Toward Rigorous Materials Production: New Approach Methodologies Have Extensive Potential to Improve Current Safety Assessment Practices

Roadmap towards safe and sustainable advanced and innovative materials. (Outlook for 2024-2030)

The adoption of innovative advanced materials holds vast potential, contingent upon addressing safety and sustainability concerns. The European Commission advocates the integration of Safe and Sustainable by Design (SSbD) principles early in the innovation process to streamline market introduction and mitigate costs. Within this framework, encompassing ecological, social, and economic factors is paramount. The NanoSafety Cluster (NSC) delineates key safety and sustainability areas, pinpointing unresolved issues and research gaps to steer the development of safe(r) materials. Leveraging FAIR data management and integration, alongside the alignment of regulatory aspects, fosters informed decision-making and innovation. Integrating circularity and sustainability mandates clear guidance, ensuring responsible innovation at every stage. Collaboration among stakeholders, anticipation of regulatory demands, and a commitment to sustainability are pivotal for translating SSbD into tangible advancements. Harmonizing standards and test guidelines, along with regulatory preparedness through an exchange platform, is imperative for governance and market readiness. By adhering to these principles, the effective and sustainable deployment of innovative materials can be realized, propelling positive transformation and societal acceptance.

Next Generation Risk Assessment approaches for advanced nanomaterials: Current status and future perspectives

This manuscript discusses the challenges of applying New Approach Methodologies (NAMs) for safe by design and regulatory risk assessment of advanced nanomaterials (AdNMs). The authors propose a framework for Next Generation Risk Assessment of AdNMs involving NAMs that is aligned to the conventional risk assessment paradigm. This framework is exposure-driven, endpoint-specific, makes best use of pre-existing information, and can be implemented in tiers of increasing specificity and complexity of the adopted NAMs. The tiered structure of the approach, which effectively combines the use of existing data with targeted testing will allow safety to be assessed cost-effectively and as far as possible with even more limited use of vertebrates. The regulatory readiness of state-of-the-art emerging NAMs is assessed in terms of Transparency, Reliability, Accessibility, Applicability, Relevance and Completeness, and their appropriateness for AdNMs is discussed in relation to each step of the risk assessment paradigm along with providing perspectives for future developments in the respective scientific and regulatory areas.

Learning from Safe-by-Design for Safe-and-Sustainable-by-Design: Mapping the current landscape of Safe-by-Design reviews, case studies, and frameworks

With the introduction of the European Commission's "Safe and Sustainable-by-Design" (SSbD) framework, the interest in understanding the implications of safety and sustainability assessments of chemicals, materials, and processes at early-innovation stages has skyrocketed. Our study focuses on the "Safe-by-Design" (SbD) approach from the nanomaterials sector, which predates the SSbD framework. In this assessment, SbD studies have been compiled and categorized into reviews, case studies, and frameworks. Reviews of SbD tools have been further classified as quantitative, qualitative, or toolboxes and repositories. We assessed the SbD case studies and classified them into three categories: safe(r)-by-modeling, safe(r)-by-selection, or safe(r)-by-redesign. This classification enabled us to understand past SbD work and subsequently use it to define future SSbD work so as to avoid confusion and possibilities of "SSbD-washing" (similar to greenwashing). Finally, the preexisting SbD frameworks have been studied and contextualized against the SSbD framework. Several key recommendations for SSbD based on our analysis can be made. Knowledge gained from existing approaches such as SbD, green and sustainable chemistry, and benign-by-design approaches needs to be preserved and effectively transferred to SSbD. Better incorporation of chemical and material functionality into the SSbD framework is required. The concept of lifecycle thinking and the stage-gate innovation model need to be reconciled for SSbD. The development of high-throughput screening models is critical for the operationalization of SSbD. We conclude that the rapid pace of both SbD and SSbD development necessitates a regular mapping of the newly published literature that is relevant to this field.

An integrated new approach methodology for inhalation risk assessment of safe and sustainable by design nanomaterials

The production and use of nanomaterials (NMs) has increased over the last decades posing relevant questions on their risk after release and exposure of the population or sub-populations. In this context, the safe and sustainable by design (SSbD) approach framework requires to assess the potential hazard connected with intrinsic properties of the material along the whole life cycle of the NM and/or of the nano enabled products. Moreover, in the last years, the use of new advanced methodologies (NAMs) has increasingly gained attention for the use of alternative methods in obtaining relevant information on NMs hazard and risk. Considering the SSbD and the NAMs frameworks, within the ASINA H2020 project, we developed new NAMs devoted at improving the hazard and risk definition of different Ag and TiO2 NPs. The NAMs are developed considering two air liquid interface exposure systems, the Vitrocell Cloud-α and the Cultex Compact module and the relevant steps to obtain reproducible exposures are described. The new NAMs build on the integration of environmental monitoring campaigns at nano-coating production sites, allowing the quantification by the multiple-path particle dosimetry (MPPD) model of the expected lung deposited dose in occupational settings. Starting from this information, laboratory exposures to the aerosolized NPs are performed by using air liquid interface exposure equipment and human alveolar cells (epithelial cells and macrophages), replicating the doses of exposure estimated in workers by MPPD. Preliminary results on cell viability and inflammatory responses are reported. The proposed NAMs may represent possible future reference procedures for assessing the NPs inhalation toxicology, supporting risk assessment at real exposure doses.

