Development of RP-HPLC method for determination of amlodipine besylate, metoprolol succinate and telmisartan by integration of box-behnken design and greenness-blueness assessment tools

In this research work, a robust, Box-Behnken design-assisted reversed-phase liquid chromatography (RPLC) has been optimized for the quantification of Amlodipine Besylate, Metoprolol Succinate and Telmisartan followed by validation of method. Method is developed by utilizing Shimadzu LC-2010C HT HPLC system, autosampler injector and photodiode array detector. The separation was attained utilizing C18 (5 mu m, 250 x 4.6 mm), Phenomenex column as stationary phase. Optimized mobile phase was methanol/50 mM ammonium phosphate buffer adjusted to pH 3.5 (65:35%v/v). Detection wavelength set for estimation was 230 nm, and flow rate of mobile phase optimized was 1 ml/min. Box-Behnken design as a part of Analytical Quality by Design approach was used for optimization considering the critically influencing method attributes, flow rate (ml/min), molar concentration of buffer (mM) and buffer solution volume (ml) that resulted in optimized chromatographic conditions. The linearity exhibited a linear response within a range of 2-10 mu g/mL, 19-95 mu g/mL and 16-80 mu g/mL (correlation coefficient: 0.9988, 0.9983 and 0.9972) for Amlodipine Besylate, Metoprolol Succinate and Telmisartan, respectively. The analytical method exhibited appropriate precision and accuracy considering the RSD values as less than 2% and mean recoveries in the range of 99.99-101.00% for all three drugs. Validation was ensured in compliance with ICH Q2 (R1) in terms of method's sensitivity, accuracy, robustness and appropriate linearity for Amlodipine Besylate, Metoprolol Succinate and Telmisartan. Environmental impact evaluation of the developed method was conducted through the utilization of various software such as complex GAPI, AGREE and BAGI confirming that the optimized method was ecologic and environmentally safe. The method has been efficient in every parameter with accurate sustainability, simplicity, sensitivity and reproducibility.