Development and Validation of an LC–MS/MS Method for Trace‐Level Nitrosamine Analysis in Mexiletine Formulations

ABSTRACT Since 2018, genotoxic targeted nitrosamine impurity levels have been monitored and restricted as a necessary quality and safety characteristic for a number of pharmaceutical products. A highly reliable and sensitive analytical technique was created and verified in this study to quantitatively identify seven minor nitrosamines in the mexiletine formulation at low concentrations. Gradient elution employed a mobile phase A consisting of 0.1% formic acid in water. 0.1% formic acid in methanol was utilized as mobile phase‐B at a flow rate of 0.5 mL/min.·A 150 mm × 4.6 mm, 5 µm Inertsil ODS C18 column was used to achieve chromatographic separation, and the column temperature was kept at 40°C. The method was validated in accordance with USP <1225> and ICH criteria. This analysis shows linearity ( R 2 > 0.999) and a high degree of accuracy, ranging from 95.3% to 104.8%. Because it uses a methodical, statistically optimized approach for method development to guarantee robustness, accuracy, and dependability, the LC‐MS/MS technology is important for mexiletine formulations. According to the study, this method might be used not only for mexiletine capsules but also as a generic screening tool to evaluate various medicinal substances and drug products under the minimal circumstances needed for method optimization.

Authors

Institutions

Publication Details

Journal
Separation Science Plus
Published
2026-04-01
DOI
https://doi.org/10.1002/sscp.70224
Primary Topic
Water Treatment and Disinfection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and Validation of an LC–MS/MS Method for Trace‐Level Nitrosamine Analysis in Mexiletine Formulations

Bharat Kumar Tripuramallu, E. Prashanth Kumar, Abhishek Sharma, Prasanth Katakam
Separation Science Plus
Water Treatment and Disinfection
article

Development and Validation of an LC–MS/MS Method for Trace‐Level Nitrosamine Analysis in Mexiletine Formulations

Bharat Kumar Tripuramallu, E. Prashanth Kumar, Abhishek Sharma, Prasanth Katakam
article en

Abstract

ABSTRACT Since 2018, genotoxic targeted nitrosamine impurity levels have been monitored and restricted as a necessary quality and safety characteristic for a number of pharmaceutical products. A highly reliable and sensitive analytical technique was created and verified in this study to quantitatively identify seven minor nitrosamines in the mexiletine formulation at low concentrations. Gradient elution employed a mobile phase A consisting of 0.1% formic acid in water. 0.1% formic acid in methanol was utilized as mobile phase‐B at a flow rate of 0.5 mL/min.·A 150 mm × 4.6 mm, 5 µm Inertsil ODS C18 column was used to achieve chromatographic separation, and the column temperature was kept at 40°C. The method was validated in accordance with USP <1225> and ICH criteria. This analysis shows linearity ( R 2 > 0.999) and a high degree of accuracy, ranging from 95.3% to 104.8%. Because it uses a methodical, statistically optimized approach for method development to guarantee robustness, accuracy, and dependability, the LC‐MS/MS technology is important for mexiletine formulations. According to the study, this method might be used not only for mexiletine capsules but also as a generic screening tool to evaluate various medicinal substances and drug products under the minimal circumstances needed for method optimization.

Separation Science PlusVol. 9(4)
Vignan's Foundation for Science, Technology & Research (IN), GITAM University (IN)
Openalex Percentile: Top 6%
Water Treatment and Disinfection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.