SciRAPnano: a pragmatic and harmonized approach for quality evaluation of in vitro toxicity data to support risk assessment of nanomaterials

Large amounts of nanotoxicity data from alternative non-animal (in vitro) test methods have been generated, but there is a lack of harmonized quality evaluation approaches for these types of data. Tools for scientifically sound and structured evaluation of the reliability and relevance of in vitro toxicity data to effectively inform regulatory hazard assessment of nanomaterials (NMs), are needed. Here, we present the development of a pragmatic approach to facilitate such evaluation. The tool was developed based on the Science in Risk Assessment and Policy (SciRAP) tool currently applicable to quality evaluation of chemical toxicity studies. The approach taken to develop the tool, referred to as SciRAPnano, included refinement of the original SciRAP in vitro tool through implementation of identified NM-relevant criteria, and further refined based on a set of case studies involving evaluation of 11 studies investigating in vitro toxicity of nano-sized titanium dioxide. Parameters considered cover key physicochemical properties as well as assay-specific aspects that impact NM toxicity, including NM interference with test methods and NM transformation. The final SciRAPnano tool contains 38 criteria for reporting quality, 19 criteria for methodological quality, and 4 guidance items to evaluate relevance. The approach covers essential parameters for pragmatic and harmonized evaluation of NM in vitro toxicity studies and allows for structured use of in vitro data in regulatory hazard assessment of NMs, including transparency on data quality.

Genome-wide DNA methylome and transcriptome changes induced by inorganic nanoparticles in human kidney cells after chronic exposure

The unique physicochemical properties make inorganic nanoparticles (INPs) an exciting tool in diagnosis and disease management. However, as INPs are relatively difficult to fully degrade and excrete, their unintended accumulation in the tissue might result in adverse health effects. Herein, we provide a methylome-transcriptome framework for chronic effects of INPs, commonly used in biomedical applications, in human kidney TH-1 cells. Renal clearance is one of the most important routes of nanoparticle excretion; therefore, a detailed evaluation of nanoparticle-mediated nephrotoxicity is an important task. Integrated analysis of methylome and transcriptome changes induced by INPs (PEG-AuNPs, Fe3O4NPs, SiO2NPs, and TiO2NPs) revealed significantly deregulated genes with functional classification in immune response, DNA damage, and cancer-related pathways. Although most deregulated genes were unique to individual INPs, a relatively high proportion of them encoded the transcription factors. Interestingly, FOS hypermethylation inversely correlating with gene expression was associated with all INPs exposures. Our study emphasizes the need for a more comprehensive investigation of INPs' biological safety, especially after chronic exposure.

Nanomaterial genotoxicity evaluation using the high-throughput p53-binding protein 1 (53BP1) assay

Toxicity evaluation of engineered nanomaterials is challenging due to the ever increasing number of materials and because nanomaterials (NMs) frequently interfere with commonly used assays. Hence, there is a need for robust, high-throughput assays with which to assess their hazard potential. The present study aimed at evaluating the applicability of a genotoxicity assay based on the immunostaining and foci counting of the DNA repair protein 53BP1 (p53-binding protein 1), in a high-throughput format, for NM genotoxicity assessment. For benchmarking purposes, we first applied the assay to a set of eight known genotoxic agents, as well as X-ray irradiation (1 Gy). Then, a panel of NMs and nanobiomaterials (NBMs) was evaluated with respect to their impact on cell viability and genotoxicity, and to their potential to induce reactive oxygen species (ROS) production. The genotoxicity recorded using the 53BP1 assay was confirmed using the micronucleus assay, also scored via automated (high-throughput) microscopy. The 53BP1 assay successfully identified genotoxic compounds on the HCT116 human intestinal cell line. None of the tested NMs showed any genotoxicity using the 53BP1 assay, except the positive control consisting in (CoO)(NiO) NMs, while only TiO2 NMs showed positive outcome in the micronucleus assay. Only Fe3O4 NMs caused significant elevation of ROS, not correlated to DNA damage. Therefore, owing to its adequate predictivity of the genotoxicity of most of the tested benchmark substance and its ease of implementation in a high throughput format, the 53BP1 assay could be proposed as a complementary high-throughput screening genotoxicity assay, in the context of the development of New Approach Methodologies.

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).

The State of the Art and Challenges of In Vitro Methods for Human Hazard Assessment of Nanomaterials in the Context of Safe-by-Design

The Safe-by-Design (SbD) concept aims to facilitate the development of safer materials/products, safer production, and safer use and end-of-life by performing timely SbD interventions to reduce hazard, exposure, or both. Early hazard screening is a crucial first step in this process. In this review, for the first time, commonly used in vitro assays are evaluated for their suitability for SbD hazard testing of nanomaterials (NMs). The goal of SbD hazard testing is identifying hazard warnings in the early stages of innovation. For this purpose, assays should be simple, cost-effective, predictive, robust, and compatible. For several toxicological endpoints, there are indications that commonly used in vitro assays are able to predict hazard warnings. In addition to the evaluation of assays, this review provides insights into the effects of the choice of cell type, exposure and dispersion protocol, and the (in)accurate determination of dose delivered to cells on predictivity. Furthermore, compatibility of assays with challenging advanced materials and NMs released from nano-enabled products (NEPs) during the lifecycle is assessed, as these aspects are crucial for SbD hazard testing. To conclude, hazard screening of NMs is complex and joint efforts between innovators, scientists, and regulators are needed to further improve SbD hazard testing.

