High-sensitive multi-attribute analysis of ADCs under native conditions by using an online multiple heart-cut 2D-LC-HRAM mass spectrometry system

Importance of the Topic

Antibody drug conjugates (ADCs) have emerged as a critical class of targeted cancer therapies. Detailed characterization of their key quality attributes such as charge variant profile, drug to antibody ratio (DAR) and drug load distribution (DLD) is essential to ensure product safety, stability and efficacy. Conventional single-dimension chromatography often relies on non-MS compatible buffers and fails to capture multiple attributes in a single run under native conditions.

Objectives and Study Overview

This study introduces a high sensitivity multi-attribute analysis workflow for cysteine-linked ADCs using an online multiple heart-cut two-dimensional liquid chromatography high resolution accurate mass spectrometry (2D-LC-HRAM MS) setup. Polatuzumab vedotin was selected as a model ADC to demonstrate simultaneous assessment of charge heterogeneity, DAR and DLD under native conditions.

Methodology and Instrumentation

An online multiple heart-cut 2D-LC-HRAM MS system was configured to perform sequential fraction transfers from strong cation exchange (SCX) or hydrophobic interaction chromatography (HIC) into size exclusion chromatography (SEC) for desalting before MS detection. Five 250 µL fractionation loops and a backflush transfer scheme minimized band broadening. Native HIC-SEC and SCX-SEC methods were optimized to separate charge variants, positional isomers and DAR species while preserving the intact ADC structure.

Instrumentation

• Thermo Scientific Vanquish 2D UHPLC system
• Thermo Scientific Orbitrap Exploris 240 mass spectrometer with Biopharma Option
• Columns: ProPac SCX (100×4 mm, 3 µm), MAbPac HIC-Butyl (100×4.6 mm, 5 µm), MabPac SEC-1 (300×4 mm, 5 µm)
• Software: Chromeleon CDS 5.3.2, BioPharma Finder 5.3

Main Results and Discussion

Using the high resolution Orbitrap MS, 18 charge variants including acidic forms from deamidation and oxidation, and basic forms from lysine truncation were resolved by SCX. HIC separated twelve peaks corresponding to DAR0 through DAR8 species. Principal glycoforms for each main DAR peak were confirmed by deconvoluted mass spectra with mass errors below 1 ppm. Low-abundance species such as odd-number DAR isomers and linker-only variants down to 0.4 % relative area were detected with strong signal-to-noise ratios. Lysine truncation (mass shift +128 Da) and other post-translational modifications were mapped across the chromatographic peaks.

Benefits and Practical Applications

• Comprehensive multi-attribute profiling in a single native-mode workflow
• Removal of non-MS compatible salts via online desalting in SEC
• High sensitivity detection of minor variants for stringent quality control
• Improved peak shape and transfer efficiency through backflush loop design

Future Trends and Opportunities

Integration of automated fraction selection and data processing could further streamline multi-attribute analysis of ADCs and related bioconjugates. Development of faster column chemistries, miniaturized 2D-LC formats and advanced data analytics including machine learning may enhance throughput and depth of characterization. Extending this approach to other biotherapeutic modalities holds promise for robust quality assessment in drug development and manufacturing.

Conclusion

An online multiple heart-cut 2D-LC-HRAM MS platform has been successfully developed for native-condition profiling of polatuzumab vedotin. This approach delivers high sensitivity and comprehensive insight into charge heterogeneity, DAR distribution and glycoform patterns, offering a powerful tool for ADC characterization and quality control.

References

• Bobály B, Fleury-Souverain S, Beck A, Veuthey JL, Guillarme D, Fekete S Current possibilities of liquid chromatography for the characterization of antibody-drug conjugates. Journal of Pharmaceutical and Biomedical Analysis 147 493-505 (2018)
• Deeks ED Polatuzumab vedotin: first global approval. Drugs 79(13) 1467-1475 (2019)