New approaches to identification and characterization of tioconazole in raw material and in pharmaceutical dosage forms / 药物分析学报
Journal of Pharmaceutical Analysis
; (6): 40-48, 2019.
Article
em Zh
| WPRIM
| ID: wpr-744106
Biblioteca responsável:
WPRO
ABSTRACT
Tioconazole (TCZ), a broad-spectrum antifungal agent, has significant activity against Candida albicans and other Candida species, and therefore, it is indicated for the topical treatment of superficial mycoses. The main goal of this work is to report an exhaustive identification and characterization procedure to improve and facilitate the online quality control and continuous process monitoring of TCZ in bulk material and loaded in two different dosage forms ovules and nail lacquer. The methodologies were based on thermal (differential scanning calorimetry (DSC), melting point, and thermogravimetry (TG)), spectroscopic (ultraviolet (UV), Raman, near infrared (NIR), infrared spectroscopy coupled to attenuated total reflectance (FTIR-ATR), and nuclear magnetic resonance (NMR)), microscopic and X-ray diffraction (XRD). The TCZ bulk powder showed a high crystallinity, as observed by XRD, with a particles size dis-tribution (3–95 mm) resolved by microscopic measurements. TCZ melting point (82.8℃) and a de-gradation peak centered at 297.8 ℃ were obtained by DSC and DTG, respectively. An unambiguous structure elucidation of TCZ was obtained by mono- and two- dimensional 1H and 13C NMR spectral data analysis. The FTIR-ATR, Raman and NIR spectra of both the raw material and the commercial products were analyzed and their characteristic bands were tabulated. The best methods for TCZ identification in ovules were DSC, TG, XRD, NIR and Raman, while NIR and FTIR-ATR were the most appropriate tech-niques to analyze it in the nail lacquer. DSC, TG, DRX, Raman, FTIR-ATR and NIR spectroscopy are effective techniques to be used in online process analysis, because they do not require sample preparation, and they are considerably sensitive to analyze complex samples.
Texto completo:
1
Base de dados:
WPRIM
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
Zh
Revista:
Journal of Pharmaceutical Analysis
Ano de publicação:
2019
Tipo de documento:
Article