A novel data processing algorithm “Mass-it” that generates MS-labeled UV chromatograms for facilitating impurity analysis using single quadrupole LC-MS

Significance of the Topic

Liquid chromatography with mass spectrometric detection is indispensable for sensitive qualitative and quantitative analysis of impurities in pharmaceutical and chemical production. The integration of UV and MS data streamlines impurity profiling by combining high sensitivity with structural information, mitigating limitations of UV-only detection and facilitating quality control.

Study Objectives and Overview

This work introduces a novel deconvolution algorithm 'Mass-it', demonstrates the robustness of a compact single quadrupole LCMS system against contamination and high sample loads, and evaluates a dual ionization source for versatile compound coverage. The study benchmarks data processing, assesses long-term performance, and illustrates algorithm-assisted impurity detection.

Methodology and Used Instrumentation

The analyses employed a Nexera XR UHPLC coupled to a Shimadzu LCMS-2050 single quadrupole MS. Chromatographic separation used LC-40B XR pumps, SIL-40C XR autosampler, CTO-40C column oven, and SPD-M40 photodiode array detector. MS detection spanned m/z 100–1000 in scan mode with dual ionization (DUIS) enabling ESI and APCI in positive and negative polarities. Standard compounds (atorvastatin, propranolol, simetryn, quintozene) were injected at defined concentrations, and default gas flow and desolvation settings applied.

Main Results and Discussion

The Mass-it algorithm processed total ion current peaks to generate UV chromatograms annotated with corresponding m/z labels. It accurately identified co-eluting species by aligning retention times from extracted ion chromatograms and suppressed background signals lacking defined peak tops. In a high-purity atorvastatin sample, a single component was consistently labeled, while impurity profiling revealed minor peaks annotated with specific m/z values. Long-term stability testing involved 10,000 sequential injections of a mixture of three pharmaceuticals at 1000 ng/µL. The system exhibited 8.5% RSD in peak area without signal degradation, demonstrating resistance to contamination. The DUIS interface showed comparable ionization efficiency for ESI-favored and APCI-favored compounds, confirming versatile ion source performance.

Benefits and Practical Applications

• Enhanced data interpretation: automated labeling of UV peaks with m/z improves identification of impurities and co-eluting species.
• Operational robustness: hardware design features (large inlet, heated off-axis gas, sweeping voltage) maintain stable performance under heavy sample loads.
• Versatile ionization: combined ESI/APCI source allows broad compound coverage in a single analysis.
• Simplified LC-MS adoption: intuitive software functions lower the barrier for non-specialized users in impurity analysis.

Future Trends and Potential Applications

• Integration with high-resolution MS: extending Mass-it to accurate mass data may improve structural elucidation of unknown impurities.
• Real-time data processing: online implementation of the algorithm could accelerate decision-making during method development.
• Machine learning enrichment: coupling chromatographic and spectral data with predictive models for automatic impurity prioritization.
• Broader industry adoption: application to environmental, food safety, and metabolomics workflows for comprehensive screening.

Conclusion

The combination of the Mass-it deconvolution algorithm, robust single quadrupole LCMS hardware, and dual ionization capability delivers a powerful platform for impurity analysis. Automated UV/MS data fusion simplifies interpretation, while contaminant-proof design and universal ion source broaden application scope. These innovations facilitate the routine use of LC-MS in quality control environments.

Reference

1. K. Koterasawa et al., Technical background for the LCMS-2050, a compact mass detector for LC, Shimadzu Corp. technical report C146-E453, 2022.
2. K. Koterasawa et al., Improvement of liquid chromatograph performance by Mass-it function, Shimadzu Corp. technical report C146-E454, 2022.