TY  - JOUR
A1  - Becht, Alexander
A1  - Schollmayer, Curd
A1  - Monakhova, Yulia
A1  - Holzgrabe, Ulrike
T1  - Tracing the origin of paracetamol tablets by near-infrared, mid-infrared, and nuclear magnetic resonance spectroscopy using principal component analysis and linear discriminant analysis
T2  - Analytical and Bioanalytical Chemistry
N2  - Most drugs are no longer produced in their own countries by the pharmaceutical companies, but by contract manufacturers or at manufacturing sites in countries that can produce more cheaply. This not only makes it difficult to trace them back but also leaves room for criminal organizations to fake them unnoticed. For these reasons, it is becoming increasingly difficult to determine the exact origin of drugs. The goal of this work was to investigate how exactly this is possible by using different spectroscopic methods like nuclear magnetic resonance and near- and mid-infrared spectroscopy in combination with multivariate data analysis. As an example, 56 out of 64 different paracetamol preparations, collected from 19 countries around the world, were chosen to investigate whether it is possible to determine the pharmaceutical company, manufacturing site, or country of origin. By means of suitable pre-processing of the spectra and the different information contained in each method, principal component analysis was able to evaluate manufacturing relationships between individual companies and to differentiate between production sites or formulations. Linear discriminant analysis showed different results depending on the spectral method and purpose. For all spectroscopic methods, it was found that the classification of the preparations to their manufacturer achieves better results than the classification to their pharmaceutical company. The best results were obtained with nuclear magnetic resonance and near-infrared data, with 94.6%/99.6% and 98.7/100% of the spectra of the preparations correctly assigned to their pharmaceutical company or manufacturer.
KW  - IR
KW  - Manufacturer
KW  - Linear discriminant analysis
KW  - Principal component analysis
Y1  - 2021
UR  - https://opus.bibliothek.fh-aachen.de/opus4/frontdoor/index/index/docId/9553
SN  - 1618-2650
VL  - 413
SP  - 3107
EP  - 3118
PB  - Springer Nature
ER  -