A Novel Nanosafety Approach Using Cell Painting, Metabolomics, and Lipidomics Captures the Cellular and Molecular Phenotypes Induced by the Unintentionally Formed Metal-Based (Nano)Particles

Additive manufacturing (AM) or industrial 3D printing uses cutting-edge technologies and materials to produce a variety of complex products. However, the effects of the unintentionally emitted AM (nano)particles (AMPs) on human cells following inhalation, require further investigations. The physicochemical characterization of the AMPs, extracted from the filter of a Laser Powder Bed Fusion (L-PBF) 3D printer of iron-based materials, disclosed their complexity, in terms of size, shape, and chemistry. Cell Painting, a high-content screening (HCS) assay, was used to detect the subtle morphological changes elicited by the AMPs at the single cell resolution. The profiling of the cell morphological phenotypes, disclosed prominent concentration-dependent effects on the cytoskeleton, mitochondria, and the membranous structures of the cell. Furthermore, lipidomics confirmed that the AMPs induced the extensive membrane remodeling in the lung epithelial and macrophage co-culture cell model. To further elucidate the biological mechanisms of action, the targeted metabolomics unveiled several inflammation-related metabolites regulating the cell response to the AMP exposure. Overall, the AMP exposure led to the internalization, oxidative stress, cytoskeleton disruption, mitochondrial activation, membrane remodeling, and metabolic reprogramming of the lung epithelial cells and macrophages. We propose the approach of integrating Cell Painting with metabolomics and lipidomics, as an advanced nanosafety methodology, increasing the ability to capture the cellular and molecular phenotypes and the relevant biological mechanisms to the (nano)particle exposure.

Predicting nanomaterials pulmonary toxicity in animals by cell culture models: Achievements and perspectives

Animal experiments are highly relevant models for the assessment of toxicological effects of engineered nanomaterials (ENMs), due to lack of biomonitoring and epidemiological studies. However, the expanding number of ENMs with different physico-chemical properties strains this approach, as there are ethical concerns and economical challenges with the use of animals in toxicology. There is an urgent need for cell culture models that predict the level of toxicological responses in vivo, consequently reducing or replacing the use of animals in nanotoxicology. However, there is still a limited number of studies on in vitro-in vivo correlation of toxicological responses following ENMs exposure. In this review, we collected studies that have compared in vitro and in vivo toxic effects caused by ENMs. We discuss the influence of cell culture models and exposure systems on the predictability of in vitro models to equivalent toxic effects in animal lungs after pulmonary exposure to ENMs. In addition, we discuss approaches to qualitatively or quantitatively compare the effects in vitro and in vivo. The magnitude of toxicological responses in cells that are exposed in submerged condition is not systematically different from the response in cells exposed in air-liquid interface systems, and there appears to be similar ENMs hazard ranking between the two exposure systems. Overall, we show that simple in vitro models with cells exposed to ENMs in submerged condition can be used to predict toxic effects in vivo, and identify future strategies to improve the associations between in vitro and in vivo ENMs-induced pulmonary toxicity. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials.

Pre-validation of a reporter gene assay for oxidative stress for the rapid screening of nanobiomaterials

Engineered nanomaterials have been found to induce oxidative stress. Cellular oxidative stress, in turn, can result in the induction of antioxidant and detoxification enzymes which are controlled by the nuclear erythroid 2-related factor 2 (NRF2) transcription factor. Here, we present the results of a pre-validation study which was conducted within the frame of BIORIMA (“biomaterial risk management”) an EU-funded research and innovation project. For this we used an NRF2 specific chemically activated luciferase expression reporter gene assay derived from the human U2OS osteosarcoma cell line to screen for the induction of the NRF2 mediated gene expression following exposure to biomedically relevant nanobiomaterials. Specifically, we investigated Fe₃O₄-PEG-PLGA nanomaterials while Ag and TiO₂ “benchmark” nanomaterials from the Joint Research Center were used as reference materials. The viability of the cells was determined by using the Alamar blue assay. We performed an interlaboratory study involving seven different laboratories to assess the applicability of the NRF2 reporter gene assay for the screening of nanobiomaterials. The latter work was preceded by online tutorials to ensure that the procedures were harmonized across the different participating laboratories. Fe₃O₄-PEG-PLGA nanomaterials were found to induce very limited NRF2 mediated gene expression, whereas exposure to Ag nanomaterials induced NRF2 mediated gene expression. TiO₂ nanomaterials did not induce NRF2 mediated gene expression. The variability in the results obtained by the participating laboratories was small with mean intra-laboratory standard deviation of 0.16 and mean inter laboratory standard deviation of 0.28 across all NRF2 reporter gene assay results. We conclude that the NRF2 reporter gene assay is a suitable assay for the screening of nanobiomaterial-induced oxidative stress responses.

