Refinement of the selection of physicochemical properties for grouping and read-across of nanoforms

Before placing a new nanoform (NF) on the market, its potential adverse effects must be evaluated. This may e.g. be done via hazard and risk assessment. Grouping and read-across of NFs is a possible strategy to reduce resource consumption, maximising the use of existing data for assessment of NFs. The GRACIOUS project provides a framework in which possible grouping and read-across for NFs is mainly based on an evaluation of their similarity. The impact of NFs on human health and the environment depends strongly on the concentration of the NF and its physicochemical properties, such as chemical composition, size distribution, shape, etc. Hence, knowledge of the most relevant physicochemical properties is essential information for comparing similarity. The presented work aims to refine existing proposals for sets of descriptors (descriptor array) that are needed to describe distinct NFs of a material to identify the most relevant ones for grouping and read-across. The selection criteria for refining this descriptor array are explained and demonstrated. Relevant protocols and methods are proposed for each physicochemical property. The required and achievable measurement accuracies of the refined descriptor array are reviewed, as this information is necessary for similarity assessment of NFs based on individual physicochemical properties.

Automated summary

Before introducing a new nanoform on the market, it is important to evaluate its potential adverse effects through hazard and risk assessment. Grouping and read-across of nanoforms can help reduce resource consumption and maximize the use of existing data for assessment. The impact of nanoforms on human health and the environment depends greatly on their concentration and physicochemical properties, making knowledge of these properties essential for assessing similarity.