o Case study (1): Detection and characterization of ranitidine metabolites in human plasma using LC-HRMS and background subtraction filter (BSF)

Introduction: Metabolite profiling, characterization, and quantification in human plasma from SAD and MAD studies are essential for MIST assessment and selecting metabolites for DDI, PK, and pharmacological activity evaluations. Complete metabolite profiling in human plasma is challenging due to low concentrations, unpredictable metabolic pathways, and interference from endogenous components. The goal was to develop and validate a novel LC-HRMS method using an untargeted background subtraction filtering technique to enhance metabolite detection.

Experimental: Human plasma samples were collected prior to dosing and 6 hours after administration of a single 150 mg dose of ranitidine. LC-HRMS data were acquired and analyzed using the Background Subtraction Filter (BSF) tool.

Results: As shown in Fig. 2A, the unprocessed total ion chromatogram (TIC) from the 6-hour sample showed only the parent drug and an N-oxide metabolite. In contrast, the BSF-processed LC/MS profile revealed multiple minor metabolites with few false positives (Fig. 2B). Additionally, the BSF-processed spectrum at 21.7 minutes clearly identified two metabolite-related ions, enabling structural elucidation (Fig. 2D), whereas the unprocessed MS spectrum at the same retention time did not show any visible metabolite ions (Fig. 2C).

Fig. 2. Comprehensive and sensitive detection of ranitidine metabolites in human plasma using LC-HRMS and BSF data processing

Conclusion: BSF is a powerful LC-HRMS data processing tool for detecting both common and uncommon metabolites, regardless of their molecular weight, mass defect, structure or fragmentation pattern.