A robust high-performance thin-layer chromatography method for the simultaneous estimation of chlorthalidone and metoprolol succinate using quality risk assessment and design of experiments-based enhanced analytical quality by design approach

2021 
A precise, robust and accurate high-performance thin-layer chromatography (HPTLC) method has been developed for the simultaneous estimation of chlorthalidone and metoprolol succinate using analytical quality by design approach based on principles of quality risk management and design of experiments. The quality risk management was performed by the identification of probable method risk parameters and their assessment by allotting a risk priority number. Design of experiments was performed by Taguchi OA screening design and central composite response surface analysis using resolution between peaks as critical method performance attributes. A total of seven method risk parameters were screened for their main effect on the resolution between peaks using Design-Expert software (trial version). The main effect of three method parameters were found critical and needed to be optimised for method development. Hence, response surface analysis was done by linking the effects of critical method parameters, mobile phase composition, volume of modifier and chamber saturation time with the resolution between peaks by central composite design. Method operable design region was navigated for development of the method as per the analytical target profile. Chromatographic separation was performed using silica gel GF254 as the stationary phase and toluene‒methanol‒triethylamine (8:2:0.5, V/V) as the mobile phase in twin-trough chamber keeping saturation time of 15 min. The developed method was validated as per the International Council for Harmonisation (ICH) Q2 (R1) guideline. The developed method was applied for the assay of combined pharmaceutical dosage forms of chlorthalidone and metoprolol succinate and the results were found in good agreement with their labelled claim.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    23
    References
    2
    Citations
    NaN
    KQI
    []