A careful look at lipid nanoparticle characterization: analysis of benchmark formulations for encapsulation of RNA cargo size gradient

With the recent success of lipid nanoparticle (LNP) based SARS-CoV-2 mRNA vaccines, the potential for RNA therapeutics has gained widespread attention. LNPs are promising non-viral delivery vectors to protect and deliver delicate RNA therapeutics, which are ineffective and susceptible to degradation alone. While food and drug administration (FDA) approved formulations have shown significant promise, benchmark lipid formulations still require optimization and improvement. In addition, the translatability of these formulations for several different RNA cargo sizes has not been compared under the same conditions. Herein we analyze "gold standard" lipid formulations for encapsulation efficiency of various non-specific RNA cargo lengths representing Antisense Oligonucleotides (ASO), small interfering RNA (siRNA), RNA Aptamers, and messenger RNA (mRNA), with lengths of 10 bases, 21 base pairs, 96 bases, 996 bases, and 1929 bases, respectively. We evaluate encapsulation efficiency as the percentage of input RNA encapsulated in the final LNP product (EE_input%), which shows discrepancy with the traditional calculation of encapsulation efficiency (EE%). EE_input% is shown to be < 50% for all formulations tested, when EE% is consistently > 85%. We also compared formulations for LNP size (Z-average) and polydispersity index (PDI). LNP size does not appear to be strongly influenced by cargo size, which is a counterintuitive finding. Thoughtful characterization of LNPs, in parallel with consideration of in vitro or in vivo behavior, will guide design and optimization for better understanding and improvement of future RNA therapeutics.