Detection, identification and quantification of potential genotoxic compound in chlorhexidine drug substance

Importance of Topic

The presence of genotoxic impurities in pharmaceutical substances can pose serious health risks and must be tightly controlled. Timely detection and accurate quantification of these impurities are essential for regulatory compliance and patient safety, yet traditional approaches are often laborious and time consuming.

Objectives and Study Overview

This study aimed to establish an efficient workflow for the detection, identification and quantification of potential genotoxic compounds formed in chlorhexidine drug substance during degradation. By comparing degraded samples with untreated controls using high-resolution mass spectrometry and advanced software tools, the work demonstrates a streamlined approach to impurity profiling.

Methodology and Instrumentation

The analytical strategy combined All Ions MS/MS acquisition with differential data analysis and targeted quantification using Agilent software.

• Sample preparation: Chlorhexidine was degraded by treating a 1000 ppm methanolic solution with formic acid at 80 °C for 1 hour and diluted to 150 ppm; control samples were untreated.
• Calibration standards: 4-chloroaniline prepared at 0.12 to 300 ng/mL in triplicate.
• Liquid chromatography: ZORBAX Eclipse Plus C18 RRHD column (3.0×50 mm, 1.8 µm), 0.5 mL/min flow, gradient elution with 0.1% formic acid in water and methanol.
• Mass spectrometry: Agilent 6545 Q-TOF in positive mode with All Ions MS/MS acquisition, Swarm Autotune optimized for 50–250 m/z, data collected at 5 spectra/s.
• Data processing: MassHunter Qualitative Analysis for feature extraction; Mass Profiler Software for recursive feature finding, fold-change filtering and PCA; ID Browser for library searches; Quantitative Analysis software for method setup.

Main Results and Discussion

Recursive feature extraction identified nine features with significant up-regulation in degraded samples. Principal component analysis clearly separated the degraded group from controls, indicating distinct impurity profiles. Accurate mass and fragment matching confirmed the presence of 4-chloroaniline among the degradation products. All Ions MS/MS data enabled simultaneous MS and MS/MS identification, while quantification showed a linear calibration over three orders of magnitude (0.1–300 ng/mL) and a quantitation limit around 50 ng/mL. The degraded chlorhexidine samples contained approximately 29 ng/mL of 4-chloroaniline.

Benefits and Practical Applications

The presented workflow allows rapid screening and reliable quantification of genotoxic impurities using standard LC-QTOF instrumentation and integrated software. It supports regulatory compliance by reducing analysis time, enhancing sensitivity and enabling routine monitoring of degradation products in stability and batch-release testing.

Future Trends and Application Potential

Advances in automated feature selection, expansion of in-house high-resolution mass libraries, and the integration of machine learning algorithms will further accelerate impurity profiling. High-throughput platforms and multiplexed quantification strategies are expected to broaden applications in pharmaceutical development and quality control.

Conclusion

The study demonstrates an effective approach to detect, identify and quantify a key genotoxic impurity in chlorhexidine drug substance. By leveraging data-independent acquisition and recursive differential analysis, the workflow achieves high confidence in impurity characterization and meets stringent regulatory requirements.

References

• Lateef SS, Joseph S. Detection, identification and quantification of potential genotoxic compound in chlorhexidine drug substance. Agilent Technologies India Pvt. Ltd; HPLC 2015: PSA-DATA-08.