A weight of evidence approach for hazard screening of engineered nanomaterials

Frameworks for screening and risk management of chemicals and advanced materials: A critical review

Despite the evolution over the last half century of regulatory programs and frameworks developed for the evaluation of safety and management of risks associated with chemicals and materials, new and emerging contaminant issues continue to be identified. These recurring issues suggest a need for review and reflection on current approaches and strategies for ensuring the safety of chemicals and materials. Twelve existing frameworks relating to the evaluation and management of chemical or material risk were reviewed to identify potential process improvements for facilitating early identification of potentially problematic substances and better inform risk management strategies (e.g., prohibition, restricted use, or selection of safer alternatives). The frameworks were selected to represent a broad spectrum of regional, national, and international authorities and purposes, including preproduction evaluation of new substances, classification and hazard communication, identification of persistent pollutants, and identification of safer alternatives. Elements common to the frameworks were identified, as well as features unique to select frameworks. A comparative evaluation was performed, and potential new strategies and approaches were identified to inform process improvement recommendations. These recommendations include requiring validated analytical procedures to enable measurement in environmental media, improved data transparency and accessibility, flexibility to incorporate advances into the state of the practice (e.g., new approach methodologies and high-throughput assessment tools), and incorporation of monitoring and adaptive management strategies to enable more timely intervention. Process improvement recommendations are discussed and summarized in a conceptual risk management framework. Integr Environ Assess Manag 2023;19:1192-1206. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Potential adverse outcome pathways with hazard identification of organophosphate esters

Data-driven analysis and pathway-based approaches contribute to reasonable arrangements of limited resources and laboratory tests for continuously emerging commercial chemicals, which provides opportunities to save time and effort for toxicity research. With the widespread usage of organophosphate esters (OPEs) on a global scale, the concentrations generally reached up to micromolar range in environmental media and even in organisms. However, potential adverse effects and toxicity pathways of OPEs have not been systematically assessed. Therefore, it is necessary to review the current situation, formulate the future research priorities, and characterize toxicity mechanisms via data-driven analysis. Results showed that the early toxicity studies focused on neurotoxicity, cytotoxicity, and metabolic disorders. Then the main focus shifted to the mechanisms of cardiotoxicity, endocrine disruption, hepatocytes, reproductive and developmental toxicity to vulnerable sub-populations, such as infants and embryos, affected by OPEs. In addition, several novel OPEs have been emerging, such as bis(2-ethylhexyl)-phenyl phosphate (HDEHP) and oxidation derivatives (OPAsO) generated from organophosphite antioxidants (OPAs), leading to multiple potential ecological and human health risks (neurotoxicity, hepatotoxicity, developmental toxicity, etc.). Notably, in-depth statistical analysis was promising in encapsulating toxicological information to develop adverse outcome pathways (AOPs) frameworks. Subsequently, network-centric analysis and quantitative weight-of-evidence (QWOE) approaches were utilized to construct and evaluate the putative AOPs frameworks of OPEs, showing the moderate confidences of the developed AOPs. In addition, frameworks demonstrated that several events, such as nuclear receptor activation, reactive oxygen species (ROS) production, oxidative stress, and DNA damage, were involved in multiple different adverse outcome (AO), and these AOs had certain degree of connectivity. This study brought new insights into facilitating the complement of AOP efficiently, as well as establishing toxicity pathways framework to inform risk assessment of emerging OPEs.

Developing Integrated Approaches for Testing and Assessment (IATAs) in order to support nanomaterial safety

Due to the unique characteristics of nanomaterials (NM) there has been an increase in their use in nanomedicines and innovative medical devices (MD). Although large numbers of NMs have now been developed, comprehensive safety investigations are still lacking. Current gaps in understanding the potential mechanisms of NM-induced toxicity can make it challenging to determine the safety testing necessary to support inclusion of NMs in MD applications. This article provides guidance for implementation of pre-clinical tailored safety assessment strategies with the aim to increase the translation of NMs from bench development to clinical use. Integrated Approaches to Testing and Assessment (IATAs) are a key tool in developing these strategies. IATAs follow an iterative approach to answer a defined question in a specific regulatory context to guide the gathering of relevant information for safety assessment, including existing experimental data, integrated with in silico model predictions where available and appropriate, and/or experimental procedures and protocols for generating new data to fill gaps. This allows NM developers to work toward current guidelines and regulations, while taking NM specific considerations into account. Here, an example IATA for NMs with potential for direct blood contact was developed for the assessment of haemocompatibility. This example IATA brings together the current guidelines for NM safety assessment within a framework that can be used to guide information and data gathering for the safety assessment of intravenously injected NMs. Additionally, the decision framework underpinning this IATA has the potential to be adapted to other testing needs and regulatory contexts.

