There has been a rapid growth in the use of engineered nanomaterials (ENM) in several industrial processes and consumer products. This has led especially to an increase in the number of workers exposed to these materials in the working environment. Assessment of hazards and risks of engineered nano materials have lagged behind compared to the ongoing discoveries of novel engineered nano materials, and the products based on them. This is due to the specific challenges caused by a number of unconventional features of engineered nano materials, as compared with traditional soluble chemicals.
To improve the ability to assess potential hazards and risks of these engineered nano materials, and to better manage them, FIOH coordinated the NANOSOLUTIONS project, led by professor Kai Savolainen and funded by the EU 7th Framework Programme, during 2013 – 2017 with 35 partners and 10 million euro contribution of EU funding.
The main goal of the project was to develop a nanosafety classifier through increasing the knowledge base and understanding of engineered nano materials (ENM) physicochemical properties and biological features. The project analyzed ENM-induced toxic endpoints in different cell types and environmental and mammalian organisms, and changes in gene and protein expression through omics technologies.
By using this largest dataset generated on engineered nano materials so far, the project, by using bioinformatics, developed means to classify ENM into three qualitative hazard categories: 1) no to low toxicity; 2) medium toxicity; and 3) high toxicity.
The results of the developed nanosafety classifier, in essence a set of genetic mathematical algorithms (artificial intelligence), will be forwarded to be used by the regulatory and scientific community to improve the reliability of assessment of engineered nano materials hazards and risks.
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