Bempedoic acid (BEM), a drug used to lower cholesterol levels in patients with atherosclerosis. Controlling its process-related impurities is crucial due to their potential toxicity. This study details the development of a RP-HPLC method for the analysis of four process-related substances in BEM. To ensure robust chromatographic performance meeting six sigma quality standards, the method was optimized using a combined approach of response surface methodology (specifically, an I-optimal design) and tolerance analysis, integrating predefined specifications for critical method attributes such as resolution, tailing factor, and number of theoretical plates into the developmental process. Chromatographic separation was achieved using a C18 column. The mobile phase consisted of 0.1 % phosphoric acid in water and acetonitrile, utilizing a stepped gradient elution profile. The flow rate was maintained at 0.9 mL/min, with UV detection performed at 210 nm. The column temperature was set to 20 °C. The method demonstrated linearity for BEM process related impurities in the range of LOQ to 30 μg mL−1. The method ability to differentiate the drug substance from its degradation products was confirmed through forced degradation study. The environmental sustainability of the developed method was assessed using multiple Green Analytical Chemistry (GAC) tools. The National Environmental Methods Index (NEMI) showed two green-shaded quadrants, and the Green Certificate modified Eco-scale awarded a score of 70. The Complementary Green Analytical Procedure Index (Complex GAPI) confirmed the method environmentally friendly profile. Additionally, The AGREE tool generated a score of 0.77, indicating strong overall greenness, while the AGREEprep tool, focused on sample preparation, yielded a score of 0.54. Other tools such as the Sample Preparation Metric of Sustainability (SPMS) and the HPLC Environmental Assessment Tool (HPLC-EAT) scored 8.42 and 569, respectively, further demonstrating the method green credentials. This robust and environmentally conscious analytical framework offers significant potential for application in quality control of BEM.
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