Issue 14, 2022

A NIR, 1H-NMR, LC-MS and chemometrics pilot study on the origin of carvedilol drug substances: a tool for discovering falsified active pharmaceutical ingredients

Abstract

Falsification of drugs, entailing the use of drug substances from unknown unapproved suppliers, is one of the main concerns for the quality of medicines. Therefore, traceability of active ingredients represents an effective tool to fight the illegal trade of medicinal products. In this view, the present pilot study explores the profile of carvedilol active ingredients and possible differences related to the origin. Sixteen samples were examined by near-infrared spectroscopy (NIR), proton nuclear magnetic resonance (1H-NMR spectrometry) and liquid chromatography mass spectrometry (LC-MS) Q-TOF and the data were analysed by principal component analysis (PCA), cluster analysis and PLSDA discriminant analysis. The results evidenced that the combined information from the three techniques gave good classification of the samples neatly distinguishing the APIs from European countries from the APIs manufactured out of Europe. In particular, NIR spectroscopy provided effective separation between European and non-European manufacturers and 1H-NMR or LC-MS added specific information related to the separation. Concerning LC-MS Q-TOF, the analysis of multiple isobaric peaks proved to be highly predictive of the drug substance origin and emerged as a promising tool in the field of medicine traceability.

Graphical abstract: A NIR, 1H-NMR, LC-MS and chemometrics pilot study on the origin of carvedilol drug substances: a tool for discovering falsified active pharmaceutical ingredients

Supplementary files

Article information

Article type
Paper
Submitted
01 Dec 2021
Accepted
25 Feb 2022
First published
28 Feb 2022

Anal. Methods, 2022,14, 1396-1405

A NIR, 1H-NMR, LC-MS and chemometrics pilot study on the origin of carvedilol drug substances: a tool for discovering falsified active pharmaceutical ingredients

M. Raimondo, A. Borioni, F. Prestinaci, I. Sestili and M. C. Gaudiano, Anal. Methods, 2022, 14, 1396 DOI: 10.1039/D1AY02035H

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