Opportunities and Challenges for Integrating New In Vitro Methodologies in Hazard Testing and Risk Assessment

Overview of in vitro-in vivo extrapolation approaches for the risk assessment of nanomaterial toxicity

Nanomaterials are increasingly used in many applications due to their enhanced properties. To ensure their safety for humans and the environment, nanomaterials need to be evaluated for their potential risk. The risk assessment analysis on the nanomaterials based on animal or in vivo studies is accompanied by several concerns, including animal welfare, time and cost needed for the studies. Therefore, incorporating in vitro studies in the risk assessment process is increasingly considered. To be able to analyze the potential risk of nanomaterial to human health, there are factors to take into account. Utilizing in vitro data in the risk assessment analysis requires methods that can be used to translate in vitro data to predict in vivo phenomena (in vitro-in vivo extrapolation (IVIVE) methods) to be incorporated, to obtain a more accurate result. Apart from the experiments and species conversion (for example, translation between the cell culture, animal and human), the challenge also includes the unique properties of nanomaterials that might cause them to behave differently compared to the same materials in a bulk form. This overview presents the IVIVE techniques that are developed to extrapolate pharmacokinetics data or doses. A brief example of the IVIVE methods for chemicals is provided, followed by a more detailed summary of available IVIVE methods applied to nanomaterials. The IVIVE techniques discussed include the comparison between in vitro and in vivo studies, methods to rene the dose metric or the in vitro models, allometric approach, mechanistic modeling, Multiple-Path Particle Dosimetry (MPPD), methods using organ burden data and also approaches that are currently being developed.

Application of machine learning in the study of development, behavior, nerve, and genotoxicity of zebrafish

Machine learning (ML) as a novel model-based approach has been used in studying aquatic toxicology in the environmental field. Zebrafish, as an ideal model organism in aquatic toxicology research, has been widely used to study the toxic effects of various pollutants. However, toxicity testing on organisms may cause significant harm, consume considerable time and resources, and raise ethical concerns. Therefore, ML is used in related research to reduce animal experiments and assist researchers in conducting toxicological research. Although ML techniques have matured in various fields, research on ML-based aquatic toxicology is still in its infancy due to the lack of comprehensive large-scale toxicity databases for environmental pollutants and model organisms. Therefore, to better understand the recent research progress of ML in studying the development, behavior, nerve, and genotoxicity of zebrafish, this review mainly focuses on using ML modeling to assess and predict the toxic effects of zebrafish exposure to different toxic chemicals. Meanwhile, the opportunities and challenges faced by ML in the field of toxicology were analyzed. Finally, suggestions and perspectives were proposed for the toxicity studies of ML on zebrafish in future applications.

New methodological developments for testing the in vitro genotoxicity of nanomaterials: Comparison of 2D and 3D HepaRG liver cell models and classical and high throughput comet assay formats

Nanomaterials (NMs) are defined as materials with at least one external dimension below 100 nm. Their small size confers them interesting unique physico-chemical properties, hence NMs are increasingly used in a diversity of applications. However, the specific properties of NMs could also make them more harmful than their bulk counterparts. Therefore, there is a crucial need to deliver efficient NM hazard assessment in order to sustain the responsible development of nanotechnology. This study analysed the genotoxic potential of several NMs: one titanium dioxide (TiO2) and two zinc oxide NMs (ZnO) that were tested up to 100 μg/mL on 2D and 3D hepatic HepaRG models. Genotoxicity analysis was performed comparing the alkaline comet assay in classical and high throughput formats. Moreover, oxidative DNA lesions were investigated with the Fpg-modified comet assay. Results showed that TiO2 NMs were not cytotoxic and not genotoxic in either cell model, although a small increase in the % tail DNA was observed in 3D HepaRG cells at 100 μg/mL in the classical format. The two ZnO NMs (ZnO S. NMs a commercial suspension and NM110 provided by the European Union Joint Research Centre) induced a concentration-dependent increase in cytotoxicity that was more pronounced in the 2D (>20% cytotoxicity was observed for ZnO S. at concentrations greater than 25 μg/mL, and for NM 110 at 50 μg/mL) than in the 3D model (more than 20% cytotoxicity for ZnO S. NMs at 50 μg/mL). While ZnO S. NMs induced DNA damage associated with cytotoxicity (at 25 and 50 μg/mL in 2D and 50 μg/mL in 3D), NM110 showed a clear genotoxic effect at non-cytotoxic concentrations (25 μg/mL in 2D and at 25 and 50 μg/mL in 3D). No major differences could be observed in the comet assay in the presence or absence of the Fpg enzyme. High throughput analysis using CometChip® mostly confirmed the results obtained with the classical format, and even enhanced the detection of genotoxicity in the 3D model. In conclusion, this study demonstrated that new approach methodologies (NAMs), 3D models and the high throughput format for the comet assay, were more efficient in the detection of genotoxic effects, and are therefore promising approaches to improve hazard assessment of NMs.

