Framework for grouping and read-across nanomaterials and nanoforms

Nov 29, 2021

(Nanowerk News) For all substances, including nanomaterials, their safe use requires assessment of risk. Each nanomaterial of a particular substance (e.g. TiO2) may be available in multiple nanoforms that vary in characteristics such as shape, size and coating. Assessing the risks of each nanoform on a case by case basis is expensive, time consuming and requires lots of test animals. Grouping is an alternative approach that can be used to reduce the testing needed for risk assessment of nanomaterials for regulatory purposes. In addition, grouping can also be used for non-regulatory reasons. For instance, grouping may assist the introduction of Safe(r)-by-Design methods into product development of nanoforms and nano-enabled products. It may also help in the identification of suitable risk management measures for industrial or professional facilities using nanomaterials. According to the European REACH regulations for chemicals, grouping requires generation of a scientific hypothesis to explain why substances are sufficiently similar to be grouped. This explanation should be scientifically solid and can be used to fill data gaps with already existing information. Evidence, including a data matrix, is required to allow the grouping hypothesis to be accepted. Once a group is established, read-across of data can then be conducted. This means that data from source substances which include hazard data for risk assessment, may be used in order to fill the hazard data gaps of target substances. Grouping and read-across of nanomaterials requires other considerations than regular substances, as not only chemical, but also physical properties of a material can have an impact on risk. However, the actual application of grouping and read-across for nanomaterials is limited, because detailed approaches to substantiate grouping and read-across of nanoforms are missing.

Project achievements

The GRACIOUS project generated a Framework to support grouping and read-across of nanoforms. The Framework will allow end users to identify if one of the pre-defined GRACIOUS grouping hypotheses are relevant to their nanoform. It is key that grouping decisions are hypothesis based. We have generated robust grouping hypotheses, based on existing published literature and grey literature. Each grouping hypothesis has an integrated approach to testing and assessment (IATA). This guides what information an end user needs to obtain to make a grouping decision. The IATAs are structured as decision trees and in the first instance we encourage end users to perform a literature search. This allows the end user to identify if existing information can be used to make a grouping decision for each decision node. If data gaps need to be filled, then the end user can use the tiered testing strategies which accompany each decision node of the IATA. These strategies are designed to identify what experimental testing should be performed to generate the necessary data for a grouping decision. The IATAs allow an end user to identify if the grouping hypothesis can be accepted or rejected. It may be that none of the GRACIOUS pre-defined grouping hypotheses are appropriate. For those cases we developed a hypothesis template to help end-users to formulate their own grouping hypothesis. Furthermore, different approach to quantify the similarity between nanoforms are compared and applied to case studies to gain experience. This Framework has been extensively tested by industrial, regulatory and academic stakeholders. The approaches used are sufficiently flexible to allow use of predicted or estimated data in the early concept stages. Such data often have high levels of uncertainty. As the user progresses through development of the nanomaterial/product, the predicted or estimated data are replaced with data sources of higher certainty. These higher certainty data are more suitable for regulatory purposes.” The GRACIOUS project partners are now happy to share some of their flagship results:

The GRACIOUS Guidance Documents

The GRACIOUS project has developed two Guidance documents explaining how users from industry, regulation and academia can use the GRACIOUS Framework for grouping and read-across of nanomaterials/nanoforms. The first is a detailed GRACIOUS Guidance Document which provides users with a detailed step-by-step guidance on how to use the Framework. This document also includes hands-on examples and practical tips for users. The second is a Guidance in a Nutshell. This is a simplified short version of the detailed document. It is intended to be an introduction to both the concepts used in the GRACIOUS Framework and the main steps the user will need to address during the use of the Framework.

The GRACIOUS Blueprint

The GRACIOUS Framework is also available as a software Blueprint PDF document. This provides building blocks and insights on how to implement the GRACIOUS framework – or specific parts of it – into existing and future software for risk assessment or safe(r)-by-design. The GRACIOUS Blueprint will be made publicly available in Zenodo. The Blueprint is open for any interested parties who wish to integrate elements of the GRACIOUS Framework in their software tools. The Blueprint will be further developed in H2020 projects SAbyNA, SbD4Nano, SUNSHINE and HARMLESS. Updates are to be expected in the upcoming years.
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The GRACIOUS Blueprint has been tested and already programmed in the SUN Decision Support System (SUNDS) which is freely available at www.sunds.gd by self-sign-up. Blueprint entities and rules for Integrated Approaches to Testing and Assessment (IATA) application have been integrated into the original SUNDS framework. This framework is now capable of performing risk assessment considering nanoforms’ characterization parameters and IATA based groups. The enriched data structure allowed by the blueprint makes the sustainability assessment provided by SUNDS more reliable and precise.

The GRACIOUS Further Achievements

Within three and a half years of intensive work, the GRACIOUS consortium aimed at reaching the ambitious goal to develop a highly innovative science-based grouping and read-across Framework. This has resulted in the development of a number of scientific, educational and innovation results. We believe these results will have a long-term impact in the nanotechnology field. These include:

The GRACIOUS Similarity Assessment Methodology

The GRACIOUS Data Quality Assessment Methodology

The GRACIOUS IATAs and Hypotheses Templates (e.g. HARN IATA, Inhalation IATA, Ingestion IATA, Framework structure description)

The GRACIOUS Decision trees, Templates, and Library for generation of grouping approaches

The GRACIOUS Nanomaterial Physicochemical templates

The GRACIOUS standard operating procedures (SOPs) (e.g. of known reproducibility, coating degradation assays, reactivity, dissolution)

The GRACIOUS WIKI (terminology harmonizer)

The GRACIOUS Database – an instance of the eNanoMapper Database that compiles data generated in the GRACIOUS project.

GRACIOUS Videos – GRACIOUS developed a number of short videos explaining key aspects of the GRACIOUS Framework.

GRACIOUS educational materials – GRACIOUS has developed a number of webinars, workshops and training sessions on various topics relevant for the project.

GRACIOUS peer-reviewed literature – GRACIOUS is at the forefront of open science. We have published a number of open access manuscripts describing our scientific results. These are available to access via our website and Openaire. Please keep an eye at our website for new publications.

GRACIOUS research data and other publications – GRACIOUS other research products are published and freely available at Openaire. These include templates, SOPs, presentations, etc.