Recombinant humanized proteins provide unique and critical therapies for debilitating diseases such as anemia, diabetes, and many forms of cancer. However, aggregation of therapeutic proteins in otherwise valuable products can severely reduce efficacy and potentially cause immune reactions in patients. Because therapeutic protein aggregates can be immunogenic, protein-based pharmaceutical products must contain acceptably low aggregate levels for the extent of their shelf lives and in-use periods. This requirement implies a need for sensitive, convenient, and reliable analytical tools for detection, quantitation, and analysis of protein aggregates.

A central objective of this dissertation is to evaluate limitations of commonly used analytical techniques for aggregate detection, quantitation, and analysis. We seek to demonstrate the importance of accurately measuring trace aggregate populations in relevant formulation, using recombinant humanized therapeutic monoclonal antibodies to analyze aggregate size and shape distribution.

We investigate disparity in monoclonal antibody aggregate quantitation by size exclusion chromatography (SEC), field flow fractionation (FFF), and sedimentation velocity (SV). We present an aggregation model, based on end-to-end monomer assembly, consistent with SV, SEC, FFF, and dynamic light scattering results. This aggregation model accounts for observed quantitation limitations in aggregate analysis techniques.

SV limits of quantitation (LOQ) of protein oligomers depend on diverse factors (molecule, instrument, and numerical analysis software). We examine the performance of SEDFIT/c(s) data analysis software with simulated antibody monomer/dimer and monomer/tetramer systems. Diminished quantitation accuracy at low oligomer levels is not accompanied by deterioration of fit quality. Because protein pharmaceuticals typically contain sugars as stabilizers, we extend analysis to sugar-containing formulations. The LOQ of simulated monoclonal antibody dimer increases threefold upon addition of 5% sugar to the formulation.

We explore sophisticated data analysis techniques to mitigate detection problems caused by sugars in product formulation. Finally, we characterize systems of monoclonal antibody, silicone oil, sucrose and surfactants. Due to increased rates of silicone oil coalescence, oil induced monoclonal antibody aggregation is reduced in formulations containing sucrose. Aggregation is further reduced in formulations containing both sucrose and a non-ionic surfactant. These additives, commonly used as stabilizers against physical stresses, may prevent protein aggregation and reduce protein exposure to silicone oil surfaces.