Developing a Quantitative Surrogate Peptide Assay – Peptide mapping through MRM Optimization for Measuring Dulaglutide in a Rat PK Study

Importance of the Topic

Fusion protein therapeutics such as dulaglutide represent a growing class of biopharmaceuticals with complex structures and pharmacokinetics. Robust, rapid LC-MS/MS workflows are essential to enable quantification of these large molecules in biological matrices and to support pharmacokinetic (PK) studies, quality control, and drug development.

Objectives and Study Overview

This work outlines a universal assay development strategy for Fc-containing fusion proteins, demonstrated by the quantitative analysis of dulaglutide in rat plasma. Key goals included peptide mapping for surrogate peptide selection, automated multiple reaction monitoring (MRM) optimization, development of a sensitive sample preparation protocol, and application of the assay to a preclinical PK study, achieving a lower limit of quantification (LLOQ) of 1 ng/mL.

Methodology and Used Instrumentation

Sample Preparation:

• Denaturation with RapiGest SF, reduction with dithiothreitol, alkylation with iodoacetamide.
• Trypsin digestion (1:10 enzyme:protein) using ProteinWorks Auto eXpress Low Volume protocol.
• Immunoaffinity capture and solid-phase extraction for rat plasma samples (detailed in companion note 720006823EN).

Peptide Mapping and Quantification:

• UPLC separation on ACQUITY UPLC I-Class PLUS with Peptide BEH C18 column.
• High-resolution MS detection on Xevo G2-XS QTof for peptide mapping (ESI+).
• MRM transition selection and collision energy optimization via MassLynx Skyline Interface on Xevo TQ-XS triple quadrupole.

Main Results and Discussion

Peptide mapping delivered 93 % sequence coverage of dulaglutide and identified 15 tryptic peptides (6–33 amino acids), from which seven candidates (8–25 residues) were filtered based on modification levels and uniqueness. Automated MRM optimization using the Skyline interface streamlined precursor and product ion selection, collision energy ramping, retention time scheduling, and method export.

In the rat PK study, two surrogate peptides were monitored: HGEGTFTSDVSSYLEEQAAK (GLP-1 region) and GLPSSIEK (Fc region). The HGEG peptide showed a half-life of ~22.9 h, consistent with literature, while GLPS exhibited a ~3-fold longer half-life due to contributions from free Fc fragments. Calibration curves were linear (r2 > 0.99) over 1–10,000 ng/mL, LLOQ was 1 ng/mL, and QC samples met ±15 % accuracy and <7 % CV criteria.

Benefits and Practical Applications of the Method

• Universal workflow adaptable to a range of Fc fusion proteins and large-molecule therapeutics.
• Rapid surrogate peptide selection and MRM optimization reduce method development timelines.
• High-throughput, sensitive quantification suitable for PK studies, bioanalysis, and QA/QC in pharmaceutical research.
• Integration of immunoaffinity capture, automated digestion, and UPLC-TQ-MS enables reproducible, high-sensitivity assays.

Future Trends and Applications

Emerging trends include integration of high-resolution MS platforms for simultaneous characterization and quantification, expansion of automated informatics pipelines for de novo peptide discovery, application to multiplexed biotherapeutic panels, and incorporation of microflow or nanoflow LC to further enhance sensitivity and throughput. Continued software integration will accelerate method transfer between HRMS and triple quadrupole systems.

Conclusion

A comprehensive workflow combining peptide mapping, automated MRM optimization, advanced sample preparation, and UPLC-TQ-MS quantification was successfully applied to dulaglutide. The method achieved high sensitivity, precision, and accuracy in a rat PK study and offers a generalizable approach for quantitative analysis of fusion protein therapeutics.

References

• Dunning CD, Wrona MW. How to Maximize Bioanalytical Performance of Fc-Fusion Proteins: Practical Sample Preparation and LC-MS/MS Workflows for Dulaglutide Quantification from Plasma. Waters Application Note 720006823EN.
• Kellie JF, Kehler JR, Szapacs ME. Application of High-Resolution MS for Development of Peptide and Large-Molecule Drug Candidates. Bioanalysis. 2016;8(3):169–177.
• Skyline Targeted Mass Spec Environment. MacCoss Lab, University of Washington; 2020.
• Zhang Y, Huo M, Zhou J, Xie S. PKSolver: An Add-In Program for Pharmacokinetic and Pharmacodynamic Data Analysis in Microsoft Excel. Comput Methods Programs Biomed. 2010;99(3):306–314.
• Australian Public Assessment Report for Dulaglutide RCH. TGA; 2015.
• Center for Drug Evaluation and Research. Pharmacology Review of Dulaglutide. FDA; 2013.
• Kang L, Camacho RC, Li W, et al. Simultaneous Catabolite Identification and Quantitation of Large Therapeutic Protein at the Intact Level by Immunoaffinity Capture LC-HRMS. Anal Chem. 2017;89(11):6065–6075.