Integrating Artificial intelligence within sustainable smart analytical chemistry for analyzing the divisor impact on UV-spectrophotometric efficiency of solifenacin and mirabegron combination

at 222 nm, while MIR exhibited linearity from 1.5 to 15.0 µg/mL at its maxima 249.0 nm. To assess the robustness and risk, cumulative validation score; CVS, was calculated, serving as instrumental sign for evaluating analytical reliability and method performance. We introduce Sustainable & Smart Analytical Chemistry (SSAC), conjoining Green Analytical Chemistry (GAC), WAC, and AI to develop analytical methods that are efficient, environmentally responsible, and consistent with the multiple Sustainable Development Goals; SDGs. The Sustainability of Analytical Methods Index (SAMI) was applied to evaluate the method's holistic alignment with the 17 SDGs. Using the Multi-Color Assessment Tool (MA), the method's greenness, realism, presentation, and novelty were evaluated, demonstrating its sustainability and global impact.