Comparative AI-optimized HPLC-DAD strategy for the simultaneous determination of ranolazine, amlodipine, and diltiazem with pharmacotherapeutic relevance and multi-trait sustainability assessment.

A robust and reliable HPLC–DAD method was developed and validated for the simultaneous determination of ranolazine, diltiazem, and amlodipine, a drug combination relevant to the concurrent management of chronic angina and hypertension. Preliminary screening of chromatographic conditions was supported by an AI-assisted platform and subsequently refined through conventional experimental optimization. The proposed method was successfully applied to bulk materials and combined dosage forms. It was further extended to spiked rat plasma to verify its applicability for monitoring ranolazine in the presence of co-administered diltiazem and amlodipine. Chromatographic separation was achieved on a C18 column using an isocratic mobile phase consisting of buffer (pH 5), acetonitrile, and methanol (60:30:10, v/v) at a flow rate of 1.0 mL/min. The developed method provided efficient separation with satisfactory peak symmetry and resolution under optimized conditions. The AI-assisted predictions showed good agreement with experimentally optimized parameters, supporting their utility as a preliminary tool to guide method development. The method was validated in accordance with established guidelines, demonstrating satisfactory linearity, accuracy, precision, and selectivity within the studied concentration range. The analytical performance and environmental impact were evaluated and compared with previous methods using the Multi-Color Assessment tool, yielding an overall Whiteness Score of 64.8% overwhelming the other reported methods. In addition, the alignment of the AI-optimized method with sustainability principles was assessed using the Need, Quality, and Sustainability tool and compared with conventional optimization. The results demonstrate that the proposed method provides a reliable and environmentally considerate analytical approach for the simultaneous quantification of the studied drug combination in pharmaceutical formulations with demonstrated applicability in biological matrices.