Validation of size estimation of nanoparticle tracking analysis on polydisperse macromolecule assembly

• Main Authors: Kim, Ahram, Ng, Wei Beng, Bernt, William, Cho, Nam-Joon
• Other Authors: School of Chemical and Biomedical Engineering
• Format: Article
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Materials; Nanoscale Biophysics; Nanoparticles
• Online Access: https://hdl.handle.net/10356/85865; http://hdl.handle.net/10220/48241
• Institution: Nanyang Technological University

As the physicochemical properties of drug delivery systems are governed not only by the material properties which they are compose of but by their size that they conform, it is crucial to determine the size and distribution of such systems with nanometer-scale precision. The standard technique used to measure the size distribution of nanometer-sized particles in suspension is dynamic light scattering (DLS). Recently, nanoparticle tracking analysis (NTA) has been introduced to measure the diffusion coefficient of particles in a sample to determine their size distribution in relation to DLS results. Because DLS and NTA use identical physical characteristics to determine particle size but differ in the weighting of the distribution, NTA can be a good verification tool for DLS and vice versa. In this study, we evaluated two NTA data analysis methods based on maximum-likelihood estimation, namely finite track length adjustment (FTLA) and an iterative method, on monodisperse polystyrene beads and polydisperse vesicles by comparing the results with DLS. The NTA results from both methods agreed well with the mean size and relative variance values from DLS for monodisperse polystyrene standards. However, for the lipid vesicles prepared in various polydispersity conditions, the iterative method resulted in a better match with DLS than the FTLA method. Further, it was found that it is better to compare the native number-weighted NTA distribution with DLS, rather than its converted distribution weighted by intensity, as the variance of the converted NTA distribution deviates significantly from the DLS results.