A methodology for the automatic evaluation of data quality and completeness of nanomaterials for risk assessment purposes

This manuscript proposes a methodology to assess the completeness and quality of physicochemical and hazard datasets for risk assessment purposes. The approach is also specifically applicable to similarity assessment as a basis for grouping of (nanoforms of) chemical substances as well as for classification of the substances according to the Classification, Labeling and Packaging regulation. The unique goal of this approach is to assess data quality in such a way that all the steps are automatized, thus reducing reliance on expert judgment. The analysis starts from available (meta)data as provided in the data entry templates developed by the NanoSafety community and used for import into the eNanoMapper database. The methodology is implemented in the templates as a traffic light system-the providers of the data can see in real time the completeness scores calculated by the system for their datasets in green, yellow, or red. This is an interactive feedback feature that is intended to provide an incentive for anyone inserting data into the database to deliver more complete and higher quality datasets. The users of the data can also see this information both in the data entry templates and on the database interface, which enables them to select better datasets for their assessments. The proposed methodology has been partially implemented in the eNanoMapper database and in a Weight of Evidence approach for the regulatory classification of nanomaterials. It was fully implemented in a publicly available online R tool.

A Weight of Evidence approach to classify nanomaterials according to the EU Classification, Labelling and Packaging Regulation criteria

In the context of the European Union (EU) Horizon 2020 GRACIOUS project (Grouping, Read-Across, Characterisation and classification framework for regulatory risk assessment of manufactured nanomaterials and Safer design of nano-enabled products), we proposed a quantitative Weight of Evidence (WoE) approach for hazard classification of nanomaterials (NMs). This approach is based on the requirements of the European Regulation on Classification, Labelling and Packaging of Substances and Mixtures (the CLP regulation), which implements the United Nations' Globally Harmonized System of Classification and Labelling of Chemicals (UN GHS) in the European Union. The goal of this WoE methodology is to facilitate classification of NMs according to CLP criteria, following the decision trees defined in ECHA's CLP regulatory guidance. In the WoE, results from heterogeneous studies are weighted according to data quality and completeness criteria, integrated, and then evaluated by expert judgment to obtain a hazard classification, resulting in a coherent and justifiable methodology. Moreover, the probabilistic nature of the proposed approach enables highlighting the uncertainty in the analysis. The proposed methodology involves the following stages: (1) collection of data for different NMs related to the endpoint of interest: each study related to each NM is referred as a Line of Evidence (LoE); (2) computation of weighted scores for each LoE: each LoE is weighted by a score calculated based on data quality and completeness criteria defined in the GRACIOUS project; (3) comparison and integration of the weighed LoEs for each NM: A Monte Carlo resampling approach is adopted to quantitatively and probabilistically integrate the weighted evidence; and (4) assignment of each NM to a hazard class: according to the results, each NM is assigned to one of the classes defined by the CLP regulation. Furthermore, to facilitate the integration and the classification of the weighted LoEs, an online R tool was developed. Finally, the approach was tested against an endpoint relevant to CLP (Aquatic Toxicity) using data retrieved from the eNanoMapper database, results obtained were consistent to results in REACH registration dossiers and in recent literature.

Integrative approach in a safe by design context combining risk, life cycle and socio-economic assessment for safer and sustainable nanomaterials

Moving towards safe and sustainable innovations is an international policy ambition. In the on-hand manuscript, a concept combining safe by design and sustainability was implemented through the integration of human and environmental risk assessment, life cycle assessment as well as an assessment of the economic viability. The result is a nested and iterative process in form of a decision tree that integrates these three elements in order to achieve sustainable, safe and competitive materials, products or services. This approach, embedded into the stage-gate-model for safe by design, allows to reduce the uncertainty related to the assessment of risks and impacts by improving the quality of the data collected along each stage. In the second part of the manuscript, the application is shown for a case study dealing with the application of nanoparticles for Li-Ion batteries. One of the general conclusions out of this case study is that data gaps are a key aspect in view of the reliability of the results.

Application of Bayesian networks in determining nanoparticle-induced cellular outcomes using transcriptomics

Inroads have been made in our understanding of the risks posed to human health and the environment by nanoparticles (NPs) but this area requires continuous research and monitoring. Machine learning techniques have been applied to nanotoxicology with very encouraging results. This study deals with bridging physicochemical properties of NPs, experimental exposure conditions and in vitro characteristics with biological effects of NPs on a molecular cellular level from transcriptomics studies. The bridging is done by developing and implementing Bayesian Networks (BNs) with or without data preprocessing. The BN structures are derived either automatically or methodologically and compared. Early stage nanotoxicity measurements represent a challenge, not least when attempting to predict adverse outcomes and modeling is critical to understanding the biological effects of exposure to NPs. The preprocessed data-driven BN showed improved performance over automatically structured BN and the BN with unprocessed datasets. The prestructured BN captures inter relationships between NP properties, exposure condition and in vitro characteristics and links those with cellular effects based on statistic correlation findings. Information gain analysis showed that exposure dose, NP and cell line variables were the most influential attributes in predicting the biological effects. The BN methodology proposed in this study successfully predicts a number of toxicologically relevant cellular disrupted biological processes such as cell cycle and proliferation pathways, cell adhesion and extracellular matrix responses, DNA damage and repair mechanisms etc., with a success rate >80%. The model validation from independent data shows a robust and promising methodology for incorporating transcriptomics outcomes in a hazard and, by extension, risk assessment modeling framework by predicting affected cellular functions from experimental conditions.

