The value of selected in vitro and in silico methods to predict acute oral toxicity in a regulatory context: Results from the European Project ACuteTox

Comparative case study on NAMs: towards enhancing specific target organ toxicity analysis

Traditional risk assessment methodologies in toxicology have relied upon animal testing, despite concerns regarding interspecies consistency, reproducibility, costs, and ethics. New Approach Methodologies (NAMs), including cell culture and multi-level omics analyses, hold promise by providing mechanistic information rather than assessing organ pathology. However, NAMs face limitations, like lacking a whole organism and restricted toxicokinetic interactions. This is an inherent challenge when it comes to the use of omics data from in vitro studies for the prediction of organ toxicity in vivo. One solution in this context are comparative in vitro-in vivo studies as they allow for a more detailed assessment of the transferability of the respective NAM data. Hence, hepatotoxic and nephrotoxic pesticide active substances were tested in human cell lines and the results subsequently related to the biology underlying established effects in vivo. To this end, substances were tested in HepaRG and RPTEC/tERT1 cells at non-cytotoxic concentrations and analyzed for effects on the transcriptome and parts of the proteome using quantitative real-time PCR arrays and multiplexed microsphere-based sandwich immunoassays, respectively. Transcriptomics data were analyzed using three bioinformatics tools. Where possible, in vitro endpoints were connected to in vivo observations. Targeted protein analysis revealed various affected pathways, with generally fewer effects present in RPTEC/tERT1. The strongest transcriptional impact was observed for Chlorotoluron in HepaRG cells (increased CYP1A1 and CYP1A2 expression). A comprehensive comparison of early cellular responses with data from in vivo studies revealed that transcriptomics outperformed targeted protein analysis, correctly predicting up to 50% of in vivo effects.

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.

In Silico Models for Predicting Acute Systemic Toxicity

In this chapter, we give a brief overview of the regulatory requirements for acute systemic toxicity information in the European Union, and we review structure-based computational models that are available and potentially useful in the assessment of acute systemic toxicity. Emphasis is placed on quantitative structure-activity relationship (QSAR) models implemented by means of a range of software tools. The most recently published literature models for acute systemic toxicity are also discussed, and perspectives for future developments in this field are offered.

An overview of current practices for regulatory risk assessment with lessons learnt from cosmetics in the European Union

Risk assessments of various types of chemical compounds are carried out in the European Union (EU) foremost to comply with legislation and to support regulatory decision-making with respect to their safety. Historically, risk assessment has relied heavily on animal experiments. However, the EU is committed to reduce animal experimentation and has implemented several legislative changes, which have triggered a paradigm shift towards human-relevant animal-free testing in the field of toxicology, in particular for risk assessment. For some specific endpoints, such as skin corrosion and irritation, validated alternatives are available whilst for other endpoints, including repeated dose systemic toxicity, the use of animal data is still central to meet the information requirements stipulated in the different legislations. The present review aims to provide an overview of established and more recently introduced methods for hazard assessment and risk characterisation for human health, in particular in the context of the EU Cosmetics Regulation (EC No 1223/2009) as well as the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) Regulation (EC 1907/2006).

In vitro prediction of clinical signs of respiratory toxicity in rats following inhalation exposure

To date there are no OECD validated alternative approaches to study toxicity following inhalation exposure to airborne chemicals. The available OECD test guidelines for acute inhalation toxicity aim to estimate a value of the lethal air concentration of the test chemical leading to the death of 50% of the exposed animals (LC50), to satisfy hazard classification and labelling requirements. This paper explores the view that alternative approaches must compare to outcomes of existing guideline methods to become accepted and implemented in a regulatory context. This case study describes the initiatives taken to validate the lung surfactant bioassay, an in vitro cell-free method, and discusses the challenges faced. While the lung surfactant bioassay could not predict the GHS classification for acute inhalation toxicity of 26 chemicals, the assay successfully predicted the clinical signs of respiratory toxicity observed during or shortly after exposure in vivo as reported in registration dossiers. The lung surfactant bioassay is a promising alternative approach to assess the potential of chemicals to cause changes to respiration remaining after exposure (indicating decreased lung function), and can be combined with other test methods in an integrated approach to testing and assessment of inhaled substances.

