Abstract
A new stability-indicating liquid chromatographic method was developed and validated for the estimation of glycopyrrolate in pharmaceutical formulations. A contemporary approach to analytical life-cycle management was followed to develop a robust and reliable chromatographic method. Scouted method variables such as % methanol, the strength of tetra butyl ammonium hydrogen sulfate and mobile phase flow rate were optimized using the design of experiment approach and their effect on critical quality attributes was studied. The critical quality attributes viz. retention time, theoretical plate count and symmetry factor were highly influenced by the three critical method variables. Optimum chromatography was attained on a C-18 column with a mobile phase methanol: 10 mM tetra butyl ammonium hydrogen sulfate (80:20, v/v) flowing at 1.0 mL.min-1. Chromatographic method specificity was ensured by degrading the drug forcefully. Validation studies postulated method acceptability and suitability for estimating glycopyrrolate in both bulk as well as injection formulation. Results for parameters viz. linearity (5-250 µg.mL-1), accuracy (>99%) and precision (<2%) advocated method reliability. Overall the method was reliable and of optimum quality and, possess the potential of application in routine and bio-analytical purposes.
Highlights
Analytical lifecycle management (ALM) is a novel approach which derives its basic principle from the combination of ICH guidelines Q8, Q9 and Q10 (USP, 2013)
It has several benefits over the traditional approach as it integrates validation, transfer and verification of procedure (Parr, Schmidt, 2018). This approach is divided into three stages starting with procedure design, which includes defining the analytical target profile (ATP) and critical quality attributes (CQAs)
HPLC grade methanol and analytical reagent grade tetra butyl ammonium hydrogen sulfate (TBAHS), hydrochloric acid, sodium hydroxide, hydrogen peroxide were used for the purpose
Summary
Analytical lifecycle management (ALM) is a novel approach which derives its basic principle from the combination of ICH guidelines Q8, Q9 and Q10 (USP, 2013). It has several benefits over the traditional approach as it integrates validation, transfer and verification of procedure (Parr, Schmidt, 2018). This approach is divided into three stages starting with procedure design, which includes defining the analytical target profile (ATP) and critical quality attributes (CQAs). Considering the advantages over the traditional approach and lack of analytical methods with the ALM framework, the authors decided to implement the same for the present research
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