4 May 2016 Recognition of pharmaceuticals with compact mini-Raman-spectrometer and automized pattern recognition algorithms
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Abstract
Robust classification of pharmaceuticals in an industrial process is an important step for validation of the final product. Especially for pharmaceuticals with similar visual appearance a quality control is only possible if a reliable algorithm based on easily obtainable spectroscopic data is available. We used Principal Component Analysis (PCA) and Support Vector Machines (SVM) on Raman spectroscopy data from a compact Raman system to classify several look-alike pharmaceuticals. This paper describes the data gathering and analysis process to robustly discriminate 19 different pharmaceuticals with similar visual appearance. With the described process we successfully identified all given pharmaceuticals which had a significant amount of active ingredients. Thus automatic validation of these pharmaceuticals in a process can be used to prevent wrong administration of look-alike drugs in an industrial setting, e.g. patient individual blistering.
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Hendrik Jähme, Hendrik Jähme, Giuseppe Di Florio, Giuseppe Di Florio, Valeria Conti Nibali, Valeria Conti Nibali, Cemal Esen, Cemal Esen, Andreas Ostendorf, Andreas Ostendorf, Markus Grafen, Markus Grafen, Erich Henke, Erich Henke, Jens Soetebier, Jens Soetebier, Carsten Brenner, Carsten Brenner, Martina Havenith, Martina Havenith, Martin R. Hofmann, Martin R. Hofmann, } "Recognition of pharmaceuticals with compact mini-Raman-spectrometer and automized pattern recognition algorithms", Proc. SPIE 9899, Optical Sensing and Detection IV, 98992M (4 May 2016); doi: 10.1117/12.2228070; https://doi.org/10.1117/12.2228070
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