Human Apparent Volume of Distribution Predicts Bioaccumulation of Ionizable Organic Chemicals in Zebrafish Embryos

Chemicals with elevated bioaccumulation profiles present potential hazards to public health and the environment. Ionizable organic compounds (IOCs) increasingly represent a large proportion of commercial chemicals; however, historical approaches for bioaccumulation determinations are mainly developed for neutral chemicals, which were not appropriate for IOCs. Herein, we employed the zebrafish embryo, a common vertebrate model in environmental and biomedical studies, to elucidate toxicokinetics and bioconcentration of eight IOCs with diverse physicochemical properties and pharmacokinetic parameters. At an environmentally relevant pH (7.5), most IOCs exhibited rapid uptake and depuration in zebrafish, suggesting the ionized forms of IOCs are readily bioavailable. Bioconcentration factors (BCF) of these IOCs ranged from 0.0530 to 250 L·kg^-1 wet weight. The human pharmacokinetic proportionality factor, apparent volume of distribution (V_D), better predicted the BCF of selected IOCs than more commonly used hydrophobicity-based parameters (e.g., pH-dependent octanol-water distribution ratio, D_ow). Predictive bioaccumulation models for IOCs were constructed and validated using V_D alone or with D_ow. Significant relationships between fish BCF and human V_D, which is readily available for pharmaceuticals, highlighted the utility of biologically based "read-across" approaches for predicting bioaccumulative potential of IOCs. Our novel findings thus provided an understanding of the partitioning behavior and improved predictive bioconcentration modeling for IOCs.

FAIR assessment tools: evaluating use and performance

Publishing research data using a findable, accessible, interoperable, and reusable (FAIR) approach is paramount to further innovation in many areas of research. In particular in developing innovative approaches to predict (eco)toxicological risks in (nano or advanced) material design where efficient use of existing data is essential. The use of tools assessing the FAIRness of data helps the future improvement of data FAIRness and therefore their re-use. This paper reviews ten FAIR assessment tools that have been evaluated and characterized using two datasets from the nanomaterials and microplastics risk assessment domain. The tools were grouped into four categories: online and offline self-assessment survey based, online (semi-) automated and other tools. We found that the online self-assessment tools can be used for a quick scan of a user's dataset due to their ease of use, little need for experience and short time investment. When a user is looking to assess full databases, and not just datasets, for their FAIRness, (semi-)automated tools are more practical. The offline assessment tools were found to be limited and unreliable due to a lack of guidance and an under-developed state. To further characterize the usability, two datasets were run through all tools to check the similarity in the tools' results. As most of the tools differ in their implementation of the FAIR principles, a large variety in outcomes was obtained. Furthermore, it was observed that only one tool gives recommendations to the user on how to improve the FAIRness of the evaluated dataset. This paper gives clear recommendations for both the user and the developer of FAIR assessment tools.

Application of cross-validation strategies to avoid overestimation of performance of 2D-QSAR models for the prediction of aquatic toxicity of chemical mixtures

The quantitative structure-activity relationship (QSAR) modelling of mixtures is not as simple as that for individual chemicals, and it needs additional care to avoid overestimation of the performance. In this research, we have developed a 2D-QSAR model using only 2D interpretable and reproducible descriptors to predict the aquatic toxicity of mixtures of polar and non-polar narcotic substances present in the environment. Partial least squares (PLS) regression has been used to model the response variable (log 1/EC50 against Photobacterium phosphoreum) and the structural features of 84 binary mixtures of polar and nonpolar narcotic toxicants complying with the Organization of Economic Co-operation and Development (OECD) protocols. The model was cross-validated by mixtures-out and compounds-out cross-validation to nullify the developmental bias. The reliability of prediction of the model has been judged by the Prediction Reliability Indicator (PRI) tool using a newly designed set. The new model is robust, reproducible, extremely predictive, easily interpretable, and can be used for reliable prediction of aquatic toxicity of any untested chemical mixtures within the applicability domain. We have additionally used a machine learning-based chemical read-across algorithm in this study to improve the quality of predictions for the toxicity of the mixtures with the modelled descriptors.

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.

How Structured Metadata Acquisition Contributes to the Reproducibility of Nanosafety Studies: Evaluation by a Round-Robin Test

It has been widely recognized that nanosafety studies are limited in reproducibility, caused by missing or inadequate information and data gaps. Reliable and comprehensive studies should be performed supported by standards or guidelines, which need to be harmonized and usable for the multidisciplinary field of nanosafety research. The previously described minimal information table (MIT), based on existing standards or guidelines, represents one approach towards harmonization. Here, we demonstrate the applicability and advantages of the MIT by a round-robin test. Its modular structure enables describing individual studies comprehensively by a combination of various relevant aspects. Three laboratories conducted a WST-1 cell viability assay using A549 cells to analyze the effects of the reference nanomaterials NM101 and NM110 according to predefined (S)OPs. The MIT contains relevant and defined descriptive information and quality criteria and thus supported the implementation of the round-robin test from planning, investigation to analysis and data interpretation. As a result, we could identify sources of variability and justify deviating results attributed to differences in specific procedures. Consequently, the use of the MIT contributes to the acquisition of reliable and comprehensive datasets and therefore improves the significance and reusability of nanosafety studies.

Nextcast: A software suite to analyse and model toxicogenomics data

The recent advancements in toxicogenomics have led to the availability of large omics data sets, representing the starting point for studying the exposure mechanism of action and identifying candidate biomarkers for toxicity prediction. The current lack of standard methods in data generation and analysis hampers the full exploitation of toxicogenomics-based evidence in regulatory risk assessment. Moreover, the pipelines for the preprocessing and downstream analyses of toxicogenomic data sets can be quite challenging to implement. During the years, we have developed a number of software packages to address specific questions related to multiple steps of toxicogenomics data analysis and modelling. In this review we present the Nextcast software collection and discuss how its individual tools can be combined into efficient pipelines to answer specific biological questions. Nextcast components are of great support to the scientific community for analysing and interpreting large data sets for the toxicity evaluation of compounds in an unbiased, straightforward, and reliable manner. The Nextcast software suite is available at: ( https://github.com/fhaive/nextcast).

