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Analysis of Solid Formulates Using UV-Visible Diffused Reflectance Spectroscopy with Multivariate Data Processing Based on Net Analyte Signal and Standard Additions Method

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  • معلومة اضافية
    • بيانات النشر:
      MDPI AG, 2024.
    • الموضوع:
      2024
    • Collection:
      LCC:Biochemistry
    • نبذة مختصرة :
      Quality control in pharmaceutical manufacturing necessitates rigorous testing and approval, adhering to Current Good Manufacturing Practices before commercialization. The production of solid drugs presents significant industrial challenges regarding uniformity, homogeneity, and consistency. Traditional quality guidelines rely on classical analytical methods such as liquid chromatography coupled with mass spectrometry. However, the emergence of Process Analytical Technology introduced non-destructive, rapid, and cost-effective methods like UV-Visible Diffuse Reflectance Spectroscopy. The present study aimed to develop a chemometric method for quantifying Active Pharmaceutical Ingredients (APIs) in Neo Nisidine®, a solid mixture drug, using spectrophotometric data. The Net Analyte Signal (NAS) method, combined with standard additions, allowed the creation of a pseudo-univariate standard addition model, overcoming some challenges in solid-phase analysis. Successful quantifications of APIs in ideal laboratory samples and real pharmaceutical tablets were obtained. NAS-based chemometric models showed high precision and reliability, whose results were validated by comparisons with HPLC ones. The study revealed that solid-phase spectrophotometric analyses can be considered a valid alternative to API analyses. Solid-phase analysis offers non-destructive, cost-effective, and environmentally friendly benefits, enabling its integration into pharmaceutical production to improve quality control.
    • File Description:
      electronic resource
    • ISSN:
      2227-9040
    • Relation:
      https://www.mdpi.com/2227-9040/12/11/227; https://doaj.org/toc/2227-9040
    • الرقم المعرف:
      10.3390/chemosensors12110227
    • الرقم المعرف:
      edsdoj.b567c2df22904bebbeeaf4f5e353b568