How can Grouping and Read-Across support Safe(r)-by-design and regulation of Nanomaterials and Advanced Materials?

Nanomaterials are defined as objects with at least two dimensions between one and one hundred nanometres. They come in a wide variety of compositions and shapes, and due to their interesting properties, they are used in a wide variety of applications including medicine, diagnostics, electronics, energy, clothing, food and antimicrobial coatings. Due to their wide use it is important that we understand their safety, but their unusual properties can make prediction of their risk difficult.
The GRACIOUS project has generated a Framework to support the grouping of different types of nanonmaterials (known as nanoforms), in order to streamline hazard testing and risk decision making during innovation and regulatory read-across. The Framework includes hypotheses that provide a scientifically robust logic for grouping based upon not just physicochemical properties (what they are), but also exposure (where they go) and hazard (what they do). The gathering of existing and new evidence to support these hypotheses is supported by novel, tailored Integrated Approaches to Testing and Assessment (IATAs). Usage of the IATAs allows compilation of a data matrix to support qualitative or quantitative similarity assessments of the putative group members.
European projects such as SAbyNA, SUNSHINE, HARMLESS and DIAGONAL, are now adopting the GRACIOUS Framework, in order to develop it further to support safe(r) by design (SbD) of nanomaterials and nano-enabled products, including multicomponent nanomaterials and advanced materials. These projects will work together to expand the existing portfolio of grouping hypotheses and IATAs to consider mixture effects and the new advanced properties anticipated. The use of tiered testing strategies to address each decision node within the IATAs, allows the hypotheses and IATAs to support decision making ideally from the initial concept stage. The approaches used are sufficiently flexible to allow use of predicted or estimated data, with high levels of uncertainty, in the early concept stages. As the user progresses through development of the nanomaterial/product, the predicted or estimated data are replaced with sources of higher certainty that are more suitable for regulatory purposes.