Quantifying Emission Factors and Setting Conditions of Use According to ECHA Chapter R.14 for a Spray Process Designed for Nanocoatings-A Case Study

Spray coatings' emissions impact to the environmental and occupational exposure were studied in a pilot-plant. Concentrations were measured inside the spray chamber and at the work room in Near-Field (NF) and Far-Field (FF) and mass flows were analyzed using a mechanistic model. The coating was performed in a ventilated chamber by spraying titanium dioxide doped with nitrogen (TiO2N) and silver capped by hydroxyethylcellulose (Ag-HEC) nanoparticles (NPs). Process emission rates to workplace, air, and outdoor air were characterized according to process parameters, which were used to assess emission factors. Full-scale production exposure potential was estimated under reasonable worst-case (RWC) conditions. The measured TiO2-N and Ag-HEC concentrations were 40.9 TiO2-μg/m3 and 0.4 Ag-μg/m3 at NF (total fraction). Under simulated RWC conditions with precautionary emission rate estimates, the worker's 95th percentile 8-h exposure was ≤171 TiO2 and ≤1.9 Ag-μg/m3 (total fraction). Environmental emissions via local ventilation (LEV) exhaust were ca. 35 and 140 mg-NP/g-NP, for TiO2-N and Ag-HEC, respectively. Under current situation, the exposure was adequately controlled. However, under full scale production with continuous process workers exposure should be evaluated with personal sampling if recommended occupational exposure levels for nanosized TiO2 and Ag are followed for risk management.

Collection of Controlled Nanosafety Data-The CoCoN-Database, a Tool to Assess Nanomaterial Hazard

Hazard assessment is the first step in nanomaterial risk assessment. The overall number of studies on the biological effects of nanomaterials or innovative materials is steadily increasing and is above 40,000. Several databases have been established to make the amount of data manageable, but these are often highly specialized or can be used only by experts. This paper describes a new database which uses an already existing data collection of about 35,000 publications. The collection from the first phase between the years 2000 and 2013 contains about 11,000 articles and this number has been reduced by specific selection criteria. The resulting publications have been evaluated for their quality regarding the toxicological content and the experimental data have been extracted. In addition to material properties, the most important value to be extracted is the no-observed-adverse-effect-level (NOAEL) for in vivo and the no-observed-effect-concentration (NOEC) for in vitro studies. The correlation of the NOAEL/NOEC values with the nanomaterial properties and the investigated endpoints has been tested in projects such as the OECD-AOP project, where the available data for inflammatory responses have been analysed. In addition, special attention was paid to titanium dioxide particles and this example is used to show with searches for in vitro and in vivo experiments on possible lung toxicity what a typical result of a database query can look like. In this review, an emerging database is described that contains valuable information for nanomaterial hazard estimation and should aid in the progress of nanosafety research.

Particles Emission from an Industrial Spray Coating Process Using Nano-Materials

Industrial spray coating processes are known to produce excellent coatings on large surfaces and are thus often used for in-line production. However, they could be one of the most critical sources of worker exposure to ultrafine particles (UFPs). A monitoring campaign at the Witek s.r.l. (Florence, Italy) was deployed to characterize the release of TiO₂ NPs doped with nitrogen (TiO₂-N) and Ag capped with hydroxyethyl cellulose (AgHEC) during automatic industrial spray-coating of polymethyl methacrylate (PMMA) and polyester. Aerosol particles were characterized inside the spray chamber at near field (NF) and far field (FF) locations using on-line and off-line instruments. Results showed that TiO₂-N suspension produced higher particle number concentrations than AgHEC in the size range 0.3–1 µm (on average 1.9 10² p/cm³ and 2.5 10¹ p/cm³, respectively) after background removing. At FF, especially at worst case scenario (4 nozzles, 800 mL/min flow rate) for TiO₂-N, the spray spikes were correlated with NF, with an observed time lag of 1 minute corresponding to a diffusion speed of 0.1 m/s. The averaged ratio between particles mass concentrations in the NF position and inside the spray chamber was 1.7% and 1.5% for TiO₂-N and for AgHEC suspensions, respectively. The released particles’ number concentration of TiO₂-N in the size particles range 0.3–1 µm was comparable for both PMMA and polyester substrates, about 1.5 and 1.6 10² p/cm³. In the size range 0.01–30 µm, the aerosol number concentration at NF for both suspensions was lower than the nano reference values (NRVs) of 16·10³ p/cm^-3.

How can we justify grouping of nanoforms for hazard assessment? Concepts and tools to quantify similarity

