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@ARTICLE{Kolb:646210,
author = {Kolb, Bastian and Graewert, Melissa and Drexel, Roland and
Meier, Florian and Raab, Justin and Wilhelmy, Christoph and
Nawroth, Thomas and Soloviov, Dmytro and Haas, Heinrich and
Langguth, Peter},
title = {{A}dvanced {Q}uality and {C}omparability {A}ssessment of
m{RNA}-{L}oaded {L}ipid {N}anoparticles: {A}bsolute {S}ize
{D}istribution {P}rofiles and {S}tructure from
{AF}4-{C}oupled {L}ight and {X}-ray {S}cattering
{M}easurements},
journal = {Analytical chemistry},
volume = {xx},
issn = {0003-2700},
address = {Columbus, Ohio},
publisher = {American Chemical Society},
reportid = {PUBDB-2026-00755},
pages = {acs.analchem.5c05911},
year = {2026},
abstract = {The success of mRNA lipid nanoparticles (LNPs) used in the
COVID-19 vaccines has demonstrated the significance of
pharmaceutical products utilizing nanoparticle-based drug
delivery systems in global healthcare. For the assessment of
the safety, efficacy, and quality of these complex,
multicomponent systems, it is important to consider not only
the properties of the individual components but also their
colloidal organization. There is a need for standardized
methods to fulfill requirements for application in regular
quality control, providing information on these properties
in pharmaceutical products. To gain insight into size and
size-resolved quality attributes of LNPs, we apply
asymmetrical flow field-flow fractionation (AF4) coupled
in-line with synchrotron small-angle X-ray scattering (SAXS)
measurements, multiangle light scattering (MALS), and UV
absorption measurements. We propose model-free algorithms
for the analysis of light scattering and X-ray scattering
data to obtain quantitative size distribution profiles from
both methodologies. The approach is equally applicable for
SAXS and MALS data, but SAXS additionally provides detailed,
size-resolved insight into internal structure. Information
on various quality-indicating parameters for the
size-fractionated samples is obtained, including drug
loading, internal organization, and particle shape. Since
this approach does not require any model assumptions to
obtain structural, quality-indicative information from
experimental data, it is ideally suitable to evaluate the
comparability of results from different systems and
different laboratories. This makes it a valuable extension
to the regular quality control panel for pharmaceutical
nanoparticles, and it should be considered as a standard
method in the pharmacopoeias.},
cin = {EMBL-User / EMBL},
ddc = {540},
cid = {I:(DE-H253)EMBL-User-20120814 / I:(DE-H253)EMBL-20120731},
pnm = {6G3 - PETRA III (DESY) (POF4-6G3)},
pid = {G:(DE-HGF)POF4-6G3},
experiment = {EXP:(DE-H253)P-P12-20150101},
typ = {PUB:(DE-HGF)16},
doi = {10.1021/acs.analchem.5c05911},
url = {https://bib-pubdb1.desy.de/record/646210},
}