The mediating role of AKT/ERK/JNK signaling on the malignant phenotype of microcystin-LR in gastric adenocarcinoma cells

Microcystin-leucine arginine (MC-LR), a widely distributed and highly toxic environmental pollutant, plays crucial roles in cancer malignancy by activating characteristically toxic signaling pathways. Traditional animal-based toxicity evaluation methods have proven insufficient for identifying the specific role of these signaling pathways. Therefore, this study aimed to uncover the regulatory relationship between the toxic pathways and the progression of gastric cancer (GC). The findings provide novel avenues for conducting in vitro toxicity tests based on the investigated pathways. We found that MC-LR promoted the migration and invasion of SGC-7901 cells while simultaneously inhibiting their apoptosis in a dose-dependent manner. This observed cytotoxicity was primarily mediated through the AKT, JNK, and ERK signaling pathways. By using a mediation analysis model, we determined that AKT and ERK exhibited competitive effects in MC-LR-treated GC malignancy, while AKT and JNK acted independently from one another. This study establishes an in vitro toxicity test model of MC-LR based on toxicity-related pathways and underscores the pivotal roles of AKT, ERK, and JNK signaling in MC-LR toxicity. The findings offer a novel, fundamental framework for conducting chemical toxicity risk assessment.

In vitro data for fire pollutants: contribution of studies using human cell models towards firefighters' occupational

Firefighters are the principal line of defense against fires, being at elevated risk of exposure to health-relevant pollutants released during fires and burning processes. Although many biomonitoring studies exist, only a limited number of human in vitro investigations in fire risk assessment are currently available. In vitro studies stand out as valuable tools to assess the toxicity mechanisms involved following exposure to fire pollutants at a cellular level. The aim of the present review was to contextualize existing in vitro studies using human cell models exposed to chemicals emitted from fire emissions and wood smoke and discuss the implications of the observed toxic outcomes on adverse health effects detected in firefighters. Most of the reported in vitro investigations focused on monocultures respiratory models and exposure to particulate matter (PM) extracts collected from fire effluents. Overall, (1) a decrease in cellular viability, (2) enhanced oxidative stress, (3) increased pro-inflammatory cytokines levels and (4) elevated cell death frequencies were noted. However, limited information remains regarding the toxicity mechanisms initiated by firefighting activities. Hence, more studies employing advanced in vitro models and exposure systems using human cell lines are urgently needed taking into consideration different routes of exposure and health-related pollutants released from fires. Data are needed to establish and define firefighters' occupational exposure limits and to propose mitigation strategies to promote beneficial human health.

A Review of Performance Prediction Based on Machine Learning in Materials Science

With increasing demand in many areas, materials are constantly evolving. However, they still have numerous practical constraints. The rational design and discovery of new materials can create a huge technological and social impact. However, such rational design and discovery require a holistic, multi-stage design process, including the design of the material composition, material structure, material properties as well as process design and engineering. Such a complex exploration using traditional scientific methods is not only blind but also a huge waste of time and resources. Machine learning (ML), which is used across data to find correlations in material properties and understand the chemical properties of materials, is being considered a new way to explore the materials field. This paper reviews some of the major recent advances and applications of ML in the field of properties prediction of materials and discusses the key challenges and opportunities in this cross-cutting area.