The risk of each nanoform (NF) of the same substance cannot be assumed to be the same, as they may vary in their physicochemical characteristics, exposure and hazard. However, neither can we justify a need for more animal testing and resources to test every NF individually. To reduce the need to test all NFs, (regulatory) information requirements may be fulfilled by grouping approaches. For such grouping to be acceptable, it is important to demonstrate similarities in physicochemical properties, toxicokinetic behaviour, and (eco)toxicological behaviour. The GRACIOUS Framework supports the grouping of NFs, by identifying suitable grouping hypotheses that describe the key similarities between different NFs. The Framework then supports the user to gather the evidence required to test these hypotheses and to subsequently assess the similarity of the NFs within the proposed group. The evidence needed to support a hypothesis is gathered by an Integrated Approach to Testing and Assessment (IATA), designed as decision trees constructed of decision nodes. Each decision node asks the questions and provides the methods needed to obtain the most relevant information. This White paper outlines existing and novel methods to assess similarity of the data generated for each decision node, either via a pairwise analysis conducted property-by-property, or by assessing multiple decision nodes simultaneously via a multidimensional analysis. For the pairwise comparison conducted property-by-property we included in this White paper: The x-fold, Bayesian and Arsinh-OWA distance algorithms performed comparably in the scoring of similarity between NF pairs. The Euclidean distance was also useful, but only with proper data transformation. The x-fold method does not standardize data, and thus produces skewed histograms, but has the advantage that it can be implemented without programming knowhow. A range of multidimensional evaluations, using for example dendrogram clustering approaches, were also investigated. Multidimensional distance metrics were demonstrated to be difficult to use in a regulatory context, but from a scientific perspective were found to offer unexpected insights into the overall similarity of very different materials. In conclusion, for regulatory purposes, a property-by-property evaluation of the data matrix is recommended to substantiate grouping, while the multidimensional approaches are considered to be tools of discovery rather than regulatory methods.

Methods, models, mechanisms and metadata: Introducing the Nanotoxicology collection at F1000Research

Nanotoxicology is a relatively new field of research concerning the study and application of nanomaterials to evaluate the potential for harmful effects in parallel with the development of applications. Nanotoxicology as a field spans materials synthesis and characterisation, assessment of fate and behaviour, exposure science, toxicology / ecotoxicology, molecular biology and toxicogenomics, epidemiology, safe and sustainable by design approaches, and chemoinformatics and nanoinformatics, thus requiring scientists to work collaboratively, often outside their core expertise area. This interdisciplinarity can lead to challenges in terms of interpretation and reporting, and calls for a platform for sharing of best-practice in nanotoxicology research. The F1000Research Nanotoxicology collection, introduced via this editorial, will provide a place to share accumulated best practice, via original research reports including no-effects studies, protocols and methods papers, software reports and living systematic reviews, which can be updated as new knowledge emerges or as the domain of applicability of the method, model or software is expanded. This editorial introduces the Nanotoxicology Collection in F1000Research. The aim of the collection is to provide an open access platform for nanotoxicology researchers, to support an improved culture of data sharing and documentation of evolving protocols, biological and computational models, software tools and datasets, that can be applied and built upon to develop predictive models and move towards in silico nanotoxicology and nanoinformatics. Submissions will be assessed for fit to the collection and subjected to the F1000Research open peer review process.

FAIRification of nanosafety data to improve applicability of (Q)SAR approaches: A case study on in vitro Comet assay genotoxicity data

(Quantitative) structure-activity relationship ([Q]SAR) methodologies are widely applied to predict the (eco)toxicological effects of chemicals, and their use is envisaged in different regulatory frameworks for filling data gaps of untested substances. However, their application to the risk assessment of nanomaterials is still limited, also due to the scarcity of large and curated experimental datasets. Despite a great amount of nanosafety data having been produced over the last decade in international collaborative initiatives, their interpretation, integration and reuse has been hampered by several obstacles, such as poorly described (meta)data, non-standard terminology, lack of harmonized reporting formats and criteria. Recently, the FAIR (Findable, Accessible, Interoperable, and Reusable) principles have been established to guide the scientific community in good data management and stewardship. The EU H2020 Gov4Nano project, together with other international projects and initiatives, is addressing the challenge of improving nanosafety data FAIRness, for maximizing their availability, understanding, exchange and ultimately their reuse. These efforts are largely supported by the creation of a common Nanosafety Data Interface, which connects a row of project-specific databases applying the eNanoMapper data model. A wide variety of experimental data relating to characterization and effects of nanomaterials are stored in the database; however, the methods, protocols and parameters driving their generation are not fully mature. This article reports the progress of an ongoing case study in the Gov4nano project on the reuse of in vitro Comet genotoxicity data, focusing on the issues and challenges encountered in their FAIRification through the eNanoMapper data model. The case study is part of an iterative process in which the FAIRification of data supports the understanding of the phenomena underlying their generation and, ultimately, improves their reusability.

Towards FAIR nanosafety data

Nanotechnology is a key enabling technology with billions of euros in global investment from public funding, which include large collaborative projects that have investigated environmental and health safety aspects of nanomaterials, but the reuse of accumulated data is clearly lagging behind. Here we summarize challenges and provide recommendations for the efficient reuse of nanosafety data, in line with the recently established FAIR (findable, accessible, interoperable and reusable) guiding principles. We describe the FAIR-aligned Nanosafety Data Interface, with an aggregated findability, accessibility and interoperability across physicochemical, bio-nano interaction, human toxicity, omics, ecotoxicological and exposure data. Overall, we illustrate a much-needed path towards standards for the optimized use of existing data, which avoids duplication of efforts, and provides a multitude of options to promote safe and sustainable nanotechnology.

An adverse outcome pathway for lung surfactant function inhibition leading to decreased lung function

Inhaled substances, such as consumer products, chemicals at the workplace, and nanoparticles, can affect the lung function in several ways. In this paper, we explore the adverse outcome pathway (AOP) that starts when inhaled substances that reach the alveoli inhibit the function of the lung surfactant, and leads to decreased lung function. Lung surfactant covers the inner surface of the alveoli, and regulates the surface tension at the air-liquid interface during breathing. The inhibition of the lung surfactant function leads to alveolar collapse because of the resulting high surface tension at the end of expiration. The collapsed alveoli can be re-opened by inspiration, but this re-opening causes shear stress on cells covering the alveoli. This can damage the alveolar-capillary membrane integrity, allowing blood components to enter the alveolar airspace. Blood components, such as albumin, can interact with the lung surfactant and further inhibit its function. The collapse of the alveoli is responsible for a decrease in the surface area available for blood oxygenation, and it reduces the volume of air that can be inhaled and exhaled. These different key events lead to decreased lung function, characterized by clinical signs of respiratory toxicity and reduced blood oxygenation. Here we present the weight of evidence that supports the AOP, and we give an overview of the methods available in vitro and in vivo to measure each key event of the pathway, and how this AOP can potentially be used in screening for inhalation toxicity.

