Abstract
The current frontiers in Biology thus in Medicine and Pharmacy are at the nanoscale. Indeed, this is the relevant scale for extracting or synthetizing, visualizing, counting, characterizing and/or modifying nanoparticles. Nanoparticles are highly diverse including: extracellular vesicles (e.g.: exosomes), proteins, viruses and nanovectors or drug delivery systems for instance. To quantify the concentration of nano-sized objects, a growing number of size-tracking instruments is being developed. However, to date, the generated data is only used to provide a concentration measurement. The objective of this study was to determine which sizes of nanoparticles are statistically significant between 2 groups of samples. Using different samples (in silico data; calibrated beads; various biological samples), an approach that statistically compares 2 groups of samples was developed and validated. The proof of concept of the proposed approach was illustrated with applications in the field of Biology, Medicine and Pharmacy using liposomes and extracellular vesicles. For the first time to our knowledge, our results suggest that the presented approach enables comparing different groups of biological samples. It may be extended to situations such as batch 1 versus batch 2; healthy versus disease or non-treated versus treated.