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Toward Nano‐Specific In Silico NAMs: How to Adjust Nano‐QSAR to the Recent Advancements of Nanotoxicology?

Authors: Ciura, Krzesimir; Moschini, Elisa; Stępnik, Maciej; Serchi, Tommaso; Gutleb, Arno; Jarzyńska, Kamila; Jagiello, Karolina; +1 Authors

Toward Nano‐Specific In Silico NAMs: How to Adjust Nano‐QSAR to the Recent Advancements of Nanotoxicology?

Abstract

AbstractThe rapid development of engineered nanomaterials (ENMs) causes humans to become increasingly exposed to them. Therefore, a better understanding of the health impact of ENMs is highly demanded. Considering the 3Rs (Replacement, Reduction, and Refinement) principle, in vitro and computational methods are excellent alternatives for testing on animals. Among computational methods, nano‐quantitative structure‐activity relationship (nano‐QSAR), which links the physicochemical and structural properties of EMNs with biological activities, is one of the leading method. The nature of toxicological experiments has evolved over the last decades; currently, one experiment can provide thousands of measurements of the organism's functioning at the molecular level. At the same time, the capacity of the in vitro systems to mimic the human organism is also improving significantly. Hence, the authors would like to discuss whether the nano‐QSAR approach follows modern toxicological studies and takes full advantage of the opportunities offered by modern toxicological platforms. Challenges and possibilities for improving data integration are underlined narratively, including the need for a consensus built between the in vitro and the QSAR domains.

Country
Poland
Keywords

nano-quantitative structure-activity relationship (nano-QSAR), Humans, Animals, Quantitative Structure-Activity Relationship, new approach methodologies, nanotoxicology, next-generation risk assessment, Nanostructures

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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
Green