Greenness-by-design (GbD) is an approach that integrates green chemistry principles into the method development stage of analytical processes, aiming to reduce their environmental impact. In this work, we applied GbD to a novel univariate double divisor corrected amplitude (DDCA) method that can resolve a quaternary pharmaceutical mixture in a fixed-dose polypill product. We also used a genetic algorithm as a chemometric modeling technique to select the informative variables for the analysis of the overlapping mixture. This resulted in more accurate and efficient predictive models. We used a computational approach to study the effect of solvents on the spectral resolution of the mixture and to minimize the spectral interferences caused by the solvent, thus achieving spectral resolution with minimal analytical effort and ecological footprint. The validated methods showed wide linear concentration ranges for the four components (1-30 µg/mL for losartan, 2.5-30 µg/mL for atorvastatin and aspirin, and 2.5-35 µg/mL for atenolol) and achieved high scores on the hexagon and spider charts, demonstrating their eco-friendliness.
Keywords: double divisor corrected amplitudes method; genetic algorithm; greenness by design; hexagon greenness protocol; spider chart.
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