Deconvoluting sub-populations of vesicles in lipid nanoparticle formulations

Lipid nanoparticles (LNPs) and vesicles are emerging classes of novel therapeutics. However, LNP formulations possess many different internal structures, and particle structure heterogeneity within samples, including sub-populations of vesicles produced as a by-product during formulation. This causes significant challenges when evaluating LNP activity in biological systems, as it is almost impossible to decouple the activity due to the LNP population and the vesicle sub-populations. Also, challenges characterising LNP internal structures in heterogeneous populations mean there is currently very limited ability to determine and apply structure-activity relationships to design new active formulations. Here, we will use SANS to systematically characterise structural variations in LNP and vesicle formulations, and mixtures thereof. Next, we apply this knowledge to characterise vesicle sub-populations natively present in specific LNP formulations. Using asymmetric flow field flow fractionation, we will separate these sub-populations, and study their individual contributions to the full sample. We will combine models we have previously used, and LNP/vesicle starting structures being developed within the ShapeSpyer programe, with which we can simulate scattering curves for pure LNP and vesicle systems and decouple any eventual mixing-mediated changes to the morphologies of particle sub-populations. The data contributes to informed design of LNPs for medical applications.