# Advanced Quality and Comparability Assessment of mRNA-Loaded Lipid Nanoparticles: Absolute Size Distribution Profiles and Structure from AF4-Coupled Light and X‑ray Scattering Measurements

## TL;DR

This paper introduces a new method to assess the quality and structure of mRNA-loaded lipid nanoparticles using advanced scattering techniques.

## Contribution

The study proposes model-free algorithms for analyzing scattering data to obtain size and structural information of lipid nanoparticles.

## Key findings

- The method provides absolute size distribution profiles of lipid nanoparticles.
- It offers detailed insights into the internal structure and quality attributes of nanoparticles.
- The approach is suitable for standardized quality control and comparability assessments.

## 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.