Prediction of Human Lethal Doses and Concentrations of MEIC Chemicals from Rodent LD50 Values: An Attempt to Make Some Reparation

The prediction of human toxicities from animal toxicity tests is often poor, and is now discouraged and in some cases banned, especially those involving the LD₅₀ test. However, there is a vast number of historical LD₅₀ data in both public and in-house repositories that are being put to little use. This study examined the correlations between human lethality (doses and concentrations) of 36 MEIC chemicals and the median values of a large number of mouse and rat LD₅₀ values obtained for four different routes of administration. The best correlations were found with mouse and rat intraperitoneal LD₅₀ values (r² = 0.838 and 0.810 for human lethal dose, and r² = 0.753 and 0.785 for human lethal concentration). The results show that excellent prediction of human lethal dose and concentration can be made, for this series of chemicals at least, by using uncurated rodent LD₅₀ values, thus offering some reparation for the millions of rodent lives sacrificed in LD₅₀ testing.

Theoretical consideration on the prediction of in vivo toxicity from in vitro toxicity: Effect of bio-uptake equilibrium, kinetics and mode of action

Although in vitro assay is an ideal alternative method for the in vivo toxicity prediction, different in vivo-in vitro correlations have been observed for the toxicity endpoints obtained from different levels of species. In this paper, theoretical in vivo-in vitro toxicity correlations have been developed for cytotoxicity versus human, mammalian and fish toxicity, respectively. These theoretical models were then used to investigate the correlations and the influencing factors between in vivo and in vitro toxicity. Bio-uptake equilibrium theory can well explain why there is a significant correlation between fish and cell toxicity (R² = 0.70); why human toxicity is very close to fish toxicity; and why hydrophobic compounds exhibit relatively greater toxicity than reactive or specifically-acting compounds to human and fish as compared to cells. The kinetic theory can well explain why there is a very poor relationship between mammal and cell toxicity (R² = 0.44). This paper reveals that polar and ionized compounds can more easily pass through cell membrane and have greater bioconcentration potential. Increasing of hydrophobicity and ionization can increase the cytotoxicity. Inclusion of descriptors representing hydrophobicity, ionization, acidity and absorption into the correlation equations can significantly improve the correlations of cytotoxicity with human and fish toxicity (R² > 0.8), but not with mammal toxicity (R² = 0.49). These descriptors reflect the differences of the toxicodynamics and toxicokinetics between cells and organisms.

Drug Discovery

Modern chemistry foundations were made in between the 18th and 19th centuries and have been extended in 20th century. R&D towards synthetic chemistry was introduced during the 1960s. Development of new molecular drugs from the herbal plants to synthetic chemistry is the fundamental scientific improvement. About 10-14 years are needed to develop a new molecule with an average cost of more than $800 million. Pharmaceutical industries spend the highest percentage of revenues, but the achievement of desired molecular entities into the market is not increasing proportionately. As a result, an approximate of 0.01% of new molecular entities are approved by the FDA. The highest failure rate is due to inadequate efficacy exhibited in Phase II of the drug discovery and development stage. Innovative technologies such as combinatorial chemistry, DNA sequencing, high-throughput screening, bioinformatics, computational drug design, and computer modeling are now utilized in the drug discovery. These technologies can accelerate the success rates in introducing new molecular entities into the market.

Longitudinal investigation of the metabolome of 3D aggregating brain cell cultures at different maturation stages by 1H HR-MAS NMR

The aim of the present study was to establish the developmental profile of metabolic changes of 3D aggregating brain cell cultures by ¹H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy. The histotypic 3D brain aggregate, containing all brain cell types, is an excellent model for mechanistic studies including OMICS analysis; however, their metabolic profile has not been yet fully investigated. Chemometric analysis revealed a clear separation of samples from the different maturation time points. Metabolite concentration evolutions could be followed and revealed strong and various metabolic alterations. The strong metabolite evolution emphasizes the brain modeling complexity during maturation, possibly reflecting physiological processes of brain tissue development. The small observed intra- and inter-experimental variabilities show the robustness of the combination of ¹H-HR-MAS NMR and 3D brain aggregates, making it useful to investigate mechanisms of toxicity that will ultimately contribute to improve predictive neurotoxicology. Graphical Abstract ᅟ.

One science-driven approach for the regulatory implementation of alternative methods: A multi-sector perspective

EU regulations call for the use of alternative methods to animal testing. During the last decade, an increasing number of alternative approaches have been formally adopted. In parallel, new 3Rs-relevant technologies and mechanistic approaches have increasingly contributed to hazard identification and risk assessment evolution. In this changing landscape, an EPAA meeting reviewed the challenges that different industry sectors face in the implementation of alternative methods following a science-driven approach. Although clear progress was acknowledged in animal testing reduction and refinement thanks to an integration of scientifically robust approaches, the following challenges were identified: i) further characterization of toxicity pathways; ii) development of assays covering current scientific gaps, iii) better characterization of links between in vitro readouts and outcome in the target species; iv) better definition of alternative method applicability domains, and v) appropriate implementation of the available approaches. For areas having regulatory adopted alternative methods (e.g., vaccine batch testing), harmonised acceptance across geographical regions was considered critical for broader application. Overall, the main constraints to the application of non-animal alternatives are the still existing gaps in scientific knowledge and technological limitations. The science-driven identification of most appropriate methods is key for furthering a multi-sectorial decrease in animal testing.

