New publication
May 20, 2024

There have been extensive efforts both in the academia and industry to optimize RNA lipid nanoparticles (LNP) to make them as uniform as possible. In this context, "uniformity" most of the time refers to "size uniformity", and a uniform preparation is usually characterized by a low polydispersity index (PDI) from dynamic light scattering (DLS) or cryogenic transmission electron microscopy (cryo-TEM).

However, with the rise of our single-nanoparticle profiling technique, cylindrical illumination confocal spectroscopy (CICS) accessing the composition of individual LNPs, we ask a fundamental question with curiosity: Does size uniformity spontaneously mean uniform distribution of payloads (i.e., loading uniformity)?

To answer this question, we coupled the original CICS platform with single-nanoparticle free solution hydrodynamic separation (SN-FSHS) technique, a chromatographical size characterization method. Adding a fourth readout of hydrodynamic size on top of the loading level of three fluorescently tagged LNP components (siRNA payload, helper lipid, and PEG lipid) of a formulation that shares the same composition as the clinically approved drug ONPATTRO, we analyzed the detailed loading-size correlations across a wide size distribution of around 30 to 200 nm. We found that LNPs of like size may have significantly different loading density, which means that loading heterogeneity can co-exist with size uniformity (not so surprisingly!). Through in-depth analyses into the the entire manufacturing process of these RNA LNPs, including the initial complexation at a relatively low pH and the subsequent dialysis towards physiological pH, we concluded that the loading heterogeneity might be a result of intrinsic diffusivity differences between assembly components and kinetics-driven assembly and stabilization during the pH shift. We expect these findings can inspire further discussions and exploration by the LNP community, not only to verify these findings independently, but to think about methods to optimize LNPs for better loading uniformity, which may facilitate a higher efficiency per unit mass of payload on LNPs.

This study was a collaborative effort by teams led by Prof. Hai-Quan Mao and Prof. Tza-huei Wang. We welcomed Prof. Tine Curk from the Department of Materials Science and Engineering of Johns Hopkins University to join the team, who contributed instrumental analyses from a molecular dynamics perspective in understanding the assembly behaviors of RNA LNPs. Our paper describing these findings has now been published with open access and can be accessed by everyone for free: Li and Hu, et al., ACS Nano, 2024.