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An Integrated Workflow for Automated Calculation of Antibody‑Drug Conjugate (ADC) Drug‑to-Antibody Ratio (DAR)

Applications | 2016 | Agilent TechnologiesInstrumentation
Software, LC/TOF, LC/HRMS, LC/MS, LC/MS/MS
Industries
Pharma & Biopharma
Manufacturer
Agilent Technologies

Summary

Significance of the Topic


Antibody–drug conjugates (ADCs) represent a critical class of targeted biotherapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic drugs. Precise measurement of the drug-to-antibody ratio (DAR) is essential to ensure therapeutic efficacy, safety, and consistency across production batches.

Objectives and Overview of the Study


This work demonstrates a fully integrated, automated workflow for DAR determination of ADCs. By coupling automated sample preparation on the Agilent AssayMAP Bravo with Agilent MassHunter Walkup and BioConfirm DAR Calculator software, the method aims to reduce hands-on time, minimize variability, and enable non-expert users to obtain reliable DAR values.

Methodology and Instrumentation


The workflow encompasses:
  • Automated in-solution reduction and deglycosylation using the Agilent AssayMAP Bravo Platform.
  • LC/TOF-MS analysis on an Agilent 1290 Infinity II UHPLC system coupled to a 6230 Accurate-Mass TOF with Dual Jet Stream ESI.
  • Sample submission and data acquisition via Agilent MassHunter Walkup software.
  • Automated deconvolution and DAR calculation in Agilent MassHunter BioConfirm with the DAR Calculator feature.

Main Results and Discussion


Across intact and reduced forms, the automated and manual workflows yielded comparable average DAR values (intact glycosylated ~3.5, reduced glycosylated ~3.2). Deconvoluted spectra revealed well-defined peak clusters (D0–D8 for intact, D0–D4 for reduced samples). Automation improved peak intensities, eliminated manual pipetting errors, and provided consistent DAR determination over multiple replicates.

Benefits and Practical Applications


The integrated solution streamlines ADC characterization by reducing operator dependency, enhancing throughput, and ensuring reproducible results. Laboratories can implement DAR analysis in routine QC, R&D workflows, and regulatory submissions without requiring in-depth LC/MS expertise.

Future Trends and Opportunities


Advancements may include AI-driven data analysis for peak assignment, seamless integration with laboratory information management systems (LIMS), and extension of the automated platform to other biotherapeutic modalities. High-throughput scaling and real-time process monitoring represent promising directions.

Conclusion


This automated ADC DAR workflow combines Agilent AssayMAP Bravo sample preparation, MassHunter Walkup acquisition, and BioConfirm DAR calculation to deliver accurate, reproducible DAR measurements with minimal hands-on effort, supporting efficient biotherapeutic development and quality control.

References


  1. Perez HL, et al. Antibody-drug conjugates: current status and future directions. Drug Discovery Today. 2014;19(7):869–81.
  2. Xu K, et al. Characterization of the drug-to-antibody ratio distribution for antibody–drug conjugates in plasma/serum. Bioanalysis. 2013;5(9):1057–1071.
  3. Beck A, et al. Cutting-edge mass spectrometry methods for the multi-level structural characterization of antibody-drug conjugates. Expert Rev Proteomics. 2016;13(2):157–183.

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