goals are discussed.

Minimum reporting standards based on a comprehensive review of the zebrafish embryo teratogenicity assay

Reproductive toxicity chemical safety assessment involves extensive use of vertebrate animals for regulatory testing purposes. Although alternative methods such as the zebrafish embryo teratogenicity assay (identified in the present manuscript by the acronym ZETA) are promising for replacing tests with mammals, challenges to regulatory application involve lack of standardization and incomplete validation. To identify key protocol aspects and ultimately support improving this situation, a comprehensive review of the literature on the level of harmonization/standardization and validation status of the ZETA has been conducted. The gaps and needed advances of the available ZETA protocols were evaluated and discussed with respect to its applicability as an alternative approach for teratogenicity assessment. Based on the review outcomes, a set of minimum reporting standards for the experimental protocol is proposed. Together with other initiatives towards implementation of alternative approaches at the screening and regulatory levels, the application of minimum reporting requirements is anticipated to support future method standardization and validation, as well as identifying potential improvement aspects. Present findings are expected to ultimately support advancing the ongoing validation initiatives towards the regulatory acceptance of the ZETA.

A Tau-Driven Adverse Outcome Pathway Blueprint Toward Memory Loss in Sporadic (Late-Onset) Alzheimer's Disease with Plausible Molecular Initiating Event Plug-Ins for Environmental Neurotoxicants

The worldwide prevalence of sporadic (late-onset) Alzheimer's disease (sAD) is dramatically increasing. Aging and genetics are important risk factors, but systemic and environmental factors contribute to this risk in a still poorly understood way. Within the frame of BioMed21, the Adverse Outcome Pathway (AOP) concept for toxicology was recommended as a tool for enhancing human disease research and accelerating translation of data into human applications. Its potential to capture biological knowledge and to increase mechanistic understanding about human diseases has been substantiated since. In pursuit of the tau-cascade hypothesis, a tau-driven AOP blueprint toward the adverse outcome of memory loss is proposed. Sequences of key events and plausible key event relationships, triggered by the bidirectional relationship between brain cholesterol and glucose dysmetabolism, and contributing to memory loss are captured. To portray how environmental factors may contribute to sAD progression, information on chemicals and drugs, that experimentally or epidemiologically associate with the risk of AD and mechanistically link to sAD progression, are mapped on this AOP. The evidence suggests that chemicals may accelerate disease progression by plugging into sAD relevant processes. The proposed AOP is a simplified framework of key events and plausible key event relationships representing one specific aspect of sAD pathology, and an attempt to portray chemical interference. Other sAD-related AOPs (e.g., Aβ-driven AOP) and a better understanding of the impact of aging and genetic polymorphism are needed to further expand our mechanistic understanding of early AD pathology and the potential impact of environmental and systemic risk factors.

High-Throughput Screening to Identify Chemical Cardiotoxic Potential

Cardiovascular (CV) disease is one of the most prevalent public health concerns, and mounting evidence supports the contribution of environmental chemicals to CV disease burden. In this study, we performed cardiotoxicity profiling for the Tox21 chemical library by focusing on high-throughput screening (HTS) assays whose targets are associated with adverse events related to CV failure modes. Our objective was to develop new hypotheses around environmental chemicals of potential interest for adverse CV outcomes using Tox21/ToxCast HTS data. Molecular and cellular events linked to six failure modes of CV toxicity were cross-referenced with 1399 Tox21/ToxCast assays to identify cardio-relevant bioactivity signatures. The resulting 40 targets, measured in 314 assays, were integrated via a ToxPi visualization tool and ranking system to prioritize 1138 chemicals based upon formal integration across multiple domains of information. Filtering was performed based on cytotoxicity and generalized cell stress endpoints to try and isolate chemicals with effects specific to CV biology, and bioactivity- and structure-based clustering identified subgroups of chemicals preferentially affecting targets such as ion channels and vascular tissue biology. Our approach identified drugs with known cardiotoxic effects, such as estrogenic modulators like clomiphene and raloxifene, anti-arrhythmic drugs like amiodarone and haloperidol, and antipsychotic drugs like chlorpromazine. Several classes of environmental chemicals such as organotins, bisphenol-like chemicals, pesticides, and quaternary ammonium compounds demonstrated strong bioactivity against CV targets; these were compared to existing data in the literature (e.g., from cardiomyocytes, animal data, or human epidemiological studies) and prioritized for further testing.

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.