Risk Governance of Nanomaterials: Review of Criteria and Tools for Risk Communication, Evaluation, and Mitigation

Nanotechnologies have been increasingly used in industrial applications and consumer products across several sectors, including construction, transportation, energy, and healthcare. The widespread application of these technologies has raised concerns regarding their environmental, health, societal, and economic impacts. This has led to the investment of enormous resources in Europe and beyond into the development of tools to facilitate the risk assessment and management of nanomaterials, and to inform more robust risk governance process. In this context, several risk governance frameworks have been developed. In our study, we present and review those, and identify a set of criteria and tools for risk evaluation, mitigation, and communication, the implementation of which can inform better risk management decision-making by various stakeholders from e.g., industry, regulators, and the civil society. Based on our analysis, we recommend specific methods from decision science and information technologies that can improve the existing risk governance tools so that they can communicate, evaluate, and mitigate risks more transparently, taking stakeholder perspectives and expert opinion into account, and considering all relevant criteria in establishing the risk-benefit balance of these emerging technologies to enable more robust decisions about the governance of their risks.

The Essential Elements of a Risk Governance Framework for Current and Future Nanotechnologies

Societies worldwide are investing considerable resources into the safe development and use of nanomaterials. Although each of these protective efforts is crucial for governing the risks of nanomaterials, they are insufficient in isolation. What is missing is a more integrative governance approach that goes beyond legislation. Development of this approach must be evidence based and involve key stakeholders to ensure acceptance by end users. The challenge is to develop a framework that coordinates the variety of actors involved in nanotechnology and civil society to facilitate consideration of the complex issues that occur in this rapidly evolving research and development area. Here, we propose three sets of essential elements required to generate an effective risk governance framework for nanomaterials. (1) Advanced tools to facilitate risk-based decision making, including an assessment of the needs of users regarding risk assessment, mitigation, and transfer. (2) An integrated model of predicted human behavior and decision making concerning nanomaterial risks. (3) Legal and other (nano-specific and general) regulatory requirements to ensure compliance and to stimulate proactive approaches to safety. The implementation of such an approach should facilitate and motivate good practice for the various stakeholders to allow the safe and sustainable future development of nanotechnology.

Weight of Evidence for Hazard Identification: A Critical Review of the Literature

BACKGROUND

Transparency when documenting and assessing weight of evidence (WOE) has been an area of increasing focus for national and international health agencies.

OBJECTIVE

The objective of this work was to conduct a critical review of WOE analysis methods as a basis for developing a practical framework for considering and assessing WOE in hazard identification in areas of application at the French Agency for Food, Environmental and Occupational Health and Safety (ANSES).

METHODS

Based on a review of the literature and directed requests to 63 international and national agencies, 116 relevant articles and guidance documents were selected. The WOE approaches were assessed based on three aspects: the extent of their prescriptive nature, their purpose-specific relevance, and their ease of implementation.

RESULTS

Twenty-four approaches meeting the specified criteria were identified from selected reviewed documents. Most approaches satisfied one or two of the assessed considerations, but not all three. The approaches were grouped within a practical framework comprising the following four stages: (1) planning the assessment, including scoping, formulating the question, and developing the assessment method; (2) establishing lines of evidence (LOEs), including identifying and selecting studies, assessing their quality, and integrating with studies of similar type; (3) integrating the LOEs to evaluate WOE; and (4) presenting conclusions.

DISCUSSION

Based on the review, considerations for selecting methods for a wide range of applications are proposed. Priority areas for further development are identified. https://doi.org/10.1289/EHP3067.

Genotoxicity induced by metal oxide nanoparticles: a weight of evidence study and effect of particle surface and electronic properties

The genetic toxicology of nanomaterials is a crucial toxicology issue and one of the least investigated topics. Substantially, the genotoxicity of metal oxide nanomaterials' data is resulting from in vitro comet assay. Current contributions to the genotoxicity data assessed by the comet assay provide a case-by-case evaluation of different types of metal oxides. The existing inconsistency in the literature regarding the genotoxicity testing data requires intelligent assessment strategies, such as weight of evidence evaluation. Two main tasks were performed in the present study. First, the genotoxicity data from comet assay for 16 noncoated metal oxide nanomaterials with different core composition were collected. An evaluation criterion was applied to establish which of these individual lines of evidence were of sufficient quality and what weight could have been given to them in inferring genotoxic results. The collected data were surveyed on (1) minimum necessary characterization points for nanomaterials and (2) principals of correct comet assay testing for nanomaterials. Second, in this study the genotoxicity effect of metal oxide nanomaterials was investigated by quantitative nanostructure-activity relationship approach. A set of quantum-chemical descriptors was developed for all investigated metal oxide nanomaterials. A classification model based on decision tree was developed for the investigated dataset. Thus, three descriptors were identified as the most responsible factors for genotoxicity effect: heat of formation, molecular weight, and surface area of the oxide cluster based on the conductor-like screening model. Conclusively, the proposed genotoxicity assessment strategy is useful to prioritize the study of the nanomaterials for further risk assessment evaluations.

