Lipid nanoparticles (LNPs) performance depends not only on formulation, but on the physical particle population that forms during synthesis. At ATEM, we examined how size, roundness and solid-core fraction relate to encapsulation and in vivo expression, based on our internal case studies.
A lipid nanoparticle (LNP) is a lipid-based carrier used to encapsulate and transport therapeutic cargo, including nucleic acids such as mRNA or siRNA. Its purpose is to package and safely deliver that payload into cells [1]. But how well LNPs perform the encapsulation and delivery depends on the structure of the particle that is actually formed – including its size, shape, and internal organization – not just the lipid ratios and process used to make it [1,2]. Yet, these structural features are not captured by many routine characterization methods. Dynamic light scattering (or DLS), for example, measures hydrodynamic particle size but cannot directly resolve particle shape or internal architecture [3]. This leaves a gap between routinely collected measurements and the underlying particle structural features that may be more closely linked to LNP performance. In this article, we examine three structural characteristics – size, shape and solid-core fraction – and how they relate to encapsulation and in-vivo performance, based on data from our internal case studies.
To define what an “optimal” LNP looks like structurally, we focused on three measurements that can be resolved directly by cryo-EM: particle size, roundness and solid-core fraction. Size captures the lipid nanoparticle’s diameter, roundness describes how closely its cross-section approaches a perfect circle, and solid-core fraction reflects the proportion of particles with a single, relatively uniform central density rather than split or blebbed structures (distinct internal compartments) [2].
In an internal case study analyzing 21 formulations, smaller LNP populations showed high encapsulation efficiency (EE), with all observations in the smaller-size range falling around 80-100% EE. As mean particle diameter increased, encapsulation became more variable. Roundness showed a similar pattern, with more circular LNP populations clustering at high EE [4].
Solid-core fraction added another structural dimension. In a separate comparison of two mixing technologies, one population was smaller and rounder and contained a higher proportion of solid-sore particles. That same population showed consistently high encapsulation around 90-100% versus 55-80% in the other group [4].
Particle size and roundness were strongly anticorrelated, and encapsulation could not be attributed to any one structural measurement alone [4]. Together, the studies suggest that better-performing LNP populations tend to be smaller, rounder and richer in solid-core particles.
When LNPs were deliberately stressed, the particles became larger, less round and less solid-core-rich, while encapsulation declined at the same time. In a graded freeze-thaw experiment, mean diameter increased from 45 to 65nm and solid-core fraction fell from 93% to 60% [4]. The changes in structure and encapsulation did not occur in a fixed proportion, however, showing that structural measurements cannot substitute for functional testing.
A similar distinction applies in vivo. The two mixing-technology populations, produced with identical lipids, buffer and mRNA, differed by 2.57-fold in total expression. Structural models also showed some relationship with organ uptake, but only in three of seven organs and not in a consistent direction [4]. This suggests that particle structure contributes to biological performance, but does not determine it on its own [5,6].
A recurring structural pattern emerges from these studies. Better-performing LNP populations tend to be smaller, rounder, and richer in solid-core particles, but no single measurement defines performance on its own. Cryo-EM adds structural context to functional testing by showing how differences between formulations relate to their performance.
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