Application of In Vitro Metabolism Activation in High-Throughput Screening

In vitro methods which incorporate metabolic capability into the assays allow us to assess the activity of metabolites from their parent compounds. These methods can be applied into high-throughput screening (HTS) platforms, thereby increasing the speed to identify compounds that become active via the metabolism process. HTS was originally used in the pharmaceutical industry and now is also used in academic settings to evaluate biological activity and/or toxicity of chemicals. Although most chemicals are metabolized in our body, many HTS assays lack the capability to determine compound activity via metabolism. To overcome this problem, several in vitro metabolic methods have been applied to an HTS format. In this review, we describe in vitro metabolism methods and their application in HTS assays, as well as discuss the future perspectives of HTS with metabolic activity. Each in vitro metabolism method has advantages and disadvantages. For instance, the S9 mix has a full set of liver metabolic enzymes, but it displays high cytotoxicity in cell-based assays. In vitro metabolism requires liver fractions or the use of other metabolically capable systems, including primary hepatocytes or recombinant enzymes. Several newly developed in vitro metabolic methods, including HepaRG cells, three-dimensional (3D) cell models, and organ-on-a-chip technology, will also be discussed. These newly developed in vitro metabolism approaches offer significant progress in dissecting biological processes, developing drugs, and making toxicology studies quicker and more efficient.

The liver, a functionalized vascular structure

The liver is not only the largest organ in the body but also the one playing one of the most important role in the human metabolism as it is in charge of transforming toxic substances in the body. Understanding the way its blood vasculature works is key. In this work we show that the challenge of predicting the hepatic multi-scale vascular network can be met thanks to the constructal law of design evolution. The work unveils the structure of the liver blood flow architecture as a combination of superimposed tree-shaped networks and porous system. We demonstrate that the dendritic nature of the hepatic artery, portal vein and hepatic vein can be predicted, together with their geometrical features (diameter ratio, duct length ratio) as the entire blood flow architectures follow the principle of equipartition of imperfections. At the smallest scale, the shape of the liver elemental systems-the lobules-is discovered, while their permeability is also predicted. The theory is compared with good agreement to anatomical data from the literature.

An ontology for developmental processes and toxicities of neural tube closure

In recent years, the development and implementation of animal-free approaches to chemical and pharmaceutical hazard and risk assessment has taken off. Alternative approaches are being developed starting from the perspective of human biology and physiology. Neural tube closure is a vital step that occurs early in human development. Correct closure of the neural tube depends on a complex interplay between proteins along a number of protein concentration gradients. The sensitivity of neural tube closure to chemical disturbance of signalling pathways such as the retinoid pathway, is well known. To map the pathways underlying neural tube closure, literature data on the molecular regulation of neural tube closure were collected. As the process of neural tube closure is highly conserved in vertebrates, the extensive literature available for the mouse was used whilst considering its relevance for humans. Thus, important cell compartments, regulatory pathways, and protein interactions essential for neural tube closure under physiological circumstances were identified and mapped. An understanding of aberrant processes leading to neural tube defects (NTDs) requires detailed maps of neural tube embryology, including the complex genetic signals and responses underlying critical cellular dynamical and biomechanical processes. The retinoid signaling pathway serves as a case study for this ontology because of well-defined crosstalk with the genetic control of neural tube patterning and morphogenesis. It is a known target for mechanistically-diverse chemical structures that disrupt neural tube closure The data presented in this manuscript will set the stage for constructing mathematical models and computer simulation of neural tube closure for human-relevant AOPs and predictive toxicology.

A cross-platform approach to characterize and screen potential neurovascular unit toxicants

Development of the neurovascular unit (NVU) is a complex, multistage process that requires orchestrated cell signaling mechanisms across several cell types and ultimately results in formation of the blood-brain barrier. Typical high-throughput screening (HTS) assays investigate single biochemical or single cell responses following chemical insult. As the NVU comprises multiple cell types interacting at various stages of development, a methodology combining high-throughput results across pertinent cell-based assays is needed to investigate potential chemical-induced disruption to the development of this complex cell system. To this end, we implemented a novel method for screening putative NVU disruptors across diverse assay platforms to predict chemical perturbation of the developing NVU. HTS assay results measuring chemical-induced perturbations to cellular key events across angiogenic and neurogenic outcomes in vitro were combined to create a cell-based prioritization of NVU hazard. Chemicals were grouped according to similar modes of action to train a logistic regression literature model on a training set of 38 chemicals. This model utilizes the chemical-specific pairwise mutual information score for PubMed MeSH annotations to represent a quantitative measure of previously published results. Taken together, this study presents a methodology to investigate NVU developmental hazard using cell-based HTS assays and literature evidence to prioritize screening of putative NVU disruptors towards a knowledge-driven characterization of neurovascular developmental toxicity. The results from these screening efforts demonstrate that chemicals representing a range of putative vascular disrupting compound (pVDC) scores can also produce effects on neurogenic outcomes and characterizes possible modes of action for disrupting the developing NVU.

Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations

Understanding the role that the environment plays in influencing public health often involves collecting and studying large, complex data sets. There have been a number of private and public efforts to gather sufficient information and confront significant unknowns in the field of environmental public health, yet there is a persistent and largely unmet need for findable, accessible, interoperable, and reusable (FAIR) data. Even when data are readily available, the ability to create, analyze, and draw conclusions from these data using emerging computational tools, such as augmented and artificial inteligence (AI) and machine learning, requires technical skills not currently implemented on a programmatic level across research hubs and academic institutions. We argue that collaborative efforts in data curation and storage, scientific computing, and training are of paramount importance to empower researchers within environmental sciences and the broader public health community to apply AI approaches and fully realize their potential. Leaders in the field were asked to prioritize challenges in incorporating big data in environmental public health research: inconsistent implementation of FAIR principles in data collection and sharing, a lack of skilled data scientists and appropriate cyber-infrastructures, and limited understanding of possibilities and communication of benefits were among those identified. These issues are discussed, and actionable recommendations are provided.

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

The European Partnership for Alternative Approaches to Animal Testing (EPAA) convened a 'Blue Sky Workshop' on new ideas for non-animal approaches to predict repeated-dose systemic toxicity. The aim of the Workshop was to formulate strategic ideas to improve and increase the applicability, implementation and acceptance of modern non-animal methods to determine systemic toxicity. The Workshop concluded that good progress is being made to assess repeated dose toxicity without animals taking advantage of existing knowledge in toxicology, thresholds of toxicological concern, adverse outcome pathways and read-across workflows. These approaches can be supported by New Approach Methodologies (NAMs) utilising modern molecular technologies and computational methods. Recommendations from the Workshop were based around the needs for better chemical safety assessment: how to strengthen the evidence base for decision making; to develop, standardise and harmonise NAMs for human toxicity; and the improvement in the applicability and acceptance of novel techniques. "Disruptive thinking" is required to reconsider chemical legislation, validation of NAMs and the opportunities to move away from reliance on animal tests. Case study practices and data sharing, ensuring reproducibility of NAMs, were viewed as crucial to the improvement of non-animal test approaches for systemic toxicity.

Human Cell-Based in vitro Phenotypic Profiling for Drug Safety-Related Attrition

Ensuring the safety of new drugs is critically important to regulators, pharmaceutical researchers and patients alike. Even so, unexpected toxicities still account for 20–30% of clinical trial failures, in part due to the persistence of animal testing as the primary approach for de-risking new drugs. Clearly, improved methods for safety attrition that incorporate human-relevant biology are needed. This recognition has spurred interest in non-animal alternatives or new approach methodologies (NAMs) including in vitro models that utilize advances in the culture of human cell types to provide greater clinical relevance for assessing risk. These phenotypic assay systems use human primary and induced pluripotent stem cell-derived cells in various formats, including co-cultures and advanced cellular systems such as organoids, bioprinted tissues, and organs-on-a-chip. Despite the promise of these human-based phenotypic approaches, adoption of these platforms into drug discovery programs for reducing safety-related attrition has been slow. Here we discuss the value of large-scale human cell-based phenotypic profiling for incorporating human-specific biology into the de-risking process. We describe learnings from our experiences with human primary cell-based assays and analysis of clinically relevant reference datasets in developing in vitro-based toxicity signatures. We also describe how Adverse Outcome Pathway (AOP) frameworks can be used to integrate results from diverse platforms congruent with weight-of-evidence approaches from risk assessment to improve safety-related decisions in early discovery.

Review of high-content screening applications in toxicology

High-content screening (HCS) technology combining automated microscopy and quantitative image analysis can address biological questions in academia and the pharmaceutical industry. Various HCS experimental applications have been utilized in the research field of in vitro toxicology. In this review, we describe several HCS application approaches used for studying the mechanism of compound toxicity, highlight some challenges faced in the toxicological community, and discuss the future directions of HCS in regards to new models, new reagents, data management, and informatics. Many specialized areas of toxicology including developmental toxicity, genotoxicity, developmental neurotoxicity/neurotoxicity, hepatotoxicity, cardiotoxicity, and nephrotoxicity will be examined. In addition, several newly developed cellular assay models including induced pluripotent stem cells (iPSCs), three-dimensional (3D) cell models, and tissues-on-a-chip will be discussed. New genome-editing technologies (e.g., CRISPR/Cas9), data analyzing tools for imaging, and coupling with high-content assays will be reviewed. Finally, the applications of machine learning to image processing will be explored. These new HCS approaches offer a huge step forward in dissecting biological processes, developing drugs, and making toxicology studies easier.