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Updated: Aug 6, 2026

Formulating and Characterizing Lipid Nanoparticles for Gene Delivery using a Microfluidic Mixing Platform
Published on: February 25, 2021
Resolving Heterogeneity of Targeted Lipid Nanoparticles Through Solution-Based Biophysical Analyses
Hannah C Geisler1, Hannah C Safford1, Ajay S Thatte1
1Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Abstract:
Targeted lipid nanoparticles (tLNPs) enable cell-specific nucleic acid delivery through covalent attachment of targeting ligands that drive receptor-mediated LNP uptake. tLNPs are potentially promising for pregnancy‑associated applications where precise delivery is required to minimize maternal toxicity and protect fetal health. Yet, rational tLNP design is limited by an incomplete understanding of how physicochemical properties influence biological performance. Traditional analytical methods report only ensemble-averaged properties, leaving the nanoscale heterogeneity of tLNPs unresolved. Here, we utilize asymmetric flow field-flow fractionation integrated with in-line UV spectral analysis, light scattering, and synchrotron small-angle X-ray scattering (AF4-UV-DLS-MALS-SAXS) to resolve ligand-dependent tLNP subpopulations that differ in size, shape, composition, and relative abundance. Protein conjugation preserves the internal lipid-RNA nanostructure of base LNPs but substantially increases particle heterogeneity, particularly for larger and multivalent ligands. Despite increased heterogeneity, tLNPs functionalized with higher-avidity ligands achieve more effective targeted placental RNA delivery in mice. Chemometric SAXS analyses reveal that only SAXS-resolved tLNP subpopulations, not ensemble-averaged parameters, correlate with targeted placental transfection in vivo, whereas bulk physicochemical metrics more strongly associate with nonspecific hepatic delivery. Together, this work harnesses a separation-coupled biophysical platform to resolve previously inaccessible tLNP subpopulations and provides insights to inform rational engineering of next-generation targeted RNA therapeutics.
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