In today’s industrial platform processes, ion exchange chromatography (IEX) is frequently used as a polishing step for the removal of product-related impurities and host cell proteins. The usage of modern chromatography resins tailored for antibody polishing often leads to a separation of charge variants. For industrial process development, this is both an opportunity and a challenge. While the adjustment of the charge variant pattern becomes possible, the development of a robust purification can be challenging.<br/>Mechanistic chromatography modelling is an efficient way of developing and improving complex separation routes in the pharmaceutical industry. In this work it is used to quantify the robustness of a pH-sensitive chromatography step used to reduce the percentage of a basic charge variant in the product pool. A total of six model calibration experiments including both linear gradient and step elution conditions were found to be sufficient for the purpose of design space characterization with a colloidal particle adsorption model.<br/>The model predictions were verified by comparing with an independently generated set of experiments planned using Design-of-Experiments (DoE). Both, the mechanistic model and DoE identified the pH as a critical parameter impacting charge variant separation. An extended simulation study showed that the reduction of the basic charge variant is best achieved at low column load density and lower pH values. However, the product yield benefits from the opposite conditions. The decisive factor for process development, however, is the fulfillment of the robustness criteria, which is better achievable at an increased pH according to the model.<br/>In summary, this comparison of in-silico and experimental process characterization showed that the modeling approach succeeded in describing the non-linear quality attributes’ dependency on process conditions. The model created from only six calibration runs allowed to generate a deep process understanding and to efficiently assess the process robustness under varying conditions.

Model-based analysis of antibody charge variant separation using cation exchange chromatography

ACS Spring 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.