Interest in lipid nanoparticles (LNPs) as delivery vehicles for precision therapies in genetic diseases and cancers remains at an all-time high. Now, scientists from the University of Pennsylvania, Brookhaven National Laboratory, and Waters have characterized the shape and structure of four LNPs in significant detail. Their work reveals that these particles come in a variety of configurations and that the differences correlate with how well individual particles deliver their therapeutic cargoes.
Full details are available in a new Nature Biotechnology paper titled “Elucidating lipid nanoparticle properties and structure through biophysical analyses.” Commenting on the findings, Kushol Gupta, PhD, one of the senior authors on the paper and a research assistant professor in biochemistry and biophysics at the Perelman School of Medicine at UPenn, noted that “these particles have already proven themselves in the clinic” and that the insights reported in the paper “will make them even more powerful by helping us tailor delivery to specific diseases more quickly.”
In his comments, Michael Mitchell, PhD, an associate professor in bioengineering and a co-senior author of the paper, noted that though “treating LNPs like one model of car has worked, as evidenced by the millions of people these particles have helped,” the particles are “not one-size-fits-all for every RNA therapy.” With the results, “just as pickups, delivery vans, and freight trucks best suit different journeys, we can now begin to match LNP designs to particular therapies and tissues, making these particles even more effective.”
This work builds on findings from studies done in the Mitchell lab and elsewhere that have shown that different LNP formulations have specific biological effects, much like mixing different ingredients changes a recipe. For example, adding phenol groups reduces inflammation while branched ionizable lipids improve delivery. But understanding why certain chemical tweaks lead to particular biological effects has proved challenging. “These particles are something of a ‘black box,’” according to Marshall Padilla, PhD, a bioengineering postdoctoral fellow and first author on the paper. “We’ve had to develop new formulations mostly by trial and error.”
To visualize the particles for this study, the scientists used a range of “dissimilar techniques” that kept the particles intact, Gupta explained. Previous efforts relied on single approaches like freezing particles in place or tagging them with fluorescent materials and taking average measurements, a technique that could alter the particle’s shape and obscure variations. With their approach, “we could be confident that agreement between the methods showed us what the particles really looked like,” Gupta said.
One visualization technique that the scientists used is called sedimentation velocity analytical ultracentrifugation (SV-AUC). It involved spinning the LNPs at high speeds to separate them by density. A second technique, dubbed field-flow fractionation coupled to multi-angle light scattering (FFF-MALS), was used to gently separate the LNPs by size and measure how the nucleic acid was distributed across the different particles. A third technique, size-exclusion chromatography in-line with synchrotron small-angle x-ray scattering (SEC-SAXS), hit the LNPS with powerful x-ray beams, enabling scientists to study their internal structure.
According to the paper, the scientists used these techniques to elucidate the structures of four LNP formulations, including those used in COVID-19 vaccines and Onpattro, an approved therapy for treating polyneuropathy of hereditary transthyretin-mediated amyloidosis (hATTR) in adults, that was developed by Alnylam Pharmaceuticals. The results were illuminating. “We used to think LNPs looked like marbles,” Gupta said. “But they’re actually more like jelly beans, irregular and varied, even within the same formulation.”
After characterizing the LNPs, the scientists tested their effects on a range of targets, including human T cells, cancer cells, and animal models. One of the findings reported in the paper was made by Hannah Yamagata, a doctoral student in the Mitchell Lab, who found that some particles’ internal structures corresponded with improved delivery outcomes. “Interestingly, it varied depending on the context,” Yamagata said. Other results showed that some LNP formulations performed better in immune cells, while others showed greater potency in animal models.
Furthermore, the LNPs’ characteristics and potency varied depending on what methods were used to prepare them. For example, microfluidic devices, which push ingredients through small tubes, led to more consistent shapes and sizes, while mixing by hand using micropipettes resulted in more variation. This was particularly interesting because scientists generally assumed that using microfluidic devices was better, but the data suggest that micropipetting may produce better results, at least in some cases.
The results open the door to a new era of rational LNP design, moving beyond today’s trial-and-error approach. It is possible that in the future, as additional labs generate structure and functional data around LNPs, the field could assemble sufficient datasets to train artificial intelligence models to design more effective LNPs. Ultimately, the findings point toward a future in which nanoparticles can be engineered with the same precision as drugs themselves. “This paper provides a road map for designing LNPs more rationally,” Mitchell said.
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