Characterization - Lipid Nanoparticles: Production, Characterization and Stability - page 45

of the width of the particle size distribution, from the autocorrelation function
(Koppel 1972 ). Particle sizes of lipid nanoparticles are often reported using effec-
tive diameter and PI values. These parameters are quite robust and are appropriate
for characterizing lipid nanoparticle dispersions. High PI values preclude evoca-
tive interpretations of the results based on the method of cumulants. The lower
the PI, the more monodisperse the suspension. Most researchers recognize PI val-
ues below 0.3 as optimum values; however, values below 0.5 have sometimes been
deemed acceptable (Kaur et al. 2008 ).
Although PCS is the most widely accepted method, it is (like most particle siz-
ing techniques) an indirect method of determination of particle size. PCS is used
to characterize particle size depending on its translational diffusion coefficient D .
A mathematical model based on the Stokes-Einstein equation ( 4.1 ) is used to con-
vert the translational diffusion coefficient into hydrodynamic diameter to deter-
mine the particle size,

kT
3 πη d

D =

(4.1)

where D is the particle diffusion coefficient, k is the Boltzmann constant, T is
the absolute temperature, η is the viscosity of the dispersion medium and d is the
diameter of the particle. Particle size determination requires knowledge of the
temperature and viscosity of the dispersion medium during measurement.
Although PCS is a simple, robust and reliable technique for characterizing
particles having a narrow and monomodal size distribution pattern in nanometer
range, it is less useful for dispersions with broad or multimodal size distributions.
PCS is not an optimal method when dispersions contain a large portion of parti-
cles in the upper-nanometer or micrometer size ranges. The presence of large par-
ticles or aggregates may have a significant impact on particle size measurements.
The lipid nanoparticle dispersions are often diluted to reduce multiple scattering
effects. It should be noted here that dilution of formulations may alter the size dis-
tribution, thus resulting the classic problem of changing the measure by the act of
measuring it.
Another disadvantage of this technique is the assumption that all particles are
spherical. This assumption is less of a concern for SLNs than for other colloidal
structures, however it can still be an issue, for example if SLNs crystallize into a
platelet-like arrangement (Esposito et al. 2008 , 2012 ). Such anisometric particles
exhibit larger hydrodynamic diameter in PCS as compared to corresponding emul-
sions. Although crystallization leads to volume reduction of particles, anisometric
particles have larger particle diffusion coefficients (Westesen et al. 2001 ). Larger
particle diffusions may influence the determination of particle sizes.
PCS has been used by a number of researchers to measure particle size of lipid
nanoparticles. Tsai et al. ( 2012 ) have reported sizes below 100 nm. Lipid nano-
particles of sizes between 100 and 200 nm have been reported by a few research-
ers (Gupta and Vyas 2012 ; Noack et al. 2012 ; Priano et al. 2011 ; Varshosaz
et al. 2012 ). Others have reported SLNs with sizes varying from 200 to above
500 nm (de Souza et al. 2012 ; Jia et al. 2012 ; Xie et al. 2011 ; Yang et al. 2013 ).