Revealing population heterogeneity in vesicle-based nanomedicines using automated, single particle Raman analysis
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
The intrinsic heterogeneity of many nanoformulations is currently challenging to characterise on both
the single particle and population level. Therefore there is great opportunity to develop new
techniques to describe and understand nanomedicine heterogeneity, which will aid translation to the
clinic by informing manufacturing quality control, characterisation for regulatory bodies, and
connecting nanoformulation properties to clinical outcomes to enable rational design. Here, we
present an analytical technique to provide such information, whilst measuring the nanocarrier and
cargo simultaneously with label-free, non-destructive single particle automated Raman trapping
analysis (SPARTA). We first synthesised a library of model compounds covering a range of
hydrophilicities and providing distinct Raman signals. These compounds were then loaded into model
nanovesicles (polymersomes) that can load both hydrophobic and hydrophilic cargo into the
membrane or core regions respectively. Using our analytical framework, we characterised the
heterogeneity of the population by correlating the per particle membrane and cargo signals. We found
that core and membrane loading can be distinguished, and we detected sub-populations of highly
loaded particlesin certain cases. We then confirmed suitability of our technique in liposomes, another
Peer reviewed version of the manuscript published in final form in ACS Nano (2023)
2
nanovesicle class, including the commercial formulation Doxil. Our label-free analytical technique
precisely determines cargo location alongside loading and release heterogeneity in nanomedicines,
which could be instrumental for future quality control, regulatory body protocols and development of
structure-function relationships, to bring more nanomedicines to the clinic
the single particle and population level. Therefore there is great opportunity to develop new
techniques to describe and understand nanomedicine heterogeneity, which will aid translation to the
clinic by informing manufacturing quality control, characterisation for regulatory bodies, and
connecting nanoformulation properties to clinical outcomes to enable rational design. Here, we
present an analytical technique to provide such information, whilst measuring the nanocarrier and
cargo simultaneously with label-free, non-destructive single particle automated Raman trapping
analysis (SPARTA). We first synthesised a library of model compounds covering a range of
hydrophilicities and providing distinct Raman signals. These compounds were then loaded into model
nanovesicles (polymersomes) that can load both hydrophobic and hydrophilic cargo into the
membrane or core regions respectively. Using our analytical framework, we characterised the
heterogeneity of the population by correlating the per particle membrane and cargo signals. We found
that core and membrane loading can be distinguished, and we detected sub-populations of highly
loaded particlesin certain cases. We then confirmed suitability of our technique in liposomes, another
Peer reviewed version of the manuscript published in final form in ACS Nano (2023)
2
nanovesicle class, including the commercial formulation Doxil. Our label-free analytical technique
precisely determines cargo location alongside loading and release heterogeneity in nanomedicines,
which could be instrumental for future quality control, regulatory body protocols and development of
structure-function relationships, to bring more nanomedicines to the clinic
Date Issued
2023-06-27
Date Acceptance
2023-05-30
Citation
ACS Nano, 2023, 17 (12), pp.11713-11728
ISSN
1936-0851
Publisher
American Chemical Society
Start Page
11713
End Page
11728
Journal / Book Title
ACS Nano
Volume
17
Issue
12
Copyright Statement
Copyright © 2023 The Authors. Published by American Chemical Society. This work is published under a CC BY licence.
License URL
Identifier
https://pubs.acs.org/doi/10.1021/acsnano.3c02452
Publication Status
Published
Date Publish Online
2023-06-06