Risk Assessment and Risk Minimization in Nanomedicine: A Need for Predictive, Alternative, and 3Rs Strategies

The use of nanomaterials in medicine has grown very rapidly, leading to a concern about possible health risks. Surely, the application of nanotechnology in medicine has many significant potentialities as it can improve human health in at least three different ways: by contributing to early disease diagnosis, improved treatment outcomes and containment of health care costs. However, toxicology or safety assessment is an integral part of any new medical technology and the nanotechnologies are no exception. The principle aim of nanosafety studies in this frame is to enable safer design of nanomedicines. The most urgent need is finding and validating novel approaches able to extrapolate acute in vitro results for the prediction of chronic in vivo effects and to this purpose a few European initiatives have been launched. While a "safe-by-design" process may be considered as utopic, "safer-by-design" is probably a reachable goal in the field of nanomedicine.

Hazard Screening Methods for Nanomaterials: A Comparative Study

Hazard identification is the key step in risk assessment and management of manufactured nanomaterials (NM). However, the rapid commercialisation of nano-enabled products continues to out-pace the development of a prudent risk management mechanism that is widely accepted by the scientific community and enforced by regulators. However, a growing body of academic literature is developing promising quantitative methods. Two approaches have gained significant currency. Bayesian networks (BN) are a probabilistic, machine learning approach while the weight of evidence (WoE) statistical framework is based on expert elicitation. This comparative study investigates the efficacy of quantitative WoE and Bayesian methodologies in ranking the potential hazard of metal and metal-oxide NMs—TiO₂, Ag, and ZnO. This research finds that hazard ranking is consistent for both risk assessment approaches. The BN and WoE models both utilize physico-chemical, toxicological, and study type data to infer the hazard potential. The BN exhibits more stability when the models are perturbed with new data. The BN has the significant advantage of self-learning with new data; however, this assumes all input data is equally valid. This research finds that a combination of WoE that would rank input data along with the BN is the optimal hazard assessment framework.

Environmental Risk Assessment Strategy for Nanomaterials

An Environmental Risk Assessment (ERA) for nanomaterials (NMs) is outlined in this paper. Contrary to other recent papers on the subject, the main data requirements, models and advancement within each of the four risk assessment domains are described, i.e., in the: (i) materials, (ii) release, fate and exposure, (iii) hazard and (iv) risk characterisation domains. The material, which is obviously the foundation for any risk assessment, should be described according to the legislatively required characterisation data. Characterisation data will also be used at various levels within the ERA, e.g., exposure modelling. The release, fate and exposure data and models cover the input for environmental distribution models in order to identify the potential (PES) and relevant exposure scenarios (RES) and, subsequently, the possible release routes, both with regard to which compartment(s) NMs are distributed in line with the factors determining the fate within environmental compartment. The initial outcome in the risk characterisation will be a generic Predicted Environmental Concentration (PEC), but a refined PEC can be obtained by applying specific exposure models for relevant media. The hazard information covers a variety of representative, relevant and reliable organisms and/or functions, relevant for the RES and enabling a hazard characterisation. The initial outcome will be hazard characterisation in test systems allowing estimating a Predicted No-Effect concentration (PNEC), either based on uncertainty factors or on a NM adapted version of the Species Sensitivity Distributions approach. The risk characterisation will either be based on a deterministic risk ratio approach (i.e., PEC/PNEC) or an overlay of probability distributions, i.e., exposure and hazard distributions, using the nano relevant models.

A quantitative framework to group nanoscale and microscale particles by hazard potency to derive occupational exposure limits: Proof of concept evaluation

The large and rapidly growing number of engineered nanomaterials (ENMs) presents a challenge to assessing the potential occupational health risks. An initial database of 25 rodent studies including 1929 animals across various experimental designs and material types was constructed to identify materials that are similar with respect to their potency in eliciting neutrophilic pulmonary inflammation, a response relevant to workers. Doses were normalized across rodent species, strain, and sex as the estimated deposited particle mass dose per gram of lung. Doses associated with specific measures of pulmonary inflammation were estimated by modeling the continuous dose-response relationships using benchmark dose modeling. Hierarchical clustering was used to identify similar materials. The 18 nanoscale and microscale particles were classified into four potency groups, which varied by factors of approximately two to 100. Benchmark particles microscale TiO2 and crystalline silica were in the lowest and highest potency groups, respectively. Random forest methods were used to identify the important physicochemical predictors of pulmonary toxicity, and group assignments were correctly predicted for five of six new ENMs. Proof-of-concept was demonstrated for this framework. More comprehensive data are needed for further development and validation for use in deriving categorical occupational exposure limits.

