TECHNICAL NOTE
Analyze self-interaction to predict viscosity and
aggregation propensity at higher concentrations
Introduction
During early discovery and optimization stages of biologic development, various
biophysical parameters help researchers determine the optimal therapeutic candidate
and formulation. Many experiments and assays for these parameters have low sample
consumption and low concentration requirements, which helps biologics researchers get
the most out of limited product prior to scale-up. However, once a therapeutic reaches
the clinic, it is o en administered at high concentrations compared to those used in the
development stages, which o en provides challenges with viscosity and aggregation that
are overlooked in early-phase workflows.
To overcome these challenges, researchers measure the self-interaction propensity
of their candidates. The self-interaction or diffusion-interaction parameter k
D
is
determined from dynamic light scattering (DLS) experiments. DLS uses light scattered
from particles to measure a diffusion coefficient (D). In turn, this value is typically used for
determining the hydrodynamic radius (r
H
), or size, of particles in solution, as well as the
distribution of particle sizes in a sample (PDI)1.
The k
D
parameter defines the first-order
dependence of D on the concentration of the protein.
As the concentration changes, the interaction between particles impacts how they behave
in solution. These changes are reflected in D, which can be plotted against concentration
to give the dependence. Attraction between molecules slows down diffusion, and
therefore results in a lower value for D; repulsion between molecules increases its value.
Philipp Schramm, Silvia Würtenberger, Christian Kleusch, Stefanie Kall
NanoTemper Technologies GmbH, Munich, Germany
