Advanced single particle characterisation of cargo loading in therapeutic particles
File(s)
Author(s)
Saunders, Catherine
Type
Thesis
Abstract
Using particles as drug delivery systems offers a flexible modality for improved biostability and controlled release. However, these systems often exhibit compositional and cargo loading heterogeneity, which impacts their biological behaviours. This heterogeneity is challenging to characterise with standard analytical techniques, which hinders translation of new formulations to the clinic. Consequently, there is great opportunity to develop advanced techniques to characterise therapeutic particles. In this thesis, several advanced characterisation methods are applied to study cargo loading in a variety of drug delivery systems. One study utilised a recently developed platform, single particle automated Raman trapping analysis (SPARTA), which gives single particle information at the population level. An analysis method was developed herein to determine cargo loading location in vesicles and population heterogeneity. This method allowed detailed characterisation of cargo loading behaviours in a wide range of nanovesicles, including commercial formulations. Another study utilised small angle neutron scattering (SANS) to study bulk-level structural changes in nanostructured lipid nanoparticles (LNP) based on formulation, and protein loading. This was combined with fluorescence correlation spectroscopy (FCS) to examine the connections between LNP formulation, morphology and loading ability. This revealed that protein loading is dictated by the interaction between electrostatic, lipid ordering and sterics. The final study utilised confocal Raman imaging to study changes in drug release and carrier morphology in microparticles for controlled release. A platform was developed to allow repeated measurements on the same microparticles over several weeks, combined with measurement automation for population-level analysis. Taken together, the methods developed and utilised in this thesis allow population-level understanding of cargo loading in therapeutic particles, with single particle detail. This approach is crucial to understanding population heterogeneity, which can support manufacturing quality control, inform regulatory characterisation standards, and aid the prediction of in vivo behaviours, to ultimately advance the translation of future particle-based therapeutics.
Version
Open Access
Date Issued
2023-09-27
Date Awarded
2024-03-01
Copyright Statement
Creative Commons Attribution NonCommercial NoDerivatives Licence
Advisor
Stevens, Molly
Sponsor
Engineering and Physical Sciences Research Council
Grant Number
EP/S023259/1
Publisher Department
Materials
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)