Liposomes and lipid nanoparticles are often used as nanocarriers to encapsulate fragile nucleic acids and hydrophobic or highly toxic drugs, and to safely deliver them to target tissue. During drug nanocarrier product and process development, as well as quality control, it is of great importance to monitor liposome size distributions accurately while also verifying drug encapsulation. FFF-MALS-DLS, consisting of field-flow fractionation (FFF) combined with multi-angle light scattering (MALS) and dynamic light scattering (DLS), is a powerful tool for characterizing the size, concentration, and structure of large nanoparticle ensembles.
Encapsulation might cause changes in liposomal dimensions, but that is not always the case and other effects could cause such changes. Therefore, a more sophisticated analysis is warranted than mere size. Here, we report the analyses of two liposome samples, one empty and one filled with drug, by means of an EclipseTM FFF system followed by a DAWN® MALS detector with embedded WyattQELSTM DLS module. The FFF separation method was optimized with the aid of Wyatt’s proprietary FFF simulation software. ASTRA software was used to collect and analyze the light scattering data to determine size and concentration (number density).
FFF separates particles according to hydrodynamic radius. Thanks to upstream separation, quantitative size distributions by FFF-MALS-DLS provide far more resolution and quantification than batch (unfractionated) DLS. Online DLS directly measures the hydrodynamic radius, Rh, sequentially for each eluting size fraction, while MALS simultaneously measures the root-mean square radius, Rg. The shape factor ρ, which is defined as the ratio Rg:Rh, provides important structural information: it can discriminate between empty and filled shells or quantify the axial ratio of a uniform ellipsoid.
Both Rg and Rh are plotted against elution time in Figure 1. The results from duplicate runs demonstrate clean separation and excellent reproducibility of the FFF-MALS-DLS method. Figure 1(a) shows that the Rh values for both empty and filled liposomes are well-overlaid, which is expected since FFF separates according to hydrodynamic size. However, as shown in Figure 1(b), Rg values for these two liposomes do not overlay, which indicates different internal structures.
Figure 2(a) plots Rg against Rh; ρ is the slope of the linear fit. Interpretation of ρ requires an assumption about the shape of the particles; here we make use of a priori knowledge that they are spherical. The values of ρ for these two populations then correlate precisely to empty and filled liposomal structures.
In addition to size and structure, FFF-MALS can determine quantitative size distributions (number density vs. size) of size-fractionated nanoparticles if the refractive index of the constituent material is known. For lipids this is quite straightforward and Figure 2(b) provides the quantitative nanoparticle concentration analysis.
For liposomes or other nanoparticles, FFF-MALS-QELS provides an easily adaptable yet powerful characterization tool to obtain information on particle size, size distribution, particle count, as well as structure—all without making assumptions about the particles or their composition. FFF-MALS-DLS instrumentation is essential for robust drug nanocarrier development and quality control.
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