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A strategy for grouping of nanomaterials based on key physico-chemical descriptors as a basis for safer-by-design NMs
Open accessAbstract
There is an urgent need to establish a fundamental understanding of the mechanisms of nanomaterial (NM) interaction with living systems and the environment, in order for regulation of NMs to keep pace with their increasing industrial application. Identification of critical properties (physicochemical descriptors) that confer the ability to induce harm in biological systems is crucial, enabling both prediction of impacts from related NMs (via quantitative nanostructure–activity relationships (QNARs) and read-across approaches) and development of strategies to ensure these features are avoided or minimised in NM production in the future (“safety by design”). A number of challenges to successful implementation of such a strategy exist, including: (i) the lack of widely available systematically varied libraries of NMs to enable generation of sufficiently robust datasets for development and validation of QNARs; (ii) the fact that many physicochemical properties of pristine NMs are inter-related and thus cannot be varied systematically in isolation from others (e.g. increasing surface charge may impact on hydrophobicity, or changing the shape of a NM may introduce defects or alter the atomic configuration of the surface); and (iii) the effect of ageing, transformation and biomolecule coating of NMs under environmental or biological conditions. A novel approach to identify interlinked physicochemical properties, and on this basis identify overarching descriptors (axes or principle components) which can be used to correlate with toxicity is proposed. An example of the approach is provided, using three principle components which we suggest can be utilised to fully describe each NM, these being the intrinsic (inherent) properties of the NM, composition (which we propose as a separate parameter) and extrinsic properties (interaction with media, molecular coronas etc.).
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Cites
Astrocyte-endothelial interactions at the blood-brain barrier
Abbott, N. J., Rönnbäck, L., & Hansson, E. (2006) · Nature Reviews Neuroscience · doi:10.1038/nrn1824 · Cited by 5,595
Physico-chemical features of engineered nanoparticles relevant to their toxicity
Fubini, B., Ghiazza, M., & Fenoglio, I. (2010) · Nanotoxicology · doi:10.3109/17435390.2010.509519 · Cited by 297
Cited by
Avellan, A., Yun, J., Morais, B. P., Clement, E. T., Rodrigues, S. M., & Lowry, G. V. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c00178 · Cited by 412
A functional assay-based strategy for nanomaterial risk forecasting
Hendren, C. O., Lowry, G. V., Unrine, J. M., & Wiesner, M. R. (2015) · Science of The Total Environment · doi:10.1016/j.scitotenv.2015.06.100 · Cited by 83
Gajewicz, A. (2017) · Nanoscale · doi:10.1039/c7nr02211e · Cited by 71
Metadata
- Authors
- Lynch, I., Weiss, C., & Valsami-Jones, E.
- Venue
- Nano Today
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 9
- Issue
- 3
- Pages
- 266-270
- ISSN
- 1748-0132 (ISSN-L)
- OpenAlex
- W2010883638
- Cited by
- 182
- References
- 2
- FWCI
- 8.64
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Lynch, I., Weiss, C., & Valsami-Jones, E. (2014). A strategy for grouping of nanomaterials based on key physico-chemical descriptors as a basis for safer-by-design NMs. Nano Today. https://doi.org/10.1016/j.nantod.2014.05.001
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