Adverse Outcome Pathway Development for Assessment of Lung Carcinogenicity by Nanoparticles

Lung cancer, one of the most common and deadly forms of cancer, is in some cases associated with exposure to certain types of particles. With the rise of nanotechnology, there is concern that some engineered nanoparticles may be among such particles. In the absence of epidemiological evidence, assessment of nanoparticle carcinogenicity is currently performed on a time-consuming case-by-case basis, relying mainly on animal experiments. Non-animal alternatives exist, including a few validated cell-based methods accepted for regulatory risk assessment of nanoparticles. Furthermore, new approach methodologies (NAMs), focused on carcinogenic mechanisms and capable of handling the increasing numbers of nanoparticles, have been developed. However, such alternative methods are mainly applied as weight-of-evidence linked to generally required animal data, since challenges remain regarding interpretation of the results. These challenges may be more easily overcome by the novel Adverse Outcome Pathway (AOP) framework, which provides a basis for validation and uptake of alternative mechanism-focused methods in risk assessment. Here, we propose an AOP for lung cancer induced by nanosized foreign matter, anchored to a selection of 18 standardized methods and NAMs for in silico- and in vitro-based integrated assessment of lung carcinogenicity. The potential for further refinement of the AOP and its components is discussed in relation to available nanosafety knowledge and data. Overall, this perspective provides a basis for development of AOP-aligned alternative methods-based integrated testing strategies for assessment of nanoparticle-induced lung cancer.

Reliable Surface Analysis Data of Nanomaterials in Support of Risk Assessment Based on Minimum Information Requirements

The minimum information requirements needed to guarantee high-quality surface analysis data of nanomaterials are described with the aim to provide reliable and traceable information about size, shape, elemental composition and surface chemistry for risk assessment approaches. The widespread surface analysis methods electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) were considered. The complete analysis sequence from sample preparation, over measurements, to data analysis and data format for reporting and archiving is outlined. All selected methods are used in surface analysis since many years so that many aspects of the analysis (including (meta)data formats) are already standardized. As a practical analysis use case, two coated TiO2 reference nanoparticulate samples, which are available on the Joint Research Centre (JRC) repository, were selected. The added value of the complementary analysis is highlighted based on the minimum information requirements, which are well-defined for the analysis methods selected. The present paper is supposed to serve primarily as a source of understanding of the high standardization level already available for the high-quality data in surface analysis of nanomaterials as reliable input for the nanosafety community.

Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials

Toxicogenomics (TGx) approaches are increasingly applied to gain insight into the possible toxicity mechanisms of engineered nanomaterials (ENMs). Omics data can be valuable to elucidate the mechanism of action of chemicals and to develop predictive models in toxicology. While vast amounts of transcriptomics data from ENM exposures have already been accumulated, a unified, easily accessible and reusable collection of transcriptomics data for ENMs is currently lacking. In an attempt to improve the FAIRness of already existing transcriptomics data for ENMs, we curated a collection of homogenized transcriptomics data from human, mouse and rat ENM exposures in vitro and in vivo including the physicochemical characteristics of the ENMs used in each study.

Rationale and decision rules behind the ECETOC NanoApp to support registration of sets of similar nanoforms within REACH

New registration requirements for nanomaterials under REACH consider the possibility to form 'sets of similar nanoforms' for a joined human health and environmental hazard, exposure and risk assessment. We developed a tool to create and justify sets of similar nanoforms and to ensure that each of the nanoforms is sufficiently similar to all other nanoforms. The decision logic is following the ECHA guidance in a transparent and evidence-based manner. For each two nanoforms the properties under consideration are compared and corresponding thresholds for maximal differences are proposed. In tier1, similarity is assessed based on intrinsic properties that mostly correspond to those required for nanoform identification under REACH: composition, impurities/additives, size, crystallinity, shape and surface treatment. Moreover, potential differences in the agglomeration/aggregation state resulting from different production processes are considered. If nanoforms were not sufficiently similar based on tier1 criteria, additional data from functional assays are required in tier2. In rare cases, additional short-term in vivo rodent data could be required in a third tier. Data required by tier 2 are triggered by the intrinsic properties in the first tier that did not match the similarity criteria. Most often this will be data on dissolution and surface reactivity followed by in vitro toxicity, dispersion stability, dustiness. Out of several nanoforms given by the user, the tool concludes which nanoforms could be justified to be in the same set and which nanoforms are outside. It defines the boundaries of sets of similar nanoforms and generates a justification for the REACH registration.

