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Master Thesis

A new combined LC (ESI+) MS/MS QTOF impurity fingerprinting and chemometrics approach for discriminating active pharmaceutical ingredient origins: example of simvastatin

Abstract : Quality monitoring of active pharmaceutical ingredient (API) used in medicinal products is of highest interest for both the pharmaceutical industry and the regulatory agencies. Therefore, a new approach combining chemometrics with API impurity profiling using high performance liquid chromatography coupled to mass spectrometry in tandem equipped with a hybrid quadrupole timeof- flight analyzer (LC-MS/MS QTOF) was examined in order to discriminate between different origins of starting materials and finished drug products. Simvastatin, a hypolipidemic agent, was chosen as test molecule for the developed method. Impurity fingerprints of forty nine samples originated from eleven distinct providers were investigated. Firstly, the LC-MS/MS QTOF trace level sensitivity (4 ng.mL-1 for simvastatin quantitation limit) enabled the identification of four new related substances. Secondly, principal component analysis, supported by hierarchical clustering analysis, was implemented to classify the various API sources. The training model, built with twenty eight observations and six variables, corresponding to six common extracted ion chromatogram peaks, explained cumulatively 92.2% of the variation, after three components, and presented a prediction coefficient of 60%. The results obtained demonstrated that the proposed approach consisting in combining singular LC-MS impurity fingerprinting with chemometric models led to unambiguously distinguish between different API suppliers.
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Master Thesis
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https://dumas.ccsd.cnrs.fr/dumas-00960820
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Dominique Hirth. A new combined LC (ESI+) MS/MS QTOF impurity fingerprinting and chemometrics approach for discriminating active pharmaceutical ingredient origins: example of simvastatin. Analytical chemistry. 2011. ⟨dumas-00960820⟩

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