Application of light scattering techniques to nanoparticle characterization and development

Copyright © 2018 Carvalho, Felício, Santos, Gonçalves and Domingues. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Over the years, the scientific importance of nanoparticles for biomedical applications has increased. The high stability and biocompatibility, together with the low toxicity of the nanoparticles developed lead to their use as targeted drug delivery systems, bioimaging systems, and biosensors. The wide range of nanoparticles size, from 10 nm to 1 μm, as well as their optical properties, allow them to be studied using microscopy and spectroscopy techniques. In order to be effectively used, the physicochemical properties of nanoparticle formulations need to be taken into account, namely, particle size, surface charge distribution, surface derivatization and/or loading capacity, and related interactions. These properties need to be optimized considering the final nanoparticle intended biodistribution and target. In this review, we cover light scattering based techniques, namely dynamic light scattering and zeta-potential, used for the physicochemical characterization of nanoparticles. Dynamic light scattering is used to measure nanoparticles size, but also to evaluate their stability over time in suspension, at different pH and temperature conditions. Zeta-potential is used to characterize nanoparticles surface charge, obtaining information about their stability and surface interaction with other molecules. In this review, we focus on nanoparticle characterization and application in infection, cancer and cardiovascular diseases.This work was supported by Fundação para a Ciência e a Tecnologia–Ministério da Ciência, Tecnologia e Ensino Superior (FCT-MCTES, Portugal) projects PTDC/BBBBQB/3494/2014 and PTDC/BBB-BMD/6307/2014. This work was also supported by LISBOA-01-0145-FEDER-007391 project, cofunded by FEDER, through POR Lisboa 2020—Programa Operacional Regional de Lisboa, PORTUGAL 2020, and Fundação para a Ciência e a Tecnologia. PMC, MRF and MMD acknowledge FCT-MCTES fellowships SFRH/BD/108077/2015, SFRH/BD/100517/2014, and SFRH/BPD/122779/2016, respectively