Eco-friendly Nano-scale Bio-analytical Insights for Spectrofluorimetric Estimation of Fimasartan Using Integrated Approach of Enhanced Microwave-assisted Hantzsch Reaction and Multicolored Analytical Chemistry

Abstract

This study introduces an innovative spectrofluorimetric method for determining fimasartan, a pharmaceutical compound, at low concentrations in drug formulations and human blood samples. The method incorporates several key features that enhance its effectiveness and sustainability. It utilizes eco-friendly solvents (water and ethanol) and reduces analysis time, making it both cost-effective and environmentally friendly. The integration of Quality by Design (QbD) principles ensures consistent quality throughout the analytical process. The method employs a microwave-assisted Hantzsch reaction for derivatization, which modifies the compound for improved detection. To optimize critical variables, the Placket-Burman design, a statistical tool, was implemented. The method demonstrates high performance with linearity in the range of 50–250 ng/mL, a Limit of Detection (LOD) of 10 ng/mL, and a Limit of Quantification (LOQ) of 50 ng/mL. It achieves excellent accuracy, with 99.61-100.58% recovery in pharmaceutical formulations and 91.67–94.94% in human plasma. The rapid analysis time of 30 s for derivatization further enhances its efficiency. Mass spectrometry confirmation verified the formation of a fluorescent Mannich base product. Notably, this method outperforms existing LC-MS and HPLC techniques based on RGB12, AGREE, and modified-GAPI assessments, demonstrating superior environmental performance. By successfully combining analytical quality, environmental sustainability, and cost-effectiveness, this new spectrofluorimetric method presents a valuable tool for researchers and pharmaceutical professionals in the analysis of fimasartan. Its ability to provide accurate measurements at very small nano-scale concentrations while maintaining eco-friendly practices makes it a significant advancement in pharmaceutical analysis techniques.