RESUMEN
A new spectral library-based approach that is capable of screening a diverse set of finished drug products using only an active pharmaceutical ingredient spectral library is described in this paper. This approach obviates the need for a comprehensive drug product library, thereby streamlining the use of spectral library-based tests for anti-counterfeiting efforts, specifically to target finished drug products containing the wrong active ingredient or no active ingredient at all. Both laboratory-based and portable spectrometers are used in the study to demonstrate the usefulness and transferability of the spectral correlation method for field screening. The spectral correlation between the active pharmaceutical ingredient and finished drug product spectra is calculated using both full spectral analysis and targeted spectral regions analysis of six types of antimalarial, antibiotic and antiviral products. The spectral regions were determined using a moving window spectral correlation algorithm, and the use of specific spectral regions is shown to be crucial in screening finished drug products using only the active pharmaceutical ingredient spectrum. This comprehensive screening spectral correlation method is tested on seven different validation samples from different manufacturers as those used to develop the method, as well as simulated counterfeits which were prepared to mimic falsified drugs containing no active ingredient. The spectral correlation method is successful in correctly identifying 100% of the authentic products and simulated counterfeit samples tested.
Asunto(s)
Antiinfecciosos/análisis , Medicamentos Falsificados/análisis , Espectrometría Raman/métodos , Algoritmos , Antibacterianos/análisis , Antibacterianos/química , Antiinfecciosos/química , Antimaláricos/análisis , Antimaláricos/química , Antivirales/análisis , Antivirales/química , Química Farmacéutica/métodos , Medicamentos Falsificados/química , Procesamiento de Señales Asistido por Computador , Tecnología Farmacéutica/métodosRESUMEN
A new second-derivative variance minimization (SDVM) procedure is used to automatically extract spectra of a dilute component (solute) from a mixture whose spectrum is dominated by a major component (solvent). This procedure involves the subtraction of Savitzky-Golay second-derivative preprocessed pure solvent and mixture spectra by minimizing the variance of the difference spectrum. The resulting undifferentiated output spectra contain primarily features associated with the solute and/or solute-induced perturbations of the solvent. The SDVM method is found to outperform several related methods, including a previously proposed derivative minimization method, as demonstrated using 1000 randomly generated solute/solvent synthetic spectral pairs and experimental Raman spectra of dilute solutions of benzene in n-hexane and water in acetone. The former experimental solution produced SDVM difference spectra containing benzene bands with virtually no n-hexane interference, while the latter revealed water-induced shifts in acetone spectral features. Several other types of SDVM applications, such as the spectroscopic analysis of layered composites, are discussed.
RESUMEN
We have developed a method to enhance fluorescence quantification in two-dimensional gel electrophoresis using the inherent Raman scattering of water as an internal standard. We demonstrate this water internal standard (WIS) method using quantitative comparisons of commercially available protein standards that were either covalently tagged or passively stained with fluorescent tags. Thus, WIS opens up the possibility of enhancing intra- and intergel quantitative comparisons.