Using Mass-MetaSite and WebMetabase to Process HDMSE Data Acquired on the Vion IMS QTof Mass Spectrometer

Significance of Topic

High-resolution ion mobility-enhanced mass spectrometry combined with UPLC and advanced data processing platforms is critical for accurate drug metabolism studies during lead optimization. Integrating third-party applications with vendor software expands analytical capabilities and accelerates pharmacokinetic profiling.

Goals and Overview

This study describes the seamless integration of Mass-MetaSite and WebMetabase with UNIFI via its API to process HDMSE datasets from a Vion IMS QTof mass spectrometer. The objective is to automate metabolite identification in hepatocyte incubations and enable both single-sample and batch analyses.

Methodology and Instrumentation

Verapamil was incubated in rat hepatocytes at 10 µM. Time-point aliquots were quenched with acetonitrile, centrifuged, diluted, and analyzed by HDMSE on a Vion IMS QTof coupled to an ACQUITY UPLC I-Class system under UNIFI control. Data were transferred via UNIFI API to a processing workstation running UNIFI 1.9.4, Mass-MetaSite, and WebMetabase. Secure, password-based authentication allowed navigation of the UNIFI folder structure for dataset selection. Two processing modes were available: single-sample analysis in Mass-MetaSite with control comparison, and batch processing across species, time points, and matrices in WebMetabase.

Used Instrumentation

• Vion IMS QTof Mass Spectrometer
• ACQUITY UPLC I-Class System
• UNIFI Scientific Information System v1.9.4 with API v1.0
• Mass-MetaSite software
• WebMetabase platform

Main Results and Discussion

Consistency between UNIFI and Mass-MetaSite outputs was confirmed, with average differences of 0.05 ppm for m/z and 0.04 % for collision cross section (CCS) values. Metabolite profiles at the 30 min time point showed clear separation of isobaric species based on m/z, retention time, and CCS. Drift time correlation furnished high-quality product ion spectra comparable to targeted MS/MS, facilitating confident metabolite annotation.

Benefits and Practical Applications

The integrated workflow enables robust, user-friendly metabolite characterization with high throughput. Batch processing supports drug discovery teams in screening multiple compounds and conditions simultaneously. Cloud-enabled reporting and visualization streamline data review across research and development sites.

Future Trends and Applications

Advances in API-driven data exchange will further enhance interoperability between vendor and third-party tools. Machine learning–based metabolite prediction, expanded cloud solutions, and automated reporting pipelines are expected to drive faster decision making in pharmacokinetic optimization.

Conclusion

The UNIFI API fosters an open ecosystem where Mass-MetaSite and WebMetabase extend core platform capabilities. Together, they provide a comprehensive, scalable solution for detailed drug metabolism studies, supporting lead candidate selection and development.

References

• Kirk J., Wrona M., Mortishire-Smith R., Zamora I., Fontaine F., Goshawk J., Lunt M., Doering K., Anderson N. Using Mass-MetaSite and WebMetabase to Process HDMSE Data Acquired on the Vion IMS QTof Mass Spectrometer. Waters Corporation, July 2018.