Simple HRMS Data Review Using Workflows, Views, and Filters Within a Novel Integrated Scientific Information System

Importance of Topic

High‐resolution mass spectrometry (HRMS) has become a cornerstone in global food safety and environmental monitoring, enabling simultaneous detection of thousands of compounds in complex matrices. Efficient data review methods are essential to rapidly distinguish compliant from non‐compliant samples, while ensuring breadth of coverage, sensitivity, and data integrity.

Goals and Study Overview

This study demonstrates a streamlined workflow for non‐targeted HRMS screening using data‐independent acquisition modes (MSⁿE and HDMSⁿE) coupled with an integrated scientific information system (UNIFI). It aims to simplify review of complex datasets, support both targeted and unknown screening, and reduce analysis time from injection to report.

Methodology and Instrumentation

The approach relies on unbiased MSⁿE acquisition, collecting low‐ and elevated‐energy spectra in alternating functions, and HDMSⁿE for orthogonal ion mobility separation. Raw data are processed by componentization, converting chromatographic peaks into discrete components characterized by isotopes, adducts, and fragments. Filters, views, and workflows in the UNIFI system enable rapid interrogation of components against target lists or user‐defined criteria.

Used instrumentation:

• ACQUITY UPLC I-Class System with BEH C18 column
• Xevo G2-S Q-Tof and Xevo G2-XS Q-Tof mass spectrometers
• SYNAPT G2-Si HDMS with ion mobility capability
• UNIFI Scientific Information System and Pesticides Screening Application

Main Results and Discussion

The componentization approach significantly improves spectral clarity by aligning ions within narrow retention time and drift windows. Compared to extracted ion chromatograms, componentized spectra exclude unrelated co‐eluting signals and false positives. Customizable filters (e.g., mass accuracy, fragment match, halogen presence) and saved workflow steps guide users through qualitative screening, quantification, binary comparisons, and unknown identification. This unified workflow reduces manual decision points and enhances consistency across operators.

Benefits and Practical Applications

• Comprehensive screening for theoretically unlimited analytes in a single injection
• Simultaneous qualitative and quantitative analysis without separate methods
• Reduced false positives through orthogonal confirmatory data (isotopes, adducts, CCS, fragments)
• Streamlined, reproducible data review via saved workflows and views
• Historical data mining enabled by database storage of raw data, methods, and components
• Quick YES/NO decision making for regulatory compliance and non‐target discovery

Future Trends and Opportunities

As the demand for broader and deeper surveillance grows, integration of machine learning for pattern recognition, expansion of CCS libraries, and real‐time data analytics are expected to enhance unknown screening capabilities. Advances in ion mobility, AI‐driven workflows, and cloud‐based data sharing will further accelerate discovery and regulatory decision support.

Conclusion

Combining non‐targeted HRMS acquisition with UNIFI’s componentization, filters, views, and workflows provides an efficient, robust solution for modern multi‐residue screening. This approach delivers high specificity, reduces review time, and supports simultaneous targeted and unknown analyses, meeting the evolving needs of food and environmental testing laboratories.

Reference

1. An Overview of the Principles of MSⁿE: The Engine that Drives MS Performance, Waters White Paper No. 720004036EN, October 2011.
2. Waters UNIFI Scientific Information System Componentization, Waters White Paper No. 720004597EN, April 2013.