Green and sustainable LC-APCI-MS/MS method for simultaneous quantification of genotoxic nitrosamines in antidiabetic medication: sitagliptin

The International Agency for Research on Cancer categorized nitrosamines as potential or probable human carcinogens. Hence, nitrosamine impurities should be controlled to minimize the cancer risk. Sustainable Development Goal 9 (SDG9: Industry, Innovation, and Infrastructure), Target 9.4 was realized by developing a simple and straightforward LC-APCI-MS/MS method for simultaneous determination of potential nitrosamines: N-nitroso dimethylamine, N-nitroso di isopropyl amine, N-nitroso isopropyl ethylamine and N-nitroso methyl aminopyridine (NDMA, NDIPA, NIPEA and NMAP) in Sitagliptin Phosphate Monohydrate API (STG-API), an antidiabetic medication for type-2 diabetes and validated as per ICH (Q2 R2) guidelines. As a part of SDG9 (Industry, Innovation, and Infrastructure), Target 9.4, greater adoption of clean and environmentally sound technologies is possible by using the current analytical method in view of (a) less consumption of solvents as it has a lower run time of 18 min (b) at-line sample collection (c) simple sample preparation (d) sample preparation process that does not require derivatization or sample extraction. The optimized LC method conditions are an Agilent Poroshell EC C18 column, a flow rate of 0.6 mL/min, an injection volume of 40 µL, a column oven temperature set at 50 °C, and a sample cooler temperature set at 6 °C. A gradient method was adopted using a mixture of mobile phases (Solvent A: 0.1% formic acid in water and Solvent B: a mixture of 50% Methanol and 50% Acetonitrile). The response was obtained with Multiple Reaction Monitoring (MRM) in APCI mode. The current method can quantify NDMA, NIPEA, NDIPA, and NMAP to a lower level of 74.19 ng/g, 19.62 ng/g, 20.36 ng/g, and 13.65 ng/g, respectively, which is less than 10% of the specified limits. Good linearity in the range of Limit of Quantitation (LOQ) to 150% of the specification limit was observed, with correlation coefficients higher than 0.996. The recoveries were over the range between 90.23 and 103.36%. Assessed the method's eco-friendliness by greenness tools like the Modified Green Analytical Procedure Index (MoGAPI), ComplexMoGAPI, Analytical GREEnness (AGREE), and Analytical Eco-Scale, and found it to be eco-friendly.

Authors

Institutions

Publication Details

Journal
BMC Chemistry
Published
2025-05-20
DOI
https://doi.org/10.1186/s13065-025-01503-4
Citations
4
Primary Topic
Pharmacological Effects and Assays
Type
article
Field-Weighted Citation Impact
4.77

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Green and sustainable LC-APCI-MS/MS method for simultaneous quantification of genotoxic nitrosamines in antidiabetic medication: sitagliptin

Venkata Nadh Ratnakaram, Sriram Pepakayala, Yuvaraj Zunjarrao, Yogesh Kumar Lohia
4 citations
BMC Chemistry
Pharmacological Effects and Assays
4.77
article

Green and sustainable LC-APCI-MS/MS method for simultaneous quantification of genotoxic nitrosamines in antidiabetic medication: sitagliptin

Venkata Nadh Ratnakaram, Sriram Pepakayala, Yuvaraj Zunjarrao, Yogesh Kumar Lohia
article en
4 citations

Abstract

The International Agency for Research on Cancer categorized nitrosamines as potential or probable human carcinogens. Hence, nitrosamine impurities should be controlled to minimize the cancer risk. Sustainable Development Goal 9 (SDG9: Industry, Innovation, and Infrastructure), Target 9.4 was realized by developing a simple and straightforward LC-APCI-MS/MS method for simultaneous determination of potential nitrosamines: N-nitroso dimethylamine, N-nitroso di isopropyl amine, N-nitroso isopropyl ethylamine and N-nitroso methyl aminopyridine (NDMA, NDIPA, NIPEA and NMAP) in Sitagliptin Phosphate Monohydrate API (STG-API), an antidiabetic medication for type-2 diabetes and validated as per ICH (Q2 R2) guidelines. As a part of SDG9 (Industry, Innovation, and Infrastructure), Target 9.4, greater adoption of clean and environmentally sound technologies is possible by using the current analytical method in view of (a) less consumption of solvents as it has a lower run time of 18 min (b) at-line sample collection (c) simple sample preparation (d) sample preparation process that does not require derivatization or sample extraction. The optimized LC method conditions are an Agilent Poroshell EC C18 column, a flow rate of 0.6 mL/min, an injection volume of 40 µL, a column oven temperature set at 50 °C, and a sample cooler temperature set at 6 °C. A gradient method was adopted using a mixture of mobile phases (Solvent A: 0.1% formic acid in water and Solvent B: a mixture of 50% Methanol and 50% Acetonitrile). The response was obtained with Multiple Reaction Monitoring (MRM) in APCI mode. The current method can quantify NDMA, NIPEA, NDIPA, and NMAP to a lower level of 74.19 ng/g, 19.62 ng/g, 20.36 ng/g, and 13.65 ng/g, respectively, which is less than 10% of the specified limits. Good linearity in the range of Limit of Quantitation (LOQ) to 150% of the specification limit was observed, with correlation coefficients higher than 0.996. The recoveries were over the range between 90.23 and 103.36%. Assessed the method's eco-friendliness by greenness tools like the Modified Green Analytical Procedure Index (MoGAPI), ComplexMoGAPI, Analytical GREEnness (AGREE), and Analytical Eco-Scale, and found it to be eco-friendly.

BMC ChemistryVol. 19(1)
Intas Pharmaceuticals (India) (IN)
Gandhi Institute of Technology and Management
Responsible consumption and production
Openalex Percentile: Top 5%
Pharmacological Effects and Assays
4.77
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.