Discriminating modes of toxic action in mice using toxicity in BALB/c mouse fibroblast (3T3) cells

The objective of this study was to determine whether toxicity in mouse fibroblast cells (3T3 cells) could predict toxicity in mice. Synthesized data on toxicity was subjected to regression analysis and it was observed that relationship of toxicities between mice and 3T3 cells was not strong (R² = 0.41). Inclusion of molecular descriptors (e.g. ionization, pKa) improved the regression to R² = 0.56, indicating that this relationship is influenced by kinetic processes of chemicals or specific toxic mechanisms associated to the compounds. However, to determine if we were able to discriminate modes of action (MOAs) in mice using the toxicities generated from 3T3 cells, compounds were first classified into "baseline" and "reactive" guided by the toxic ratio (TR) for each compound in mice. Sequence, binomial and recursive partitioning analyses provided strong predictions of MOAs in mice based upon toxicities in 3T3 cells. The correct classification of MOAs based on these methods was 86%. Nearly all the baseline compounds predicted from toxicities in 3T3 cells were identified as baseline compounds from the TR in mice. The incorrect assignment of MOAs for some compounds is hypothesized to be due to experimental uncertainty that exists in toxicity assays for both mice and 3T3 cells. Conversely, lack of assignment can also arise because some reactive compounds have MOAs that are different in mice compared to 3T3 cells. The methods developed here are novel and contribute to efforts to reduce animal numbers in toxicity tests that are used to evaluate risks associated with organic pollutants in the environment.

Alternative approaches for identifying acute systemic toxicity: Moving from research to regulatory testing

Acute systemic toxicity testing provides the basis for hazard labeling and risk management of chemicals. A number of international efforts have been directed at identifying non-animal alternatives for in vivo acute systemic toxicity tests. A September 2015 workshop, Alternative Approaches for Identifying Acute Systemic Toxicity: Moving from Research to Regulatory Testing, reviewed the state-of-the-science of non-animal alternatives for this testing and explored ways to facilitate implementation of alternatives. Workshop attendees included representatives from international regulatory agencies, academia, nongovernmental organizations, and industry. Resources identified as necessary for meaningful progress in implementing alternatives included compiling and making available high-quality reference data, training on use and interpretation of in vitro and in silico approaches, and global harmonization of testing requirements. Attendees particularly noted the need to characterize variability in reference data to evaluate new approaches. They also noted the importance of understanding the mechanisms of acute toxicity, which could be facilitated by the development of adverse outcome pathways. Workshop breakout groups explored different approaches to reducing or replacing animal use for acute toxicity testing, with each group crafting a roadmap and strategy to accomplish near-term progress. The workshop steering committee has organized efforts to implement the recommendations of the workshop participants.

Development and characterization of a human embryonic stem cell-derived 3D neural tissue model for neurotoxicity testing

Alternative models for more rapid compound safety testing are of increasing demand. With emerging techniques using human pluripotent stem cells, the possibility of generating human in vitro models has gained interest, as factors related to species differences could be potentially eliminated. When studying potential neurotoxic effects of a compound it is of crucial importance to have both neurons and glial cells. We have successfully developed a protocol for generating in vitro 3D human neural tissues, using neural progenitor cells derived from human embryonic stem cells. These 3D neural tissues can be maintained for two months and undergo progressive differentiation. We showed a gradual decreased expression of early neural lineage markers, paralleled by an increase in markers specific for mature neurons, astrocytes and oligodendrocytes. At the end of the two-month culture period the neural tissues not only displayed synapses and immature myelin sheaths around axons, but electrophysiological measurements also showed spontaneous activity. Neurotoxicity testing - comparing non-neurotoxic to known neurotoxic model compounds - showed an expected increase in the marker of astroglial reactivity after exposure to known neurotoxicants methylmercury and trimethyltin. Although further characterization and refinement of the model is required, these results indicate its potential usefulness for in vitro neurotoxicity testing.

