Loading...
Thumbnail Image
Item

Clustering of Tadalafil API Samples According to their Manufacturer in the Context of API Falsification Detection

Raimondo, M.
Borioni, A.
Grange, Y.
Rebière, H.
Mihailova, A.
Bøyum, O.
Maurin, J.K.
Pioruńska-Sędłak, K.
Stengelshøj, Olsen, L.
... show 7 more
Citations
Altmetric:
Abstract

This paper reports the results of the active pharmaceutical ingredient (API) fingerprint study, organised by the General European Official Medicines Control Laboratory Network (GEON), on tadalafil. A classical market surveillance study, evaluating compliance to the European Pharmacopoeia, was combined with a fingerprint study, the latter to obtain characteristic data for the different manufacturers, allowing the network laboratories to conduct authenticity tests for future samples, as well as to detect substandard and falsified samples.

; ;

In total, 46 tadalafil API samples from 13 different manufacturers were collected. For all samples fingerprint data was collected through analysis of impurities and residual solvents, mass spectrometric screening, X-ray powder diffraction and proton nuclear magnetic resonance (1H-NMR). Chemometric analysis revealed that all manufacturers could be characterised based on the impurity, residual solvent and 1H-NMR data. Future suspicious samples in the network will therefore be analysed with these techniques in order to attribute the sample to one of the manufacturers. If the sample cannot be attributed, a more profound investigation will be necessary to reveal the origin of the sample. In cases where the suspect sample is claimed to be from one of the manufacturers included in this study, analysis can be limited to the test distinguishing that manufacturer.

Description
Date
2023-01-11
Journal Title
Journal ISSN
Volume Title
Publisher
Chapter title
Publication type
Peer reviewed scientific article
Research Projects
Organizational Units
Journal Issue
Keywords
APIs, fingerprint, GEON/OMCL network, illegal medicinal products, Tadalafil
Citation
Topic(s)
Related project
FAGG #1000011#
Embedded videos