Literature DB >> 26514627

QbD-Based Development and Validation of a Stability-Indicating HPLC Method for Estimating Ketoprofen in Bulk Drug and Proniosomal Vesicular System.

Nand K Yadav1, Ashish Raghuvanshi2, Gajanand Sharma3, Sarwar Beg4, Om P Katare4, Sanju Nanda5.   

Abstract

The current studies entail systematic quality by design (QbD)-based development of simple, precise, cost-effective and stability-indicating high-performance liquid chromatography method for estimation of ketoprofen. Analytical target profile was defined and critical analytical attributes (CAAs) were selected. Chromatographic separation was accomplished with an isocratic, reversed-phase chromatography using C-18 column, pH 6.8, phosphate buffer-methanol (50 : 50v/v) as a mobile phase at a flow rate of 1.0 mL/min and UV detection at 258 nm. Systematic optimization of chromatographic method was performed using central composite design by evaluating theoretical plates and peak tailing as the CAAs. The method was validated as per International Conference on Harmonization guidelines with parameters such as high sensitivity, specificity of the method with linearity ranging between 0.05 and 250 µg/mL, detection limit of 0.025 µg/mL and quantification limit of 0.05 µg/mL. Precision was demonstrated using relative standard deviation of 1.21%. Stress degradation studies performed using acid, base, peroxide, thermal and photolytic methods helped in identifying the degradation products in the proniosome delivery systems. The results successfully demonstrated the utility of QbD for optimizing the chromatographic conditions for developing highly sensitive liquid chromatographic method for ketoprofen.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Year:  2015        PMID: 26514627     DOI: 10.1093/chromsci/bmv151

Source DB:  PubMed          Journal:  J Chromatogr Sci        ISSN: 0021-9665            Impact factor:   1.618


  1 in total

1.  Application of Design of Experiments® Approach-Driven Artificial Intelligence and Machine Learning for Systematic Optimization of Reverse Phase High Performance Liquid Chromatography Method to Analyze Simultaneously Two Drugs (Cyclosporin A and Etodolac) in Solution, Human Plasma, Nanocapsules, and Emulsions.

Authors:  Syed Nazrin Ruhina Rahman; Oly Katari; Datta Maroti Pawde; Gopi Sumanth Bhaskar Boddeda; Abhinab Goswami; Srinivasa Rao Mutheneni; Tamilvanan Shunmugaperumal
Journal:  AAPS PharmSciTech       Date:  2021-05-13       Impact factor: 3.246

  1 in total

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