Exploring waiving opportunities for mammalian acute systemic toxicity tests

A survey was carried out to explore opportunities for waiving mammalian acute systemic toxicity tests. We were interested in finding out whether data from a sub-acute toxicity test could be used to predict the outcome of an acute systemic toxicity test. The survey was directed at experts in the field of toxicity testing, and was carried out in the context of the upcoming 2018 final registration deadline for chemicals under the EU REACH Regulation. In addition to the survey, a retrospective data analysis of chemicals that had already been registered with the European Chemicals Agency, and for which both acute and sub-acute toxicity data were available, was carried out. This data analysis was focused on chemicals that were administered via the oral route. The answers to the questionnaire showed a willingness to adopt waiving opportunities. In addition, the responses showed that data from a sub-acute toxicity test or dose-range finding study might be useful for predicting chemicals that do not require classification for acute oral toxicity (LD50 > 2000mg/kg body weight). However, with the exception of substances that fall into the non-classified category, it is difficult to predict current acute oral toxicity categories.

In Silico Models for Acute Systemic Toxicity

In this chapter, we give an overview of the regulatory requirements for acute systemic toxicity information in the European Union, and we review the availability of structure-based computational models that are available and potentially useful in the assessment of acute systemic toxicity. The most recently published literature models for acute systemic toxicity are also discussed, and perspectives for future developments in this field are offered.

Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing

The recent advent of microphysiological systems - microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro - is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various dedicated research programs in Europe and Asia have led recently to the first cutting-edge achievements of human single-organ and multi-organ engineering based on microphysiological systems. The expectation is that test systems established on this basis would model various disease stages, and predict toxicity, immunogenicity, ADME profiles and treatment efficacy prior to clinical testing. Consequently, this technology could significantly affect the way drug substances are developed in the future. Furthermore, microphysiological system-based assays may revolutionize our current global programs of prioritization of hazard characterization for any new substances to be used, for example, in agriculture, food, ecosystems or cosmetics, thus, replacing laboratory animal models used currently. Thirty-six experts from academia, industry and regulatory bodies present here the results of an intensive workshop (held in June 2015, Berlin, Germany). They review the status quo of microphysiological systems available today against industry needs, and assess the broad variety of approaches with fit-for-purpose potential in the drug development cycle. Feasible technical solutions to reach the next levels of human biology in vitro are proposed. Furthermore, key organ-on-a-chip case studies, as well as various national and international programs are highlighted. Finally, a roadmap into the future is outlined, to allow for more predictive and regulatory-accepted substance testing on a global scale.

Current and Future Perspectives on the Development, Evaluation, and Application of in Silico Approaches for Predicting Toxicity

Exploiting non-testing approaches to predict toxicity early in the drug discovery development cycle is a helpful component in minimizing expensive drug failures due to toxicity being identified in late development or even during clinical trials. Changes in regulations in the industrial chemicals and cosmetics sectors in recent years have prompted a significant number of advances in the development, application, and assessment of non-testing approaches, such as (Q)SARs. Many efforts have also been undertaken to establish guiding principles for performing read-across within category and analogue approaches. This review offers a perspective, as taken from these sectors, of the current status of non-testing approaches, their evolution in light of the advances in high-throughput approaches and constructs such as adverse outcome pathways, and their potential relevance for drug discovery. It also proposes a workflow for how non-testing approaches could be practically integrated within testing and assessment strategies.

In silico ADME/T modelling for rational drug design

In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

Big data in chemical toxicity research: the use of high-throughput screening assays to identify potential toxicants

High-throughput screening (HTS) assays that measure the in vitro toxicity of environmental compounds have been widely applied as an alternative to in vivo animal tests of chemical toxicity. Current HTS studies provide the community with rich toxicology information that has the potential to be integrated into toxicity research. The available in vitro toxicity data is updated daily in structured formats (e.g., deposited into PubChem and other data-sharing web portals) or in an unstructured way (papers, laboratory reports, toxicity Web site updates, etc.). The information derived from the current toxicity data is so large and complex that it becomes difficult to process using available database management tools or traditional data processing applications. For this reason, it is necessary to develop a big data approach when conducting modern chemical toxicity research. In vitro data for a compound, obtained from meaningful bioassays, can be viewed as a response profile that gives detailed information about the compound's ability to affect relevant biological proteins/receptors. This information is critical for the evaluation of complex bioactivities (e.g., animal toxicities) and grows rapidly as big data in toxicology communities. This review focuses mainly on the existing structured in vitro data (e.g., PubChem data sets) as response profiles for compounds of environmental interest (e.g., potential human/animal toxicants). Potential modeling and mining tools to use the current big data pool in chemical toxicity research are also described.

