Resolving heterogeneity of targeted lipid nanoparticles through solution-based biophysical analyses

Abstract

Targeted lipid nanoparticles (tLNPs) represent the next frontier in nucleic acid therapeutics, enabling cell-specific delivery through covalent attachment of targeting ligands that drive receptor-mediated uptake. tLNPs are particularly promising for pregnancy-associated applications where precise on-target delivery is required to minimize maternal toxicity and protect fetal health. Yet, their rational design is limited by an incomplete understanding of how tLNP physicochemical properties influence biological performance. Conventional LNPs already exhibit pronounced heterogeneity in size, composition, and RNA loading, which is further amplified in tLNPs by variability in ligand attachment and surface density. Because traditional analytical methods report only ensemble-averaged properties, the nanoscale diversity of tLNPs remains unresolved. Here, we find that tLNP functional behavior is governed by previously inaccessible, structurally distinct tLNP subpopulations that are not captured by bulk measurements. 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. We find that protein conjugation preserves the internal lipid-RNA nanostructure of base LNPs but substantially increases particle heterogeneity, particularly for larger and multivalent targeting ligands. Despite increased heterogeneity, tLNPs functionalized with higher-avidity ligands achieve more effective targeted placental RNA delivery in mice, suggesting that binding avidity can offset the functional consequences of polydispersity. Chemometric SAXS analyses reveal that only SAXS-resolved tLNP subpopulations, not ensemble-averaged parameters, correlate with targeted placental transfection in vivo, whereas bulk-derived 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 demonstrates that subpopulation nanoscale structure, rather than bulk-averaged properties, dictates targeted RNA delivery. These insights provide a mechanistic foundation for rational engineering of next-generation precision targeted RNA LNP therapeutics.