Home > Nanotechnology Columns > Nanosafety and Nonanimal Testing Methods > Grouping and Read-Across Approaches for Nanomaterials
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Monita Sharma Nanotoxicology Specialist PETA International Science Consortium Ltd. |
Abstract:
Monita Sharma and Jodie Melbourne
Nanomaterials (NMs) are used in a variety of consumer products, including food, electronics, paints, and building materials.
June 21st, 2016
Grouping and Read-Across Approaches for Nanomaterials
Nanomaterials (NMs) are used in a variety of consumer products, including food, electronics, paints, and building materials. Based on their intended use, NMs can be manufactured from various materials (e.g., metal, metal oxide, carbon, or polymers), have diverse shapes (e.g., spheres, cubes, rods, or wires) and sizes, and can have unique surface modifications. Furthermore, NMs undergo transformations during their lifecycle specific to their environment, such as agglomeration, dissolution, and changes to surface properties, altering them from their as-manufactured state. The safe incorporation of the growing list of different types of NMs into consumer products requires adequate assessment of the biological and environmental impact of each type and form. However, generating data on every possible type of NM in a timely manner is a daunting task and one of the main problems confronting the field of nanotechnology today.
Grouping, or categorization, has been proposed as a possible solution for assessing NMs, while simultaneously reducing the amount of testing conducted. As with traditional chemicals, grouping can facilitate read-across, which essentially means predicting hazard information for a substance by using existing data from tests conducted on another, similar substance. Once grouped, the characteristics of a NM, including its toxicity, can be predicted by reading across data from other, similar NMs within the same group [1].
The grouping of NMs can be based on a number of parameters, including their location within the product (i.e., likely exposure) and their physico-chemical properties [2,3,4,5]. The potential toxicity of a substance can be predicted by linking NM properties, such as material type (e.g., carbonaceous, metal oxide, or metal), shape (e.g., sphere, fibre, or rod), size, solubility, or hydrophobicity, to its biological impact. Grouping approaches that consider multiple aspects, such as use, exposure, biophysical interaction, uptake, and NM properties can facilitate read-across and be used to create effective risk-assessment strategies that rely on nonanimal techniques [6].
To increase the robustness and accuracy of grouping and read-across, data from well-designed in vitro studies should continue to be used and generated in order to link bio- and ecologically relevant NM forms to their effects. Confidence in grouping and read-across approaches can also be increased through their practical application in the form of published case studies and through the sharing of data for the development of hazard- and risk-assessment strategies [7,8].
Grouping and read-across are vital tools in expediting hazard testing. They also play an important role in moving away from traditional regulatory "check the box" testing procedures and reducing the number of tests conducted by collating and structuring the available data in a systematic way, thereby contributing to the sustainable development of nanotechnology.
References:
1. Gajewicz A, et al. Novel approach for efficient predictions properties of large pool of nanomaterials based
on limited set of species: nano-read-across. Nanotechnology. 2015;26(1):015701.
2. Braakhuis HM, Oomen AG, Cassee FR. Grouping nanomaterials to predict their potential to induce
pulmonary inflammation. Toxicol Appl Pharmacol. 2016;299(0):3-7.
3. Hansen SF, et al. Categorization framework to aid exposure assessment of nanomaterials in consumer
products. Ecotoxicology. 2008;17(5):438-47.
4. Hansen SF, et al. Categorization framework to aid hazard identification of nanomaterials.
Nanotoxicology. 2007;1(3):243-250.
5. Hallock MF, et al. Potential risks of nanomaterials and how to safely handle materials of uncertain toxicity.
J Chemical Health Safety. 2009;16(1):16-23.
6. Arts JH, et al. A decision-making framework for the grouping and testing of nanomaterials
(DF4nanoGrouping). Regul Toxicol Pharmacol. 2015;71(2 Suppl):S1-S27.
7. Oomen AG, et al. Grouping and read-across approaches for risk assessment of nanomaterials. Int
J Environ Res Public Health. 2015;12(10):13415-13434.
8. Arts JH, et al. A decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping). Regul Toxicol Pharmacol, 2015. 71(2 Suppl): p. S1-27.
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