A Tutorial for Analysing the Cost-effectiveness of Alternative Methods for Assessing Chemical Toxicity: The Case of Acute Oral Toxicity Prediction

Compared with traditional animal methods for toxicity testing, in vitro and in silico methods are widely considered to permit a more cost-effective assessment of chemicals. However, how to assess the cost-effectiveness of alternative methods has remained unclear. This paper offers a user-oriented tutorial for applying cost-effectiveness analysis (CEA) to alternative (non-animal) methods. The purpose is to illustrate how CEA facilitates the identification of the alternative method, or the combination of methods, that offers the highest information gain per unit of cost. We illustrate how information gains and costs of single methods and method combinations can be assessed. By using acute oral toxicity as an example, we apply CEA to a set of four in silico methods (ToxSuite, TOPKAT, TEST, ADMET Predictor), one in vitro method (the 3T3 Neutral Red Uptake cytotoxicity assay), and various combinations of these methods. Our results underline that in silico tools are more cost-effective than the in vitro test. Battery combinations of alternative methods, however, do not necessarily outperform single methods, because additional information gains from the battery are easily outweighed by additional costs.

Selection of test methods to be included in a testing strategy to predict acute oral toxicity: an approach based on statistical analysis of data collected in phase 1 of the ACuteTox project

More than 50 different in vitro and in silico methods assessing specific organ- and system-toxicity, such as haemato-, neuro-, nephro- and hepatotoxicity, as well as intestinal absorption, distribution and metabolism, have been used in the first phase of the ACuteTox project to test a common set of 57 chemicals. This paper describes the methods used for statistical evaluation of concentration-response data collected for each of the endpoint assays, and for the development of a testing strategy applicable for acute toxicity classification of chemicals based on the achieved results of the concentration-response analysis. A final list of in vitro test methods considered to be promising candidates for building blocks of the testing strategy is presented. Only these selected test methods were further investigated in the prevalidation phase of the project. The test methods were chosen according to their reproducibility and reliability and most importantly, according to their potential to classify chemicals into the official acute oral toxicity categories of the EU Classification, Labelling and Packaging (CLP) Regulation. The potential of the test methods to correctly classify the chemicals was assessed by Classification and Regression Trees (CART) analysis.

Evaluation of aggregating brain cell cultures for the detection of acute organ-specific toxicity

As part of the ACuteTox project aimed at the development of non-animal testing strategies for predicting human acute oral toxicity, aggregating brain cell cultures (AGGR) were examined for their capability to detect organ-specific toxicity. Previous multicenter evaluations of in vitro cytotoxicity showed that some 20% of the tested chemicals exhibited significantly lower in vitro toxicity as expected from in vivo toxicity data. This was supposed to be due to toxicity at supracellular (organ or system) levels. To examine the capability of AGGR to alert for potential organ-specific toxicants, concentration-response studies were carried out in AGGR for 86 chemicals, taking as endpoints the mRNA expression levels of four selected genes. The lowest observed effect concentration (LOEC) determined for each chemical was compared with the IC20 reported for the 3T3/NRU cytotoxicity assay. A LOEC lower than IC20 by at least a factor of 5 was taken to alert for organ-specific toxicity. The results showed that the frequency of alerts increased with the level of toxicity observed in AGGR. Among the chemicals identified as alert were many compounds known for their organ-specific toxicity. These findings suggest that AGGR are suitable for the detection of organ-specific toxicity and that they could, in conjunction with the 3T3/NRU cytotoxicity assay, improve the predictive capacity of in vitro toxicity testing.

Design of a testing strategy using non-animal based test methods: lessons learnt from the ACuteTox project

In the framework of toxicology, a testing strategy can be viewed as a series of steps which are taken to come to a final prediction about a characteristic of a compound under study. The testing strategy is performed as a single-step procedure, usually called a test battery, using simultaneously all information collected on different endpoints, or as tiered approach in which a decision tree is followed. Design of a testing strategy involves statistical considerations, such as the development of a statistical prediction model. During the EU FP6 ACuteTox project, several prediction models were proposed on the basis of statistical classification algorithms which we illustrate here. The final choice of testing strategies was not based on statistical considerations alone. However, without thorough statistical evaluations a testing strategy cannot be identified. We present here a number of observations made from the statistical viewpoint which relate to the development of testing strategies. The points we make were derived from problems we had to deal with during the evaluation of this large research project. A central issue during the development of a prediction model is the danger of overfitting. Procedures are presented to deal with this challenge.