A model for screening and prioritizing consumer nanoproduct risks: A case study from South Africa

The potential risks of the increasing variety and volume of engineered nanomaterials (ENMs) entering into the ecosystem remain poorly quantified. In recent years, information essential to evaluate the ecological risks of ENMs has increased. However, the data are highly fragmented, limited, or severely lacking. This limits the usefulness of the information to support holistic screening and prioritization of potentially harmful ENMs. To screen and prioritize ENMs risks, we adopted a two-phased approach. First, a holistic framework model was developed to integrate a diverse set of factors aimed to assess the potential hazard, exposure, and in turn, risk to the ecosystem of ENMs from a given consumer nanoproduct. Secondly, using published literature we created a database of consumer nanoproduct categories, and types based on embedded ENMs type. The database consisted of eight consumer product categories, eleven different types of ENMs, and twenty-three nanoproduct types. The model results indicates the largest quantities of ENMs were released from sunscreens, textiles, cosmetics and paints with dominant ENMs quantities in descending order (based on quantity) as nTiO₂>nZnO>nSiO₂>nAg, and nFe₂O₃. In addition, according to the results from this study, nAg from washing machine were found to likely the highest risk to the environment. Overall, our model-derived results based on the case study illustrated: (i) the holistic framework's ability to screen, prioritize, rank, and compare ENMs potential exposure and risks among different nanoproducts categories and types, (ii) the derived risk estimations could support nanowastes classification with likelihood of non-uniformity of nanowastes classes even from the same nanoproduct category (e.g. cosmetics), and (iii) the lack of a mass-based criteria specific for EMNs impedes realistic exposure and risk evaluation in the ecological systems.

A decision analysis framework for estimating the potential hazards for drinking water resources of chemicals used in hydraulic fracturing fluids

Despite growing concerns over the potential for hydraulic fracturing to impact drinking water resources, there are limited data available to identify chemicals used in hydraulic fracturing fluids that may pose public health concerns. In an effort to explore these potential hazards, a multi-criteria decision analysis (MCDA) framework was employed to analyze and rank selected subsets of these chemicals by integrating data on toxicity, frequency of use, and physicochemical properties that describe transport in water. Data used in this analysis were obtained from publicly available databases compiled by the United States Environmental Protection Agency (EPA) as part of a larger study on the potential impacts of hydraulic fracturing on drinking water. Starting with nationwide hydraulic fracturing chemical usage data from EPA's analysis of the FracFocus Chemical Disclosure Registry 1.0, MCDAs were performed on chemicals that had either noncancer toxicity values (n=37) or cancer-specific toxicity values (n=10). The noncancer MCDA was then repeated for subsets of chemicals reported in three representative states (Texas, n=31; Pennsylvania, n=18; and North Dakota, n=20). Within each MCDA, chemicals received scores based on relative toxicity, relative frequency of use, and physicochemical properties (mobility in water, volatility, persistence). Results show a relative ranking of these chemicals based on hazard potential, and provide preliminary insight into chemicals that may be more likely than others to impact drinking water resources. Comparison of nationwide versus state-specific analyses indicates regional differences in the chemicals that may be of more concern to drinking water resources, although many chemicals were commonly used and received similar overall hazard rankings. Several chemicals highlighted by these MCDAs have been reported in groundwater near areas of hydraulic fracturing activity. This approach is intended as a preliminary analysis, and represents one possible method for integrating data to explore potential public health impacts.

The changing face of nanomaterials: Risk assessment challenges along the value chain

Risk assessment (RA) of manufactured nanomaterials (MNM) is essential for regulatory purposes and risk management activities. Similar to RA of "classical" chemicals, MNM RA requires knowledge about exposure as well as of hazard potential and dose response relationships. What makes MNM RA especially challenging is the multitude of materials (which is expected to increase substantially in the future), the complexity of MNM value chains and life cycles, the accompanying possible changes in material properties over time and in contact with various environmental and organismal milieus, and the difficulties to obtain proper exposure data and to consider the proper dose metric. This article discusses these challenges and also critically overviews the current state of the art regarding MNM RA approaches.

A Tractable Method for Measuring Nanomaterial Risk Using Bayesian Networks

While control banding has been identified as a suitable framework for the evaluation and the determination of potential human health risks associated with exposure to nanomaterials (NMs), the approach currently lacks any implementation that enjoys widespread support. Large inconsistencies in characterisation data, toxicological measurements and exposure scenarios make it difficult to map and compare the risk associated with NMs based on physicochemical data, concentration and exposure route. Here we demonstrate the use of Bayesian networks as a reliable tool for NM risk estimation. This tool is tractable, accessible and scalable. Most importantly, it captures a broad span of data types, from complete, high quality data sets through to data sets with missing data and/or values with a relatively high spread of probability distribution. The tool is able to learn iteratively in order to further refine forecasts as the quality of data available improves. We demonstrate how this risk measurement approach works on NMs with varying degrees of risk potential, namely, carbon nanotubes, silver and titanium dioxide. The results afford even non-experts an accurate picture of the occupational risk probabilities associated with these NMs and, in doing so, demonstrated how NM risk can be evaluated into a tractable, quantitative risk comparator.