Experimental and Computational Nanotoxicology-Complementary Approaches for Nanomaterial Hazard Assessment

The growing development and applications of nanomaterials lead to an increasing release of these materials in the environment. The adverse effects they may elicit on ecosystems or human health are not always fully characterized. Such potential toxicity must be carefully assessed with the underlying mechanisms elucidated. To that purpose, different approaches can be used. First, experimental toxicology consisting of conducting in vitro or in vivo experiments (including clinical studies) can be used to evaluate the nanomaterial hazard. It can rely on variable models (more or less complex), allowing the investigation of different biological endpoints. The respective advantages and limitations of in vitro and in vivo models are discussed as well as some issues associated with experimental nanotoxicology. Perspectives of future developments in the field are also proposed. Second, computational nanotoxicology, i.e., in silico approaches, can be used to predict nanomaterial toxicity. In this context, we describe the general principles, advantages, and limitations especially of quantitative structure–activity relationship (QSAR) models and grouping/read-across approaches. The aim of this review is to provide an overview of these different approaches based on examples and highlight their complementarity.

The Road to Achieving the European Commission's Chemicals Strategy for Nanomaterial Sustainability-A PATROLS Perspective on New Approach Methodologies

The European Green Deal outlines ambitions to build a more sustainable, climate neutral, and circular economy by 2050. To achieve this, the European Commission has published the Chemicals Strategy for Sustainability: Towards a Toxic-Free Environment, which provides targets for innovation to better protect human and environmental health, including challenges posed by hazardous chemicals and animal testing. The European project PATROLS (Physiologically Anchored Tools for Realistic nanOmateriaL hazard aSsessment) has addressed multiple aspects of the Chemicals Strategy for Sustainability by establishing a battery of new approach methodologies, including physiologically anchored human and environmental hazard assessment tools to evaluate the safety of engineered nanomaterials. PATROLS has delivered and improved innovative tools to support regulatory decision-making processes. These tools also support the need for reducing regulated vertebrate animal testing; when used at an early stage of the innovation pipeline, the PATROLS tools facilitate the safe and sustainable development of new nano-enabled products before they reach the market.

Towards More Human and Humane Testing: The Role of the Device Supplier Industry

In vivo testing has been the gold standard for preclinical drug development and toxicology. However, animal-based methods often lack human relevance and have a low predictability rate, not to mention the enormous ethical and financial concerns associated with their use. For instance, according to the US Congressional Budget Office (cbo.gov), it takes an average of 10.5 years to take a compound from the preclinical phase to the market, with a cost of US$1-US$2 billion. 90% of drugs that are tested in animals and enter clinical trials fail due to lack of safety and efficacy - this fact questions the significance of in vivo testing. Cells in culture can recapitulate certain aspects of physiology and disease, as well as indicate drug responses and toxicity. Thus, they represent a sophisticated human-relevant and humane alternative. With advances in the in vitro field, it is anticipated that confidence will be gained towards a move away from traditional in vivo models. Specialised supplier industries have been a driving force in the transition to non-animal research, by translating new approach methodologies into scalable products that have been adopted by the regulatory and testing industries - but we are still at the beginning. In this article, we introduce the perspective of the device supplier industry on the current challenges and opportunities surrounding the adoption of new in vitro methods, with the goal of promoting effective co-operation with scientists and other stakeholders. In addition, we highlight some examples of where non-animal approaches have been used in regulatory submissions, as well as listing some educational and training resources that can help when selecting the most appropriate assay.

Recent advancements and application of in vitro models for predicting inhalation toxicity in humans

Animals have been indispensable in testing chemicals that can pose a risk to human health, including those delivered by inhalation. In recent years, the combination of societal debate on the use of animals in research and testing, the drive to continually enhance testing methodologies, and technology advancements have prompted a range of initiatives to develop non-animal alternative approaches for toxicity testing. In this review, we discuss emerging in vitro techniques being developed for the testing of inhaled compounds. Advanced tissue models that are able to recreate the human response to toxic exposures alongside examples of their ability to complement in vivo techniques are described. Furthermore, technology being developed that can provide multi-organ toxicity assessments are discussed.