Density Matching Multi-wavelength Analytical Ultracentrifugation to Measure Drug Loading of Lipid Nanoparticle Formulations.
ACS Nano
; 15(3): 5068-5076, 2021 03 23.
Article
en En
| MEDLINE
| ID: mdl-33617224
Previous work suggested that lipid nanoparticle (LNP) formulations, encapsulating nucleic acids, display electron-dense morphology when examined by cryogenic-transmission electron microscopy (cryo-TEM). Critically, the employed cryo-TEM method cannot differentiate between loaded and empty LNP formulations. Clinically relevant formulations contain high lipid-to-nucleic acid ratios (10-25 (w/w)), and for systems that contain mRNA or DNA, it is anticipated that a substantial fraction of the LNP population does not contain a payload. Here, we present a method based on the global analysis of multi-wavelength sedimentation velocity analytical ultracentrifugation, using density matching with heavy water, that not only measures the standard sedimentation and diffusion coefficient distributions of LNP mixtures, but also reports the corresponding partial specific volume distributions and optically separates signal contributions from nucleic acid cargo and lipid shell. This makes it possible to reliably predict molar mass and anisotropy distributions, in particular, for systems that are heterogeneous in partial specific volume and have low to intermediate densities. Our method makes it possible to unambiguously measure the density of nanoparticles and is motivated by the need to characterize the extent to which lipid nanoparticles are loaded with nucleic acid cargoes. Since the densities of nucleic acids and lipids substantially differ, the measured density is directly proportional to the loading of nanoparticles. Hence, different loading levels will produce particles with variable density and partial specific volume. An UltraScan software module was developed to implement this approach for routine analysis.
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Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Preparaciones Farmacéuticas
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Ácidos Nucleicos
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Nanopartículas
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
ACS Nano
Año:
2021
Tipo del documento:
Article