Application of FT-IR Spectroscopy as a Non-Invasive Multi-Attribute Monitoring Platform for Critical Quality Attributes in Monoclonal Antibodies

Abstract

Monoclonal antibodies (mAbs) are a major class of biopharmaceuticals widely used to treat cancers, inflammatory, infectious, and autoimmune diseases. The manufacturing of these therapeutics involves multiple complex and time-consuming steps that may introduce product-and process-related impurities and cause alterations in critical quality attributes (CQAs). Such changes can affect the structural integrity, stability, pharmacokinetics, and pharmacodynamics of monoclonal antibodies. Conventional analytical techniques used to monitor impurities and CQAs in protein therapeutics are effective but often labour-intensive, time-consuming, and costly, highlighting the need for rapid and integrated analytical approaches. This study investigates the feasibility of Fourier transform infrared (FT-IR) spectroscopy as a rapid, non-invasive, and costeffective multi-attribute monitoring strategy for assessing CQAs, including aggregation, oxidation, deamidation, and glycation. Characteristic FT-IR spectral regions in stressed and non-stressed monoclonal antibody samples were analyzed using multivariate statistical tools. Liquid chromatography-mass spectrometry (LC-MS), including top-down and bottom-up approaches, confirmed the post-translational modifications (PTMs) detected by FT-IR spectroscopy. Circular dichroism (CD) spectroscopy revealed a decrease in α-helical content and an increase in β-sheet structures in stressed samples, indicating stress-induced structural changes. Complementary analyses using size-exclusion chromatography-high-performance liquid chromatography (SEC-HPLC), dynamic light scattering (DLS), and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) further confirmed the presence of aggregates and fragments. Overall, these findings highlight the potential of FT-IR spectroscopy for rapid monitoring of biotherapeutic structural integrity and quality attributes.