High-Throughput Screening and Analysis of Charge Variants of Monoclonal Antibodies in Multiple Formulations. (September 2017)

• Record Type: Journal Article
• Authors: Alekseychyk, Larysa; Su, Cheng; Becker, Gerald W.; Treuheit, Michael J.; Razinkov, Vladimir I.
• Is Part Of: SLAS discovery. Volume 22:Number 8(2017)
• Page Start: 1044
• Page End: 1052
• Publication Date: 2017-09
• Subjects: monoclonal antibody -- cation exchange chromatography -- predictive stability models -- high-throughput formulation screening; Drugs -- Analysis -- Periodicals; Drugs -- Testing -- Periodicals; Biomolecules -- Analysis -- Periodicals; Biomolecules -- Analysis; Drugs -- Analysis; Drugs -- Testing; Drug Evaluation, Preclinical; Molecular Biology -- methods; Periodicals; Periodicals; 615.1
• DOI: 10.1177/2472555217711666
• Languages: English
• ISSNs: 2472-5552

Abstract

Among different biopharmaceutical products, monoclonal antibodies (mAbs) show a high level of complexity, including heterogeneity due to differences in size, hydrophobicity, charge, and so forth. Such heterogeneity can be related to both cell-based production and any of the stages of purification, storage, and delivery that the mAb is subjected to. Choosing the right formulation composition providing both physical and chemical stabilities can be a very challenging process, especially when done in the limited time frame required for a typical drug development cycle. Charge variants, a common type of heterogeneity for mAbs, are easy to detect by ion exchange, specifically cation exchange chromatography (CEX). We have developed and implemented a high-throughput CEX-based approach for the rapid screening and analysis of charge modifications in multiple formulation conditions. In this work, 96 different formulations of antistreptavidin IgG1 and IgG2 molecules were automatically prepared and analyzed after incubation at high temperature. Design of experiment and statistical analysis tools have been utilized to determine the major formulation factors responsible for chemical stability of antibodies. Regression models were constructed to find the optimal formulation conditions. The methodology can be applied to different stages of preformulation and formulation development of mAbs.