A Robust Workflow for Biosimilar Comparability Assessment via Intact and Subunit RPLC-MS and Native IEX-MS with the Xevo G3 QTof MS Platform
Applications | 2022 | WatersInstrumentation
Comprehensive comparison of innovator and biosimilar monoclonal antibodies (mAbs) is critical for regulatory approval and quality assurance. Characterizing glycoforms and charge variants at intact and subunit levels ensures that structural and post-translational modifications fall within acceptable similarity thresholds, safeguarding efficacy and safety in therapeutic applications.
This study aimed to establish a robust, streamlined workflow for biosimilar comparability assessment of infliximab (Remicade®) and three biosimilars (Inflectra®, Avsola®, Renflexis®). Key goals included:
Analyses were performed in triplicate at intact and subunit levels. Experimental design:
Intact RPLC-MS profiles revealed distinct mass shifts corresponding to N-glycoform variants and C-terminal lysine truncation. Mirror plots of deconvoluted spectra enabled confident assignment of major glycoforms (FA2/FA2G1, FA2G1/FA2G2) and minor forms down to 5% relative abundance. Native IEX-MS separated charge variants, confirming three C-terminal lysine species in Remicade and biosimilars through MaxEnt1 deconvolution and post-treatment with carboxypeptidase B.
Subunit RPLC-MS provided enhanced sensitivity, quantifying Fc N-glycoforms at ~1% levels and detecting immunogenic glycans (NeuGc, α-Gal). IEX-MS subunit analysis of (Fd+LC)2 fragments distinguished acidic species consistent with deamidation or conformational variants, supporting intact findings.
The combined intact and subunit workflows offer:
Advances may include integration of higher-resolution instruments, automated data interpretation with machine learning, and expansion to real-time release testing. Further, application to other therapeutic proteins and multi-attribute methods will enhance throughput and confidence in biotherapeutic comparability assessments.
The Xevo G3 QTof-based RPLC-MS and IEX-MS workflows successfully characterized key structural attributes of infliximab and its biosimilars, detecting glycoform and charge variant differences at low abundance. The approach supports robust comparability assessment, meeting regulatory expectations for biosimilarity evaluation.
No formal references were provided in the source document, beyond trademark acknowledgments for Waters and biopharma products.
LC/TOF, LC/HRMS, LC/MS, LC/MS/MS
IndustriesPharma & Biopharma
ManufacturerWaters
Summary
Significance of the Topic
Comprehensive comparison of innovator and biosimilar monoclonal antibodies (mAbs) is critical for regulatory approval and quality assurance. Characterizing glycoforms and charge variants at intact and subunit levels ensures that structural and post-translational modifications fall within acceptable similarity thresholds, safeguarding efficacy and safety in therapeutic applications.
Objectives and Study Overview
This study aimed to establish a robust, streamlined workflow for biosimilar comparability assessment of infliximab (Remicade®) and three biosimilars (Inflectra®, Avsola®, Renflexis®). Key goals included:
- Developing denatured reversed-phase LC-MS (RPLC-MS) and native ion exchange LC-MS (IEX-MS) assays on the Xevo G3 QTof platform
- Comparing intact mAb and IdeS-digested subunit profiles for N-glycoforms and C-terminal lysine variants
- Demonstrating confident assignment at low abundance levels (<5% for intact, ~1% for subunit)
Methodology and Instrumentation
Analyses were performed in triplicate at intact and subunit levels. Experimental design:
- Sample preparation: Denatured intact mAbs and IdeS digests yielding (Fc)2 and (Fd+LC) subunits
- RPLC conditions: ACQUITY Premier BEH C4 column with inline UV 280 nm detection
- IEX conditions: BioResolve SCX mAb column under native buffer conditions
- Mass spectrometry: Waters Xevo G3 QTof platform controlled via UNIFI software and waters_connect informatics
- Data processing: UNIFI applications for INTACT and UNIFI for subunit quantitation and deconvolution (MaxEnt1)
Main Results and Discussion
Intact RPLC-MS profiles revealed distinct mass shifts corresponding to N-glycoform variants and C-terminal lysine truncation. Mirror plots of deconvoluted spectra enabled confident assignment of major glycoforms (FA2/FA2G1, FA2G1/FA2G2) and minor forms down to 5% relative abundance. Native IEX-MS separated charge variants, confirming three C-terminal lysine species in Remicade and biosimilars through MaxEnt1 deconvolution and post-treatment with carboxypeptidase B.
Subunit RPLC-MS provided enhanced sensitivity, quantifying Fc N-glycoforms at ~1% levels and detecting immunogenic glycans (NeuGc, α-Gal). IEX-MS subunit analysis of (Fd+LC)2 fragments distinguished acidic species consistent with deamidation or conformational variants, supporting intact findings.
Benefits and Practical Applications
The combined intact and subunit workflows offer:
- High sensitivity and resolution for minor variant detection
- Streamlined data acquisition and processing via a unified informatics platform
- Applicable comparability strategy for regulatory submissions and quality control in biopharmaceutical development
Future Trends and Opportunities
Advances may include integration of higher-resolution instruments, automated data interpretation with machine learning, and expansion to real-time release testing. Further, application to other therapeutic proteins and multi-attribute methods will enhance throughput and confidence in biotherapeutic comparability assessments.
Conclusion
The Xevo G3 QTof-based RPLC-MS and IEX-MS workflows successfully characterized key structural attributes of infliximab and its biosimilars, detecting glycoform and charge variant differences at low abundance. The approach supports robust comparability assessment, meeting regulatory expectations for biosimilarity evaluation.
References
No formal references were provided in the source document, beyond trademark acknowledgments for Waters and biopharma products.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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