Benefits of 2D-LC/MS/MS in Pharmaceutical Bioanalytics

Applications | 2018 | Agilent TechnologiesInstrumentation
LC/MS, LC/MS/MS, LC/QQQ, 2D-LC
Industries
Pharma & Biopharma
Manufacturer
Agilent Technologies

Summary

Significance of the Topic


The accurate quantification of small-molecule drugs and their metabolites in complex biological matrices is critical for pharmacokinetic and bioanalytical studies. Traditional one-dimensional LC/MS/MS methods often face challenges from coeluting matrix components, leading to signal suppression and in-source cross-talk. Implementing two-dimensional liquid chromatography coupled with tandem mass spectrometry (2D-LC/MS/MS) can overcome these obstacles, enhancing sensitivity and selectivity.

Objectives and Study Overview


This application note describes two case studies illustrating how the Agilent InfinityLab 2D-LC system combined with an Agilent 6495 triple quadrupole LC/MS can:
  • Eliminate coelution and reduce matrix-related signal suppression or cross-talk through multidimensional separation.
  • Improve MS detection sensitivity by optimizing the eluent composition in the second chromatographic dimension.

Both examples focus on in vitro assays involving complex mixtures of drug candidates, metabolites, substrates, and inhibitors.

Methodology and Instrumentation Used


All analyses employed the Agilent 1290 Infinity II 2D-LC system linked to an Agilent 6495 triple quadrupole LC/MS with Jet Stream ESI. Key components included high-speed pumps, multisamplers with cooling, a multicolumn thermostat, and heart-cutting valve modules equipped with multiple loops. Data were acquired and quantified using Agilent OpenLAB CDS ChemStation and MassHunter Workstation software suites.

Main Results and Discussion


• Avoiding signal suppression and cross-talk: A cell suspension assay generated a complex supernatant containing 16 target metabolites amid high-abundance substrates and inhibitors. Time-based multiple heart-cutting transferred target windows from the first-dimension C18 column to a second PFP column. This resolved coeluting species and prevented signal loss. A full 35-minute 2D run replaced six separate one-dimensional methods, saving sample and instrument time.
• Enhancing MS detection sensitivity: An in vitro cell culture assay required quantification of one parent compound and up to three metabolites. Initial screening showed compromised sensitivity using standard formic acid/acetonitrile mobile phases, while ammonium acetate/methanol improved signal but sacrificed chromatographic resolution. By performing a high-flow first-dimension run for separation and trapping heart-cuts on a second-dimension non-endcapped C18 column eluted with ammonium acetate/methanol, the method achieved a 3-fold increase in signal intensity and reduced cycle time from 9.5 to 6.5 minutes.

Benefits and Practical Application


  • Substantial reduction of matrix effects and cross-talk, improving quantitation limits.
  • Consolidation of multiple assays into a single 2D-LC workflow, saving analysis time.
  • Enhanced sensitivity by introducing analytes in a solvent optimized for MS detection.

Future Trends and Opportunities


Advances in multidimensional separation technologies and faster valve switching will further streamline bioanalytical workflows. Emerging column chemistries and on-line sample cleanup modules can expand the range of tackleable matrices. Integration with high-resolution MS and data-independent acquisition strategies promises even greater selectivity.

Conclusion


2D-LC/MS/MS demonstrates significant advantages for pharmaceutical bioanalysis by addressing matrix complexity and enhancing detection sensitivity. The dual-dimension approach reduces assay times, consolidates workflows, and delivers robust, reproducible quantitation of drugs and metabolites in challenging biological samples.

References


  • Vanhoenacker, G.; et al. Two-Dimensional LC/MS/MS to Reduce Ion Suppression in the Determination of Cannabinoids in Blood Plasma. Agilent Technologies Application Note 5991-7859EN, 2017.

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