waters_connect™ for IVD and the QUAN Review application: Advanced Tools for Managing LC-MS Data Analysis

Importance of the Topic

The integration of advanced data-review tools into clinical LC-MS workflows addresses critical needs in modern laboratories. Efficient review systems reduce manual effort, improve data integrity, and accelerate decision-making in diagnostic and research settings.

Aim and Overview of the Application

The QUAN Review application, part of the waters_connect™ for IVD solution, is designed to streamline LC-MS/MS data processing. It offers a layered, user-friendly interface that consolidates key review steps and focuses attention on out-of-specification results.

Methodology and Instrumentation

The application organizes data into grouped views of standards, calibration curves, and QC samples. Exception-Focused Review (XfR) identifies and prioritizes data requiring user intervention. The PanoGramic Display overlays multiple chromatograms and calibration traces for rapid visual inspection.

• Data grouping: standards, calibration, QC in one dashboard
• Automated flagging: set rules for R², signal-to-noise, and deviation thresholds
• Exception handling: focus on anomalies to reduce review time

Instrument Used

QUAN Review is optimized for LC-MS/MS workflows and integrates seamlessly with Waters ACQUITY UPLC systems.

Main Results and Discussion

Implementation of QUAN Review can halve data-review time compared to traditional software such as TargetLynx™. By applying user-defined acceptance criteria automatically, labs see reduced error rates and faster turnaround, even under high sample volumes and complex analytical methods.

Benefits and Practical Applications

The solution enhances throughput and consistency in regulated environments. Key advantages include:

• Up to 50% reduction in manual data review
• Customizable alerts aligned with SOPs
• Improved visibility of out-of-range results
• Scalable performance for high-volume laboratories

Future Trends and Applications

Advances in machine learning and cloud-based collaboration are expected to further automate anomaly detection and facilitate remote data review. Integration with broader informatics ecosystems will support real-time monitoring and global standardization of LC-MS/MS analyses.

Conclusion

QUAN Review within waters_connect for IVD offers a powerful approach to accelerate and standardize clinical LC-MS/MS data processing. Its exception-focused design and intuitive displays deliver measurable efficiency gains, paving the way for next-generation automated review workflows.