Two advanced metabolomics-based data processing approaches for comprehensive drug metabolite identification using...

Area of Science:

• Pharmacology and Toxicology
• Analytical Chemistry
• Metabolomics

Background:

• Accurate drug metabolite identification is crucial for drug development and safety assessment.
• Stable isotope tracing (SIT) coupled with dose-response techniques offers a powerful approach for metabolite profiling.
• Further validation is needed to establish the robustness and comprehensiveness of these analytical methods.

Purpose of the Study:

• To validate a previously developed dose-response technique combined with stable isotope tracing (SIT) for drug metabolite identification.
• To assess the consistency and efficacy of the method using different incubation strategies and replicate datasets.
• To compare the performance of the developed approach with mass defect filtering (MDF) coupled with SIT.

Main Methods:

• Utilized a dose-response technique integrated with stable isotope tracing (SIT).
• Employed two distinct incubation methods: coincubation and separate incubation of the drug and its labeled analog.
• Analyzed two replicate datasets for each incubation method to ensure reproducibility.
• Applied mass defect filtering (MDF) coupled with SIT as a comparative method.

Main Results:

• Identified a total of 24 potential rosiglitazone (ROS) metabolite ions with proposed structures.
• Demonstrated high consistency in metabolite identification, with 12 out of 13 ions consistently identified across replicates in coincubation datasets.
• Separate incubation datasets yielded more potential metabolites (n=20) for screening compared to coincubation (n=13).
• Observed similar identification trends when comparing the developed approach with MDF coupled with SIT.

Conclusions:

• The dose-response technique coupled with SIT provides a reliable and consistent method for drug metabolite identification.
• Coincubation datasets showed higher reproducibility for metabolite identification compared to separate incubation datasets.
• The developed approach and MDF coupled with SIT can complement each other, enhancing the comprehensiveness of analytical strategies for drug metabolism studies.