Application of NIR chemometric methods for quantification of the crystalline fraction of warfarin sodium in drug product. (2nd April 2016)

• Record Type: Journal Article
• Authors: Korang-Yeboah, Maxwell; Akhtar, Sohail; Siddiqui, Akhtar; Rahman, Ziyaur; Khan, Mansoor A.
• Is Part Of: Drug development and industrial pharmacy. Volume 42:Number 4(2016:Apr.)
• Page Start: 584
• Page End: 594
• Publication Date: 2016-04-02
• Subjects: Amorphous warfarin sodium -- amorphous quantification -- chemometrics -- crystalline warfarin sodium -- near infrared spectroscopy -- partial least square -- principal component; Pharmaceutical chemistry -- Periodicals; Pharmaceutical industry -- Periodicals; Drug Industry -- Periodicals; Technology, Pharmaceutical -- Periodicals; 615.05
• DOI: 10.3109/03639045.2015.1058817
• Languages: English
• ISSNs: 0363-9045

Abstract

Abstract: Monitoring of the physical state of warfarin sodium (WS) in products is essential for minimizing product quality variability in order to ensure consistent clinical performance. This study reports the development of chemometric models for quantifying the crystalline and amorphous fractions of WS in commercial drug products using NIR spectroscopy. Formulations based on commercially available products with different API to excipient ratio were used for the study. For each content, two formulations containing either lactose monohydrate or lactose anhydrous as the predominant formulation excipient were prepared. Two formulations containing either 100% amorphous WS (AWS) or crystalline WS (CWS) were prepared and mixed in various ratios to obtain sample matrices containing AWS/CWS 0–100%. The uniformity of the samples was confirmed by near infrared chemical imaging. Data were mathematically pretreated by multiplicative signal correction and Savitzky–Golay second derivative. Principal component regression and partial least square regression models were developed from mathematically treated data. All the models showed linear trend for amorphous and crystalline fractions of the WS as indicated by correlation and R 2 > 0.99 and >0.98, respectively. The models demonstrated good performance parameters with a low-root mean squared error, standard error and bias. The model predicted CWS and AWS contents were in very close agreement with the actual values. The study indicated the utility of NIR chemometric methods in quantification of the crystalline and/or amorphous fraction of WS in its products.