JOURNAL ARTICLE

DoE Screening and Optimization of Liquid Chromatographic Determination of Nicotinic Acid and Six Statins: Application to Pharmaceutical Preparations and Counterfeit Detection.

  • Published In: Journal of Chromatographic Science, 2023, v. 61, n. 1. P. 74 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Salem, Wadhah Atef; Elkady, Ehab Farouk; Fouad, Marwa Ahmed; Mohammad, Mohammad Abdul-Azim 3 of 3

Abstract

The article focuses on the development and validation of an isocratic reversed-phase high-performance liquid chromatography (RP-HPLC) method for the simultaneous determination of nicotinic acid (NIA) and six statins—pravastatin sodium (PRS), rosuvastatin calcium (ROS), atorvastatin calcium (ATS), pitavastatin calcium (PIS), lovastatin sodium (LOS), and simvastatin sodium (SIS)—with an emphasis on detecting counterfeit drugs in pharmaceutical and traditional herbal medicines (THM). Using design of experiment (DOE) methodologies, including Plackett–Burman and Box–Behnken designs, the method was optimized and validated according to International Conference on Harmonization guidelines, demonstrating high sensitivity, accuracy, precision, and robustness. Application of the method revealed substandard ATS content in an Indian pharmaceutical product and the presence of unlabelled synthetic statins (LOS, ATS, ROS) adulterating THM samples from India and China, highlighting public health risks associated with counterfeit and adulterated medicines. The study provides a comprehensive analytical approach for screening, confirming, and quantifying counterfeit dyslipidemia drugs in both pharmaceutical and herbal products.

Additional Information

  • Source:Journal of Chromatographic Science. 2023/01, Vol. 61, Issue 1, p74
  • Document Type:Article
  • Subject Area:Consumer Health
  • Publication Date:2023
  • ISSN:0021-9665
  • DOI:10.1093/chromsci/bmab131
  • Accession Number:161134743
  • Copyright Statement:Copyright of Journal of Chromatographic Science is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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