Identification and Structural Elucidation of Amlodipine Impurities Using High Resolution LC/MS and LC-MS/MS

Importance of Topic

The structural characterization of drug impurities is a key aspect of pharmaceutical development ensuring that trace contaminants are identified and controlled in drug products. Regulatory guidelines require the elucidation of impurity structures once they exceed defined thresholds. High resolution accurate mass spectrometry coupled with advanced data processing enables confident identification of unknown compounds and supports safety assessments.

Objectives and Study Overview

This study aimed to identify and determine the structure of in process amlodipine impurities using high resolution liquid chromatography quadrupole time of flight mass spectrometry and dedicated software tools. Known impurity standards were used to build a custom spectral library. Unknown in process samples were analyzed by accurate mass MS, MS/MS and pseudo MS3 to propose elemental compositions and structural assignments.

Methodology

Data dependent acquisition at low and high fragmentor voltage generated MS, MS/MS and pseudo MS3 spectra. Custom spectral libraries were created using the Personal Compound and Database Library software from MS/MS data of known standards. Fragment search and formula generation identified matching substructures in unknowns. The Molecular Structure Correlator proposed fragmentation pathways by comparing experimental fragment masses with in silico fragments.

Used Instrumentation

• Agilent 1290 Infinity binary pump and Dual Jet Stream source
• Agilent 6540 quadrupole time of flight accurate mass spectrometer
• Agilent MassHunter qualitative analysis software
• Personal Compound and Database Library manager
• Molecular Structure Correlator software
• ACD ChemSketch and ACD MS Fragmentor

Main Results and Discussion

Nine distinct impurity peaks were detected in the in process amlodipine sample with accurate masses in the range of mz 180 to mz 643. Mass errors were maintained below five ppm. Fragment ions observed at mz 294 and mz 192 matched those of known impurity standards E and H confirming common substructures. Structural proposals for each impurity were generated and validated through pseudo MS3 pathways. Software assisted correlation enabled assignment of elemental compositions and fragmentation patterns.

Benefits and Practical Applications

• Improved confidence in impurity identification through high resolution accurate mass and MS/MS techniques
• Efficient use of custom spectral libraries for rapid substructure matching
• Support for regulatory compliance in drug development and quality control
• Reduction of manual interpretation time using software assisted workflows

Future Trends and Potential Applications

Integration of artificial intelligence for automated spectral interpretation and expansion of spectral databases will streamline impurity profiling. Coupling real time monitoring with high resolution mass spectrometry could enable dynamic process control. Advances in fragmentation prediction models and software integration offer further opportunities for high throughput structural elucidation in pharmaceutical research.

Conclusion

The combination of high resolution LC Q TOF MS acquisition modes with intelligent data processing software enabled the identification and structural characterization of nine amlodipine related impurities. Custom spectral libraries and software tools provided detailed insight into fragmentation pathways and accelerated impurity profiling in compliance with regulatory requirements.

Reference

• No specific literature references were provided in the source document