Carcinogenic N -nitrosamines were recently found in the sartan family of drugs and caused many drug recalls. Both of their detection and quantification are therefore important. Methods reported for N -nitrosamine quantitation rely on the use of standards and are just applicable to simple N -nitrosamines. There is an urgent need to quantify N -nitrosamines derived from drugs with a complicated structure that lack standards. To tackle the issue, this study describes a novel absolute quantitation strategy for N -nitrosamines using coulometric mass spectrometry (CMS) without standards. In our approach, N -nitrosamine is first converted into electrochemically active hydrazine via zinc reduction under acidic condition and the resulting hydrazine can then be easily quantified using CMS. To validate our method, six simple N -nitrosamines, N -nitrosodiethylamine (NDEA), N -nitroso-4-phenylpiperidine (NPhPIP), N -nitrosodiphenylamine (NDPhA), N -nitrosodibutylamine (NDBA), N -nitrosodipropylamine (NDPA), and N -nitrosopiperidine (NPIP), were chosen as test samples, and they all were quantified with excellent measurement accuracy (quantitation error ≤1.1%). Taking this one step further, as a demonstration of the method utility, a drug-like N -nitrosamine, ( R )- N -(2-(6-chloro-5-methyl-1'-nitroso-2,3-dihydrospiro[indene-1,4'-piperidin]-3-yl)propan-2-yl)acetamide ( VII ), was also synthesized and successfully quantified using our method at 15 ppb level in a complex formulation matrix, following solvent extraction, N -nitrosamine isolation, and reductive conversion. Because of the feature of requiring no standards, CMS provides a simple and powerful approach for N -nitrosamine absolute quantitation and has great potential for analysis of other drug impurities or metabolites.
Keyphrases
- mass spectrometry
- liquid chromatography
- ms ms
- high performance liquid chromatography
- liquid chromatography tandem mass spectrometry
- tandem mass spectrometry
- gas chromatography
- capillary electrophoresis
- high resolution
- solid phase extraction
- drug induced
- emergency department
- simultaneous determination
- ionic liquid
- machine learning
- fluorescent probe
- deep learning
- risk assessment
- sensitive detection