Enhancing sensitivity and robustness of PS20 quantification in monoclonal antibody formulation using an acclaim surfactant plus column

Polysorbate 20 (PS20) is a commonly used surfactant in biopharmaceutical formulations. In certain liquid formulations, PS20 degradation can be observed when stored at cold or ambient temperature, which can cause the formation and accumulation of free fatty acids and subsequent product aggregation during long term storage. Additionally, polysorbate can be adsorbed by sterile filters, leading to PS20 reduction in the final drug products and posing a risk for formulation robustness and product stability.

The analytical methods commonly used to quantify PS20 content in monoclonal antibody (mAb) samples employ a combination of an Oasis Max column (30 mm, 2.1 X 20 mm) and a Charged Aerosol Detector (CAD) detector. The CAD, being a universal detector, is well suited for quantifying PS20. The mixed mode resin of the Oasis Max column separates mAb and other components in the formulation from the PS20, thus enable the quantitation of PS20 as a single peak.

The Oasis Max column is 20 mm long and was originally intended as a solid phase extraction column for desalting prior to analysis on a separate analytical HPLC column, challenges related to robustness were encountered, including PS20 peak tailing and column-to-column variability.

To address these concerns regarding method robustness, a new method using an analytical HPLC column was developed. Afte screening of greater than 10 different columns, an Acclaim Surfactant Plus column (3 mm, 2.1 X 100 mm) from Thermo Fisher Scientific was selected. This optimized method effectively separates PS20 from other components in mAb samples, with PS20 sub-species eluted out as a single peak for quantification by a CAD detector. The method quantification has been successfully performed. Compared to Water Oasis Max column, the Acclaim Surfactant Plus column offers enhanced sensitivity, improved baseline quality, peak shape, column lifespan, and method robustness. This poster presents the key findings during the method development, optimization, and qualification.