Nanotechnology is rapidly expanding. However, some types of engineered nanoparticles can be toxic for living organisms and exhibit negative impact on the environment. Thus, the design of new nanoparticles must be accompanied by a rigorous risk analysis. Following the recommendations by the EU REACH system and regarding ethical aspects, the risk assessment procedures should be performed with possible reduction of living animals’ use. One of the most promising options is the application of computational techniques. In addition to the reduction of animal use, such a solution enables significantly reducing costs of the required risk assessment.

The main objective of the ^NanoPUZZLES project is to develop, within three years, a package of computational algorithms for the comprehensive modelling of the relationships between the structure, properties, molecular interactions and toxicity of selected classes of engineered nanoparticles (NPs). The package (i) will serve as a proof-of-the-concept that the risk related to NPs can be comprehensively assessed with use of computational techniques and (ii) will define a basis for development of further modelling techniques for a large variety of nanoparticles.

The project will focus on two groups of compounds: (i) inorganic engineered nanoparticles (metal nanooxides) and (ii) carbon nanoparticles (carbon nanotubes (single-walled and multi-walled), fullerenes and fullerene derivatives). That choice was dictated by the wide application of these nanoparticles in everyday household products, and by the fact that these compounds are commercially available in the market whch eliminates the necessity for their synthesis (reduction of costs).

Computational algorithms will be developed within four work packages related to the following thematic areas:

• Quality assessment of physicochemical and toxicological data available for nanomaterials and data exploration (^NanoDATA),
• Development of novel descriptors for nanoparticles’ structure (^NanoDESC),
• Simulating interactions of nanoparticles with biological systems (^NanoINTER),
• Quantitative and qualitative structure-activity relationship modelling, grouping and read across (^NanoQSAR).

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