Nanomaterials (NMs) display many unique and useful physico-chemical properties. However, reliable approaches are needed for risk assessment of NMs. The present study was performed in the FP7-MARINA project, with the objective to identify and evaluate in vitro test methods for toxicity assessment in order to facilitate the development of an intelligent testing strategy (ITS). Six representative oxide NMs provided by the EC-JRC Nanomaterials Repository were tested in nine laboratories. The in vitro toxicity of NMs was evaluated in 12 cellular models representing 6 different target organs/systems (immune system, respiratory system, gastrointestinal system, reproductive organs, kidney and embryonic tissues). The toxicity assessment was conducted using 10 different assays for cytotoxicity, embryotoxicity, epithelial integrity, cytokine secretion and oxidative stress. Thorough physico-chemical characterization was performed for all tested NMs. Commercially relevant NMs with different physico-chemical properties were selected: two TiO2 NMs with different surface chemistry – hydrophilic (NM-103) and hydrophobic (NM-104), two forms of ZnO – uncoated (NM-110) and coated with triethoxycapryl silane (NM-111) and two SiO2 NMs produced by two different manufacturing techniques – precipitated (NM-200) and pyrogenic (NM-203). Cell specific toxicity effects of all NMs were observed; macrophages were the most sensitive cell type after short-term exposures (24-72h) (ZnO>SiO2>TiO2). Longer term exposure (7 to 21 days) significantly affected the cell barrier integrity in the presence of ZnO, but not TiO2 and SiO2, while the embryonic stem cell test (EST) classified the TiO2 NMs as potentially ‘weak-embryotoxic’ and ZnO and SiO2 NMs as ‘non-embryotoxic’. A hazard ranking could be established for the representative NMs tested (ZnO NM-110 > ZnO NM-111 > SiO2 NM-203 > SiO2 NM-200 > TiO2 NM-104 > TiO2 NM-103). This ranking was different in the case of embryonic tissues, for which TiO2 displayed higher toxicity compared with ZnO and SiO2. Importantly, the in vitro methodology applied could identify cell- and NM-specific responses, with a low variability observed between different test assays. Overall, this testing approach, based on a battery of cellular systems and test assays, complemented by an exhaustive physico-chemical characterization of NMs, could be deployed for the development of an ITS suitable for risk assessment of NMs. This study also provides a rich source of data for modeling of NM effects.

Physicochemical properties of chemicals affect their exposure, toxicokinetics/fate and hazard, and for nanomaterials, the variation of these properties results in a wide variety of materials with potentially different risks. To limit the amount of testing for risk assessment, the information gathering process for nanomaterials needs to be efficient. At the same time, sufficient information to assess the safety of human health and the environment should be available for each nanomaterial. Grouping and read-across approaches can be utilised to meet these goals. This article presents different possible applications of grouping and read-across for nanomaterials within the broader perspective of the MARINA Risk Assessment Strategy (RAS), as developed in the EU FP7 project MARINA. Firstly, nanomaterials can be grouped based on limited variation in physicochemical properties to subsequently design an efficient testing strategy that covers the entire group. Secondly, knowledge about exposure, toxicokinetics/fate or hazard, for example via properties such as dissolution rate, aspect ratio, chemical (non-)activity, can be used to organise similar materials in generic groups to frame issues that need further attention, or potentially to read-across. Thirdly, when data related to specific endpoints is required, read-across can be considered, using data from a source material for the target nanomaterial. Read-across could be based on a scientifically sound justification that exposure, distribution to the target (fate/toxicokinetics) and hazard of the target material are similar to, or less than, the source material. These grouping and read-across approaches pave the way for better use of available information on nanomaterials and are flexible enough to allow future adaptations related to scientific developments.

Bringing together topic-related European Union (EU)-funded projects, the so-called “NanoSafety Cluster” aims at identifying key areas for further research on risk assessment procedures for nanomaterials (NM). The outcome of NanoSafety Cluster Working Group 10, this commentary presents a vision for concern-driven integrated approaches for the (eco-)toxicological testing and assessment (IATA) of NM. Such approaches should start out by determining concerns, i.e., specific information needs for a given NM based on realistic exposure scenarios. Recognised concerns can be addressed in a set of tiers using standardised protocols for NM preparation and testing. Tier 1 includes determining physico-chemical properties, non-testing (e.g., structure–activity relationships) and evaluating existing data. In tier 2, a limited set of in vitro and in vivo tests are performed that can either indicate that the risk of the specific concern is sufficiently known or indicate the need for further testing, including details for such testing. Ecotoxicological testing begins with representative test organisms followed by complex test systems. After each tier, it is evaluated whether the information gained permits assessing the safety of the NM so that further testing can be waived. By effectively exploiting all available information, IATA allow accelerating the risk assessment process and reducing testing costs and animal use (in line with the 3Rs principle implemented in EU Directive 2010/63/EU). Combining material properties, exposure, biokinetics and hazard data, information gained with IATA can be used to recognise groups of NM based upon similar modes of action. Grouping of substances in return should form integral part of the IATA themselves.

Commercialization of nanotechnologies entails a regulatory requirement for understanding their environmental, health and safety (EHS) risks. Today we face challenges to assess these risks, which emerge from uncertainties around the interactions of manufactured nanomaterials (MNs) with humans and the environment. In order to reduce these uncertainties, it is necessary to generate sound scientific data on hazard and exposure by means of relevant frameworks and tools. The development of such approaches to facilitate the risk assessment (RA) of MNs has become a dynamic area of research. The aim of this paper was to review and critically analyse these approaches against a set of relevant criteria. The analysis concluded that none of the reviewed frameworks were able to fulfill all evaluation criteria. Many of the existing modelling tools are designed to provide screeninglevel assessments rather than to support regulatory RA and risk management. Nevertheless, there is a tendency towards developing more quantitative, higher-tier models, capable of incorporating uncertainty into their analyses. There is also a trend towards developing validated experimental protocols for material identification and hazard testing, reproducible across laboratories. These tools could enable a shift from a costly case-by-case RA of MNs towards a targeted, flexible and efficient process, based on grouping and read-across strategies and compliant with the 3R (Replacement, Reduction, Refinement) principles. In order to facilitate this process, it is important to transform the current efforts on developing databases and computational models into creating an integrated data and tools infrastructure to support the risk assessment and management of MNs.

We developed a population physiology model, physB, which provides a statistical description of the physiological characteristics in the human population, in terms of the physiological parameters that are needed in physiologically based pharmacokinetic modelling. The model predicts individual organ weights, blood flows and some respiratory parameters from anthropometric properties (body height and weight, age and gender). It draws on two existing models, PK-Pop and P(3)M, but various changes and improvements were made. The conceptual differences among the three models are discussed and they are quantitatively compared by running all three models for various specific combinations of anthropometric properties.