Fc galactosylation is a critical quality attribute for anti-tumor recombinant immunoglobulin G (IgG)-based monoclonal antibody (mAb) therapeutics with complement-dependent cytotoxicity (CDC) as the mechanism of action. Although the correlation between galactosylation and CDC has been known, the underlying structure–function relationship is unclear. Heterogeneity of the Fc N-glycosylation produced by Chinese hamster ovary (CHO) cell culture biomanufacturing process leads to variable CDC potency. Here, we derived a kinetic model of galactose transfer reaction in the Golgi apparatus and used this model to determine the correlation between differently galactosylated species from CHO cell culture process. The model was validated by a retrospective data analysis of more than 800 historical samples from small-scale and large-scale CHO cell cultures. Furthermore, using various analytical technologies, we discovered the molecular basis for Fc glycan terminal galactosylation changing the three-dimensional conformation of the Fc, which facilitates the IgG1 hexamerization, thus enhancing C1q avidity and subsequent complement activation. Our study offers insight into the formation of galactosylated species, as well as a novel three-dimensional understanding of the structure–function relationship of terminal galactose to complement activation in mAb therapeutics.

Heterogeneity of therapeutic Monoclonal antibody (mAb) drugs are due to protein variants generated during the manufacturing process. These protein variants can be critical quality attributes (CQAs) depending on their potential impact on drug safety and/or efficacy. To identify CQAs and ensure the drug product qualities, a thorough characterization is required but challenging due to the complex structure of biotherapeutics. Past characterization studies for basic and acidic variants revealed that full characterizations were limited to the basic charge variants, while the quantitative measurements of acidic variants left gaps. Consequently, the characterization and quantitation of acidic variants are more challenging. A case study of a therapeutic mAb1 accounted for two-thirds of the enriched acidic variants in the initial characterization study. This led to additional investigations, closing the quantification gaps of mAb1 acidic variants. This work demonstrates that a well-designed study with the right choices of analytical methods can play a key role in characterization studies. Thus, the updated strategies for more complete antibody charge variant characterization are recommended.

Hydrophobic interaction chromatography (HIC) is commonly used to determine the drug-to-antibody ratio (DAR) and drug load distribution of antibody-drug conjugates (ADCs). However, identifying various DAR species separated by HIC is challenging due to the traditional use of mobile phases that are incompatible with mass spectrometry (MS). Existing approaches used to couple HIC with MS often encounter issues, such as complex instrumentation, compromised separation efficiency, and reduced MS sensitivity. In this study, we introduce a 22-min online native HIC-MS method for the separation and characterization of different DAR species in ADCs, addressing these challenges. The key novelty of this method is the use of ammonium tartrate, a kosmotropic and thermally decomposable salt, as the salt of HIC mobile phase, ensuring both excellent HIC separation and MS compatibility. Additionally, an ultrashort size exclusion chromatography step is integrated for online sample cleaning, enhancing MS sensitivity. This platform native HIC-MS method offers a rapid, sensitive, and robust solution for comprehensive profiling of DAR species in ADCs with a simple and cost-effective instrumental setup.

Large molecule protein therapeutics have steadily grown and now represent a significant portion of the overall pharmaceutical market. These complex therapies are commonly manufactured using cell culture technology. Sequence variants (SVs) are undesired minor variants that may arise from the cell culture biomanufacturing process that can potentially affect the safety and efficacy of a protein therapeutic. SVs have unintended amino acid substitutions and can come from genetic mutations or translation errors. These SVs can either be detected using genetic screening methods or by mass spectrometry (MS). Recent advances in Next-generation Sequencing (NGS) technology have made genetic testing cheaper, faster, and more convenient compared to time-consuming low-resolution tandem MS and Mascot Error Tolerant Search (ETS)-based workflows which often require ~6 to 8 weeks data turnaround time. However, NGS still cannot detect non-genetic derived SVs while MS analysis can do both. Here, we report a highly efficient Sequence Variant Analysis (SVA) workflow using high-resolution MS and tandem mass spectrometry combined with improved software to greatly reduce the time and resource cost associated with MS SVA workflows. Method development was performed to optimize the high-resolution tandem MS and software score cutoff for both SV identification and quantitation. We discovered that a feature of the Fusion Lumos caused significant relative under-quantitation of low-level peptides and turned it off. A comparison of common Orbitrap platforms showed that similar quantitation values were obtained on a spiked-in sample. With this new workflow, the amount of false positive SVs was decreased by up to 93%, and SVA turnaround time by LC-MS/MS was shortened to 2 weeks, comparable to NGS analysis speed and making LC-MS/MS the top choice for SVA workflow.