Smart dual-wavelength UV-vis spectroscopic method and smartphone-based RGB method for the rapid quantification of pyronaridine tetraphosphate: integration with the SDG approach

Abstract

The proposed study is based on the development of the UV-vis spectrum of pyronaridine tetraphosphate by AI, attention-based recurrent neural networks, DFT and in-lab experiments. This novel smart method was developed using water to maintain greenness, and the area under the curve was measured at two peak maxima, 260 and 425 nm. The synergy of greenness, analytical performance and AI makes this smart analytical spectroscopic method suitable for the study of pyronaridine tetraphosphate. A new smartphone-based method was also developed on the basis of RGB values. The PhotoMetrix PRO software was used to develop the vector RGB-based method. Both methods were validated as per ICH Q2(R1) guidelines. The greenness of the computational assessment of pyronaridine tetraphosphate was conducted using AGREE, GAPI, AGSA and CaFRI. The blueness, redness, clickness and whiteness were assessed by BAGI, RAPI, CACI and RGB 12. The proposed study shows the development of two new methods, namely, the smart UV-vis spectroscopic method and a smartphone-based RGB method. Both the methods align with the SDG goals, which benefits industries and the environment.