Gemini Surfactant as a Template Agent for the Synthesis of More Eco-Friendly Silica Nanocapsules

Silica mesoporous nanocapsules are a class of “smart” engineered nanomaterials (ENMs) applied in several fields. Recent studies have highlighted that they can exert deleterious effects into marine organisms, attributed to the use of the toxic cationic surfactant N-hexadecyl-N,N,N-trimethylammonium bromide (CTAB) during the synthesis of ENMs. The present study reports the successful synthesis and characterization of novel gemini surfactant-based silica nanocapsules. The gemini surfactant 1,4-bis-[N-(1-dodecyl)-N,N-dimethylammoniummethyl]benzene dibromide (QSB2-12) was chosen as a more environmentally-friendly replacement of CTAB. Nanocapsules were characterized by scanning electron microscopy (SEM), Fourier-transformed infrared spectroscopy (FTIR), dynamic light scattering (DLS), thermogravimetric analysis (TGA) and N2 adsorption-desorption isotherms. Short-term exposure effects of new ENMs were evaluated in four marine species (Nannochloropsis gaditana, Tetraselmis chuii and Phaeodactylum tricornutum) and the microcrustacean (Artemia salina). The replacement of the commercial cationic surfactant by the gemini surfactant does not change the structure nor the environmental behaviour in seawater of the newly synthesised silica nanocontainers. Additionally, it is demonstrated that using gemini surfactants can reduce the toxicity of novel silica nanocapsules towards the tested marine species. As a result, environmentally-friendly ENMs can be obtained based on a safe-by-design approach, thereby fitting the concept of Green Chemistry.

Nanocharacterization, Materials Modeling, and Research Integrity as Enablers of Sound Risk Assessment: Designing Responsible Nanotechnology

Nanotechnology, as a mature enabling technology, has great potential to boost societal welfare. However, nanomaterials' current and foreseen applications raise serious concerns about their impact on human health and the environment. These concerns emerge because a reliable risk assessment in nanotechnology is yet to be achieved. The reasons for such a shortcoming are the inherent difficulties in characterizing nanomaterials properties. The interaction of characterization with modeling is an open issue and, due to overarching concerns about the reliability of research results, usually framed within the context of research integrity. This essay explores the connection between these different, but deeply intertwined concerns and the way they enable the production of responsible nanotechnology, i.e., nanotechnology devoted to societal welfare.

Recent insights on indirect mechanisms in developmental toxicity of nanomaterials

BACKGROUND

Epidemiological and animal studies provide compelling indications that environmental and engineered nanomaterials (NMs) pose a risk for pregnancy, fetal development and offspring health later in life. Understanding the origin and mechanisms underlying NM-induced developmental toxicity will be a cornerstone in the protection of sensitive populations and the design of safe and sustainable nanotechnology applications.

MAIN BODY

Direct toxicity originating from NMs crossing the placental barrier is frequently assumed to be the key pathway in developmental toxicity. However, placental transfer of particles is often highly limited, and evidence is growing that NMs can also indirectly interfere with fetal development. Here, we outline current knowledge on potential indirect mechanisms in developmental toxicity of NMs.

SHORT CONCLUSION

Until now, research on developmental toxicity has mainly focused on the biodistribution and placental translocation of NMs to the fetus to delineate underlying processes. Systematic research addressing NM impact on maternal and placental tissues as potential contributors to mechanistic pathways in developmental toxicity is only slowly gathering momentum. So far, maternal and placental oxidative stress and inflammation, activation of placental toll-like receptors (TLRs), impairment of placental growth and secretion of placental hormones, and vascular factors have been suggested to mediate indirect developmental toxicity of NMs. Therefore, NM effects on maternal and placental tissue function ought to be comprehensively evaluated in addition to placental transfer in the design of future studies of developmental toxicity and risk assessment of NM exposure during pregnancy.

Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment

Transcriptomics data are relevant to address a number of challenges in Toxicogenomics (TGx). After careful planning of exposure conditions and data preprocessing, the TGx data can be used in predictive toxicology, where more advanced modelling techniques are applied. The large volume of molecular profiles produced by omics-based technologies allows the development and application of artificial intelligence (AI) methods in TGx. Indeed, the publicly available omics datasets are constantly increasing together with a plethora of different methods that are made available to facilitate their analysis, interpretation and the generation of accurate and stable predictive models. In this review, we present the state-of-the-art of data modelling applied to transcriptomics data in TGx. We show how the benchmark dose (BMD) analysis can be applied to TGx data. We review read across and adverse outcome pathways (AOP) modelling methodologies. We discuss how network-based approaches can be successfully employed to clarify the mechanism of action (MOA) or specific biomarkers of exposure. We also describe the main AI methodologies applied to TGx data to create predictive classification and regression models and we address current challenges. Finally, we present a short description of deep learning (DL) and data integration methodologies applied in these contexts. Modelling of TGx data represents a valuable tool for more accurate chemical safety assessment. This review is the third part of a three-article series on Transcriptomics in Toxicogenomics.

NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment

Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals. Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment (IATA) for human and environmental risk assessment, all within the NanoSolveIT cloud-platform. These established and well-characterized NM libraries (e.g. NanoMILE, NanoSolutions, NANoREG, NanoFASE, caLIBRAte, NanoTEST and the Nanomaterial Registry (>2000 NMs)) contain physicochemical characterization data as well as data for several relevant biological endpoints, assessed in part using harmonized Organisation for Economic Co-operation and Development (OECD) methods and test guidelines. Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse effects and to predict the effects of other NMs for which less data is available. The project specifically addresses the needs of regulatory agencies and industry to effectively and rapidly evaluate the exposure, NM hazard and risk from nanomaterials and nano-enabled products, enabling implementation of computational 'safe-by-design' approaches to facilitate NM commercialization.