LC-MS Bioanalytical Quantification of a GalNAc-siRNA Conjugate Oligonucleotide Using Semi-Automated Solid Phase Extraction

Importance of the Topic

Oligonucleotide therapeutics require sensitive and robust quantification methods due to their tendency to bind metal surfaces and proteins in biological matrices. Semi-automated sample preparation addresses variability in manual workflows and improves recovery and reproducibility in bioanalytical studies. The combination of advanced LC columns with high performance surface technology further reduces analyte loss and enhances detection sensitivity.

Study Objectives and Overview

This study aimed to develop and validate a semi-automated solid phase extraction method for the quantification of a GalNAc-siRNA conjugated oligonucleotide in plasma and urine using LC-MS/MS. Key objectives included minimizing sample handling errors, achieving low limits of detection, and demonstrating linearity, accuracy, and precision according to regulatory guidelines.

Methodology

Biological samples were prepared using a mixed-mode weak anion exchange microelution SPE plate. Calibration curves and quality controls were prepared by robotic liquid handling with a pipetting workstation, covering concentration ranges from 2 to 1000 nanograms per milliliter. Plasma and urine samples underwent pretreatment and SPE using positive pressure. Chromatographic separation was performed on a reversed-phase C18 column with high performance surface treatment under a gradient of aqueous and organic mobile phases containing hexafluoroisopropanol and diisopropylethylamine. Mass spectrometric detection employed multiple reaction monitoring in negative electrospray mode.

Použitá instrumentace

• Pipette+ automated pipetting workstation
• Otto SPEcialist positive pressure manifold
• ACQUITY Premier LC System
• ACQUITY Premier Oligonucleotide BEH C18 Column
• Xevo TQ-XS triple quadrupole mass spectrometer
• MassLynx v4.2 and TargetLynx software

Main Results and Discussion

Solid phase extraction recoveries for neat solutions were 109.7 percent at 10 nanograms per milliliter and 88.6 percent at 1000 nanograms per milliliter with relative standard deviations below 10 percent. Post-extraction analysis in plasma and urine achieved limits of detection of 1 nanogram per milliliter, linear dynamic ranges up to 1000 nanograms per milliliter with correlation coefficients above 0.996, and accuracy and precision within 20 percent criteria. Matrix effects remained below 10 percent, demonstrating robust performance across multiple batches.

Benefits and Practical Applications

• Reduced user variability and improved reproducibility through semi-automation
• Consistent method transferability across laboratories using unified software protocols
• Lower detection limits and higher recovery rates by mitigating metal adsorption with advanced column surfaces
• Efficient workflow from sample to quantification in pharmacokinetic and toxicokinetic studies

Future Trends and Potential Applications

Advances in automated sample preparation are expected to integrate with high-throughput bioanalysis platforms, supporting large-scale oligonucleotide screening. Continued development of LC column chemistries will further reduce analyte losses and enhance sensitivity. Emerging applications may include personalized medicine workflows and real-time therapeutic monitoring using integrated microfluidic and mass spectrometry systems.

Conclusion

The semi-automated SPE method combined with advanced LC-MS instrumentation provides sensitive, accurate, and reproducible quantification of GalNAc-siRNA conjugates in biological fluids. This workflow addresses common challenges in oligonucleotide analysis and supports rigorous bioanalytical method validation requirements.

Reference

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2. Brennan K, et al. Improved Oligonucleotide SPE-LC-MS Analysis Using MaxPeak High Performance Technology. Waters Application Note 720007019EN; 2020.
3. Bansal S, DeStefano A. Key Elements of Bioanalytical Method Validation for Small Molecules. AAPS Journal. 2007;9(1):E109-E114.