Comparing the qualitative performances of handheld NIR and Raman spectrometers for the analysis of falsified pharmaceutical products.

The last decade has seen a significant growth of the pharmaceutical market of emerging countries to the point that it has induced many falsifications. Research activities have followed this growth but not proportionately. Recently, several chemical analysis methods for the detection of counterfeit or falsified drugs have been developed using spectroscopic techniques.
In this study, different spectrometers were used to collect near-infrared (NIR) and Raman spectral data sets of selected drugs to help improve existing methods. The objective of this work was to evaluate the qualitative performances of the NIR and Raman spectrometers; two benchtop equipment (NIR and Raman) and four handheld ones (three Raman and one NIR) were used. In particular, we made a critical comparison in the evaluation of the accuracy of the prediction.
The predictive ability of the different equipments was compared statistically using chemometrics: clustering algorithm, soft modeling (DD-SIMCA) and hard modeling (PLS-DA).
All these chemometric strategies were applied on each equipment. Clustering approaches, DD-SIMCA and PLSDA enabled us to compare the qualitative performances of handheld NIR and Raman equipment and to make a critical analysis of their use in the field of the detection of falsified drugs.