Abstract
Raman spectroscopy has become an attractive tool for the analysis of pharmaceutical solid dosage forms. In the present study it is used to ensure the identity of tablets. The two main applications of this method are release of final products in quality control and detection of counterfeits. Twenty-five product families of tablets have been included in the spectral library and a non-linear classification method, the Support Vector Machines (SVMs), has been employed. Two calibrations have been developed in cascade: the first one identifies the product family while the second one specifies the formulation. A product family comprises different formulations that have the same active pharmaceutical ingredient (API) but in a different amount. Once the tablets have been classified by the SVM model, API peaks detection and correlation are applied in order to have a specific method for the identification and allow in the future to discriminate counterfeits from genuine products. This calibration strategy enables the identification of 25 product families without error and in the absence of prior information about the sample. Raman spectroscopy coupled with chemometrics is therefore a fast and accurate tool for the identification of pharmaceutical tablets.
Introduction
Vibrational spectroscopy encompasses near-infrared (NIR), mid-infrared (MIR) and Raman spectroscopy. Aided by relentless instrumentation advances, the Raman techniques have now entered common use for the study of solid-state samples [1], [2]. Raman spectroscopy has thus found many applications in the pharmaceutical industry such as polymorphism screening, solid-state analysis, quantitative determination of active pharmaceutical ingredient (API) content [3] and distribution of API in tablets by Raman mapping [4], [5]. Moreover Raman spectroscopy can be used in a laboratory for quality control application but also for on-line analysis [6] and for process analytical technology projects [7].
In this paper a method is proposed to identify pharmaceutical tablets by Raman spectroscopy. The objective of the study is, in case of release analyses of products in quality control, to ensure the identity of the samples. Classical analytical tools have so far been used for the identification of pharmaceutical drugs and counterfeits: liquid chromatography [8], high performance liquid chromatography [9], nuclear magnetic resonance [10] or recently near-infrared (NIR) spectroscopy [11], [12], [13], [14] and near-infrared imaging [15]. Raman spectroscopy is a fast technique compared to other techniques such as classical chromatography. Indeed, in less than 1 min, a sample can be analyzed. Contrary to NIR spectra, Raman spectra of tablets have the advantage of revealing API specific peaks.
The present paper describes the calibration strategy developed for an automatic identification of the tablets produced by the firm in Basel, which represents 25 product families. The classification determines the product family. Moreover acceptance criteria like API peak detection and correlation with the database spectra are applied. No prior information about the sample is needed to identify correctly its product family as long as the product type is part of the database. For some of the products, the formulation can even be automatically identified.
Section snippets
Pharmaceutical samples
In this study, 25 different product families have been analyzed and initially 44 formulations have been measured. A product family comprises different formulations that have the same API in different amounts. Depending on the concentration of API in the tablets, the excipients may have different concentrations within the same product family. The chemical composition of excipients can also slightly differ from one formulation to another.
For each formulation, five batches were selected and for
Spectral interpretation
API specific peaks can be detected in Raman spectra of tablets observed in Fig. 1. The spectra of two tablets of the same product family have been displayed together with the spectrum of their common API, the first tablet containing 24% of API and the second one a higher dosage (32%). The API can clearly be observed on the spectra of both tablets.
The API content of some tablets is very low. In Fig. 2A the detection of API by Raman can be evaluated by observing the spectra of increasing
Conclusions
A new scheme for the identification of tablets by Raman spectroscopy has been proposed in this paper. The presented method is specific and fast regarding the measurement and the automatic generation of a result. Even close chemically related structures like benzodiazepines could be distinguished. The method is also robust and effective. This innovative calibration strategy first consists in the determination of the product family name and then of the formulation of the samples when available.