In-lab synthesized turn-off fluorescence sensor for estimation of Gemigliptin and Rosuvastatin polypill appraised by Spider diagram, AGREE and whiteness metrics

Abstract

AbstractGemigliptin-Rosuvastatin single-pill combination is a promising therapeutic tool in the effective control of hyperglycemia and hypercholesterolemia. Organic sensors with high quantum yields have profoundly significant applications in the pharmaceutical industry, such as routine quality control of marketed formulations. Herein, the fluorescence sensor, 2-Morpholino-4,6-dimethyl nicotinonitrile 3, (λex; 226 nm, λem; 406 nm), was synthesized with a fluorescence quantum yield of 56.86% and fully characterized in our laboratory. This sensor showed high efficiency for the determination of Gemigliptin (GEM) and Rosuvastatin (RSV) traces through their stoichiometric interactions and simultaneously fractionated by selective solvation. The interaction between the stated analytes and sensor 3 was a quenching effect. Various experimental parameters and the turn-off mechanism were addressed. The adopted approach fulfilled the ICH validation criteria and showed linear satisfactory ranges, 0.2–2 and 0.1–1 μg/mL for GEM and RSV, respectively with nano-limits of detection less than 30 ng/mL for both analytes. The synthesized sensor has been successfully applied for GEM and RSV co-assessment in their synthetic polypill with excellent % recoveries of 98.83 ± 0.86 and 100.19 ± 0.64, respectively. No statistically significant difference between the results of the proposed and reported spectrophotometric methods in terms of the F- and t-tests. Ecological and whiteness appraisals of the proposed study were conducted via three novel approaches: the Greenness Index via Spider Diagram, the Analytical Greenness Metric, and the Red–Green–Blue 12 model. The aforementioned metrics proved the superiority of the adopted approach over the previously published one regarding eco-friendliness and sustainability. Our devised fluorimetric turn-off sensing method showed high sensitivity, selectivity, feasibility, and rapidity with minimal cost and environmental burden over other sophisticated techniques, making it reliable in quality control labs.