Drug Metabolite Identification Using Waters™ SELECT SERIES™ Cyclic™ Ion Mobility Mass Spectrometer and waters_connect™ Application Manager

Significance of the Topic

The identification and profiling of drug metabolites is critical for safe and efficient drug discovery and development.
By combining ion mobility enabled high resolution mass spectrometry with advanced informatics, researchers can accurately track in vivo biotransformations and improve confidence in safety assessments.

Objectives and Study Overview

This study applied a generic, high throughput workflow to characterize the in vivo metabolic fate of fasiglifam, a GPR40 agonist withdrawn from trials due to liver toxicity.
Key aims included:

• Detection of drug related metabolites over a 96 hour time course
• Accurate mass measurement and collision cross section determination
• Localization of biotransformation sites using structural informatics

Methodology and Instrumentation

Plasma samples from rats dosed at 50 mg/kg were protein precipitated and analyzed by reversed phase UPLC coupled to HDMSE in negative electrospray mode.
Data acquisition captured precursor, fragment, and ion mobility CCS data in one pass.

Instrumentation Used

• ACQUITY UPLC I Class system with ACQUITY HSS T3 column
• Waters SELECT SERIES Cyclic Ion Mobility Spectrometer
• MassLynx 4.2 for data collection
• waters_connect with UNIFI for automated metabolite identification

Main Results and Discussion

A total of 15 fasiglifam related metabolites were detected with an average mass error of -0.77 ppm.
Key findings include:

• Identification of both previously reported and novel metabolites
• Glucuronidation and oxidative biotransformations localized by fragment analysis
• Retention of drug and metabolites in plasma up to 96 hours
• Summary plots illustrating time course profiles of parent and metabolites

Practical Benefits and Applications

The described platform offers:

• Robust and generic acquisition methods for rapid screening
• Customizable informatics workflows for confident metabolite assignment
• Integrated CCS data to resolve isobaric species

Future Trends and Applications

Advances may include:

• Expansion of CCS libraries for broader compound coverage
• Integration of machine learning to predict metabolic pathways
• Adoption in regulatory environments for safety assessment

Conclusion

This study demonstrates how ion mobility enabled mass spectrometry combined with advanced informatics streamlines drug metabolite profiling.
The workflow balances high throughput with structural confidence, enabling comprehensive characterization of drug safety profiles.

References

1. Li X et al. Fasiglifam inhibits hepatobiliary transporters, Drug Metab Dispos 2015;43(11):1751 1759
2. Otieno MA et al. Mechanistic investigation of fasiglifam induced liver injury, Toxicol Sci 2018;163(2):374 384
3. Kogame A et al. Disposition and metabolism of TAK 875 in rats dogs and humans, Xenobiotica 2019;49(4):433 445