Concern-driven integrated approaches for the grouping, testing and assessment of nanomaterials

NM's potential to induce adverse effects in humans or the environment is being addressed in numerous research projects, and methods and tools for NM hazard identification and risk assessment are advancing. This article describes how integrated approaches for the testing and assessment of NMs can ensure the safety of nanomaterials, while adhering to the 3Rs principle.

Alternative Testing Strategies for Nanomaterials: State of the Science and Considerations for Risk Analysis

The rapid growth of the nanotechnology industry has warranted equal progress in the nanotoxicology and risk assessment fields. In vivo models have traditionally been used to determine human and environmental risk for chemicals; however, the use of these tests has limitations, and there are global appeals to develop reliable alternatives to animal testing. Many have investigated the use of alternative (nonanimal) testing methods and strategies have quickly developed and resulted in the generation of large toxicological data sets for numerous nanomaterials (NMs). Due to the novel physicochemical properties of NMs that are related to surface characteristics, the approach toward toxicity test development has distinct considerations from traditional chemicals, bringing new requirements for adapting these approaches for NMs. The methodical development of strategies that combine multiple alternative tests can be useful for predictive NM risk assessment and help screening-level decision making. This article provides an overview of the main developments in alternative methods and strategies for reducing uncertainty in NM risk assessment, including advantages and disadvantages of in vitro, ex vivo, and in silico methods, and examples of existing comprehensive strategies. In addition, knowledge gaps are identified toward improvements for experimental and strategy design, specifically highlighting the need to represent realistic exposure scenarios and to consider NM-specific concerns such as characterization, assay interferences, and standardization. Overall, this article aims to improve the reliability and utility of alternative testing methods and strategies for risk assessment of manufactured NMs.

Considerations of Environmentally Relevant Test Conditions for Improved Evaluation of Ecological Hazards of Engineered Nanomaterials

Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations-where observing outcomes is difficult-versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test end points, duration, and study conditions-including ENM test concentrations-that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.

An interlaboratory comparison of nanosilver characterisation and hazard identification: Harmonising techniques for high quality data

Within the FP7 EU project NanoValid a consortium of six partners jointly investigated the hazard of silver nanoparticles (AgNPs) paying special attention to methodical aspects that are important for providing high-quality ecotoxicity data. Laboratories were supplied with the same original stock dispersion of AgNPs. All partners applied a harmonised procedure for storage and preparation of toxicity test suspensions. Altogether ten different toxicity assays with a range of environmentally relevant test species from different trophic levels were conducted in parallel to AgNP characterisation in the respective test media. The paper presents a comprehensive dataset of toxicity values and AgNP characteristics like hydrodynamic sizes of AgNP agglomerates and the share (%) of Ag(+)-species (the concentration of Ag(+)-species in relation to the total measured concentration of Ag). The studied AgNP preparation (20.4±6.8 nm primary size, mean total Ag concentration 41.14 mg/L, 46-68% of soluble Ag(+)-species in stock, 123.8±12.2 nm mean z-average value in dH2O) showed extreme toxicity to crustaceans Daphnia magna, algae Pseudokirchneriella subcapitata and zebrafish Danio rerio embryos (EC50<0.01 mg total Ag/L), was very toxic in the in vitro assay with rainbow trout Oncorhynchus mykiss gut cells (EC50: 0.01-1 mg total Ag/L); toxic to bacteria Vibrio fischeri, protozoa Tetrahymena thermophila (EC50: 1-10 mg total Ag/L) and harmful to marine crustaceans Artemia franciscana (EC50: 10-100 mg total Ag/L). Along with AgNPs, also the toxicity of AgNO3 was analyzed. The toxicity data revealed the same hazard ranking for AgNPs and AgNO3 (i.e. the EC50 values were in the same order of magnitude) proving the importance of soluble Ag(+)-species analysis for predicting the hazard of AgNPs. The study clearly points to the need for harmonised procedures for the characterisation of NMs. Harmonised procedures should consider: (i) measuring the AgNP properties like hydrodynamic size and metal ions species in each toxicity test medium at a range of concentrations, and (ii) including soluble metal salt control both in toxicity testing as well as in Ag(+)-species measurements. The present study is among the first nanomaterial interlaboratory comparison studies with the aim to improve the hazard identification testing protocols.

