S-05-02 How can grouping and read-across support safe(r)-by-design of nanomaterials and advanced materials? GRACIOUS

Research output: Contribution to journalMeeting abstract


The GRACIOUS project has generated a Framework to support the grouping of nanoforms, in order to streamline human and environmental hazard testing, risk decision making during innovation and regulatory read-across. The Framework includes over 40 pre-defined 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). If the predefined hypotheses are not suitable, then the user is supported via a template to make their own user-defined hypothesis. 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. Quantitative similarity assessments conducted in a pairwise manner, property by property are needed for regulatory applications, while multifactor assessments using machine learning provide interesting research tools to look at entire data sets generated by the IATAs. A Guidance Document has been generated to support users in application of the GRACIOUS Framework, while a software blueprint has been generated to provide grouping and read-across functionality to risk assessment software.

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 (assessing forexample, the ability of substances to induce inflammation, oxidative stress, genotoxicity etc) 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.

GRACIOUS has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 760840.
Original languageEnglish
Pages (from-to)S19
Number of pages1
JournalToxicology Letters
Issue numberSupplement
Publication statusPublished - 1 Sept 2022


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