Engineered nanoparticles: Revisiting safety concerns in light of ethno medicine

The nanoparticles are a miracle invention of the century that has opened novel avenues of applications in various fields. The safety aspect of exposure to nanoparticles for humans, plants, animals, soil micro-flora, and ecosystem at large has been questioned. The safety concern can be addressed by laboratory studies to assess the actual risk and recommend exposure limits and related regulation. There is also a suggestion for considering the nanoparticle form of conventional compounds as a new chemical and subject it to safety assessment in line with the chemical regulatory agencies. In the light of the current scenario of popularity and safety concerns regarding nanoparticles, the use of ancient metal based forms like, Bhasma is revisited in the present article. The current approach of green synthesis of nanoparticles is compared with the Ayurveda Rasayana Shastra guidelines of Bhasma preparation and modern preparation of engineered nanoparticles. Since the benefits of nanotechnology are undeniable, and safety concerns are also not ungrounded, there is a pressing need to revisit the ways nanoparticles are manufactured, and to carry out safety assessment by the techniques specially adapted for this novel compound.

From "weight of evidence" to quantitative data integration using multicriteria decision analysis and Bayesian methods

“Weighing” available evidence in the process of decision-making is unavoidable, yet it is one step that routinely raises suspicions: what evidence should be used, how much does it weigh, and whose thumb may be tipping the scales? This commentary aims to evaluate the current state and future roles of various types of evidence for hazard assessment as it applies to environmental health. In its recent evaluation of the US Environmental Protection Agency’s Integrated Risk Information System assessment process, the National Research Council committee singled out the term “weight of evidence” (WoE) for critique, deeming the process too vague and detractive to the practice of evaluating human health risks of chemicals. Moving the methodology away from qualitative, vague and controversial methods towards generalizable, quantitative and transparent methods for appropriately managing diverse lines of evidence is paramount for both regulatory and public acceptance of the hazard assessments. The choice of terminology notwithstanding, a number of recent Bayesian WoE-based methods, the emergence of multi criteria decision analysis for WoE applications, as well as the general principles behind the foundational concepts of WoE, show promise in how to move forward and regain trust in the data integration step of the assessments. We offer our thoughts on the current state of WoE as a whole and while we acknowledge that many WoE applications have been largely qualitative and subjective in nature, we see this as an opportunity to turn WoE towards a quantitative direction that includes Bayesian and multi criteria decision analysis.

A system-of-systems approach as a broad and integrated paradigm for sustainable engineered nanomaterials

There is an urgent need for a trans-disciplinary approach for the collective evaluation of engineered nanomaterial (ENM) benefits and risks. Currently, research studies are mostly focused on examining effects at individual endpoints with emphasis on ENM risk effects. Less research work is pursuing the integration needed to advance the science of sustainable ENMs. Therefore, the primary objective of this article is to discuss the system-of-systems (SoS) approach as a broad and integrated paradigm to examine ENM benefits and risks to society, environment, and economy (SEE) within a sustainability context. The aims are focused on: (a) current approaches in the scientific literature and the need for a broad and integrated approach, (b) documentation of ENM SoS in terms of architecture and governing rules and practices within sustainability context, and (c) implementation plan for the road ahead. In essence, the SoS architecture is a communication vehicle offering the opportunity to track benefits and risks in an integrated fashion so as to understand the implications and make decisions about advancing the science of sustainable ENMs. In support of the SoS architecture, we propose using an analytic-based decision support system consisting of a knowledge base and analytic engine along the benefit and risk informatics routes in the SEE system to build sound decisions on what constitutes sustainable and unsustainable ENMs in spite of the existing uncertainties and knowledge gaps. The work presented herein is neither a systematic review nor a critical appraisal of the scientific literature. Rather, it is a position paper that largely expresses the views of the authors based on their expert opinion drawn from industrial and academic experience.

How decision analysis can further nanoinformatics

The increase in nanomaterial research has resulted in increased nanomaterial data. The next challenge is to meaningfully integrate and interpret these data for better and more efficient decisions. Due to the complex nature of nanomaterials, rapid changes in technology, and disunified testing and data publishing strategies, information regarding material properties is often illusive, uncertain, and/or of varying quality, which limits the ability of researchers and regulatory agencies to process and use the data. The vision of nanoinformatics is to address this problem by identifying the information necessary to support specific decisions (a top-down approach) and collecting and visualizing these relevant data (a bottom-up approach). Current nanoinformatics efforts, however, have yet to efficiently focus data acquisition efforts on the research most relevant for bridging specific nanomaterial data gaps. Collecting unnecessary data and visualizing irrelevant information are expensive activities that overwhelm decision makers. We propose that the decision analytic techniques of multicriteria decision analysis (MCDA), value of information (VOI), weight of evidence (WOE), and portfolio decision analysis (PDA) can bridge the gap from current data collection and visualization efforts to present information relevant to specific decision needs. Decision analytic and Bayesian models could be a natural extension of mechanistic and statistical models for nanoinformatics practitioners to master in solving complex nanotechnology challenges.

Titanium nanoparticle inhalation induces renal fibrosis in mice via an oxidative stress upregulated transforming growth factor-β pathway

Titanium dioxide nanoparticles (Nano-TiO2) are gradually being used extensively in clinical settings, industry, and daily life. Accumulation studies showed that Nano-TiO2 exposure is able to cause injuries in various animal organs, including the lung, liver, spleen, and kidney. However, it remains unclear whether exposure of Nano-TiO2 by inhalation causes renal fibrosis. Here, we investigated the role of reactive oxygen species (ROS)/reactive nitrogen species (RNS) related signaling molecules in chronic renal damage after Nano-TiO2 inhalation in mice. Mice were treated with Nano-TiO2 (0.1, 0.25, and 0.5 mg/week) or microparticle-TiO2 (0.5 mg/week) by nonsurgical intratracheal instillation for 4 weeks. The results showed that Nano-TiO2 inhalation increased renal pathological changes in a dose-dependent manner. No renal pathological changes were observed in microparticle-TiO2-instilled mice. Nano-TiO2 (0.5 mg/week) possessed the ability to precipitate in the kidneys, determined by transmission electron microscopy and increased serum levels of blood urea nitrogen. The expressions of markers of ROS/RNS and renal fibrosis markers, including nitrotyrosine, inducible nitric oxide synthase, hypoxia inducible factor-1α (HIF-1α), heme oxygenase 1, transforming growth factor-β (TGFβ), and collagen I, determined by immunohistochemical staining were increased in the kidneys. Furthermore, Nano-TiO2-induced renal injury could be mitigated by iNOS inhibitor aminoguanidine and ROS scavenger N-acetylcysteine treatment in transcription level. The in vitro experiments showed that Nano-TiO2 significantly and dose-dependently increased the ROS production and the expressions of HIF-1α and TGFβ in human renal proximal tubular cells, which could be reversed by N-acetylcysteine treatment. Taken together, these results suggest Nano-TiO2 inhalation might induce renal fibrosis through a ROS/RNS-related HIF-1α-upregulated TGF-β signaling pathway.

ITS-NANO--prioritising nanosafety research to develop a stakeholder driven intelligent testing strategy

Background

To assess the risk of all nanomaterials (NMs) on a case-by-case basis is challenging in terms of financial, ethical and time resources. Instead a more intelligent approach to knowledge gain and risk assessment is required.

Methods

A framework of future research priorities was developed from the accorded opinion of experts covering all major stake holder groups (government, industry, academia, funders and NGOs). It recognises and stresses the major topics of physicochemical characterisation, exposure identification, hazard identification and modelling approaches as key components of the current and future risk assessment of NMs.

Results

The framework for future research has been developed from the opinions of over 80 stakeholders, that describes the research priorities for effective development of an intelligent testing strategy (ITS) to allow risk evaluation of NMs. In this context, an ITS is a process that allows the risks of NMs to be assessed accurately, effectively and efficiently, thereby reducing the need to test NMs on a case-by-case basis.

For each of the major topics of physicochemical characterisation, exposure identification, hazard identification and modelling, key-priority research areas are described via a series of stepping stones, or hexagon diagrams structured into a time perspective. Importantly, this framework is flexible, allowing individual stakeholders to identify where their own activities and expertise are positioned within the prioritisation pathway and furthermore to identify how they can effectively contribute and structure their work accordingly. In other words, the prioritisation hexagon diagrams provide a tool that individual stakeholders can adapt to meet their own particular needs and to deliver an ITS for NMs risk assessment. Such an approach would, over time, reduce the need for testing by increasing the reliability and sophistication of in silico approaches.

The manuscript includes an appraisal of how this framework relates to the current risk assessment approaches and how future risk assessment could adapt to accommodate these new approaches. A full report is available in electronic format (pdf) at http://www.nano.hw.ac.uk/research-projects/itsnano.html.

Conclusion

ITS-NANO has delivered a detailed, stakeholder driven and flexible research prioritisation (or strategy) tool, which identifies specific research needs, suggests connections between areas, and frames this in a time-perspective.

Environmental exposure assessment framework for nanoparticles in solid waste

Information related to the potential environmental exposure of engineered nanomaterials (ENMs) in the solid waste management phase is extremely scarce. In this paper, we define nanowaste as separately collected or collectable waste materials which are or contain ENMs, and we present a five-step framework for the systematic assessment of ENM exposure during nanowaste management. The framework includes deriving EOL nanoproducts and evaluating the physicochemical properties of the nanostructure, matrix properties and nanowaste treatment processes as well as transformation processes and environment releases, eventually leading to a final assessment of potential ENM exposure. The proposed framework was applied to three selected nanoproducts: nanosilver polyester textile, nanoTiO₂ sunscreen lotion and carbon nanotube tennis racquets. We found that the potential global environmental exposure of ENMs associated with these three products was an estimated 0.5-143 Mg/year, which can also be characterised qualitatively as medium, medium, low, respectively. Specific challenges remain and should be subject to further research: (1) analytical techniques for the characterisation of nanowaste and its transformation during waste treatment processes, (2) mechanisms for the release of ENMs, (3) the quantification of nanowaste amounts at the regional scale, (4) a definition of acceptable limit values for exposure to ENMs from nanowaste and (5) the reporting of nanowaste generation data.