A Green analytical method for simultaneous determination of dexamethasone sodium phosphate and prednisolone acetate in veterinary formulations using UV spectroscopy and dimension reduction algorithms.

Precise determination of veterinary pharmaceutical concentrations represents a critical foundation for delivering safe and efficacious animal healthcare interventions. Two synthetic glucocorticoids - dexamethasone sodium phosphate (DXM) and prednisolone acetate (PRD) - are extensively employed in veterinary medicine due to their potent anti-inflammatory capabilities. Our research presents a novel, cost-effective, and environmentally sustainable analytical methodology that enables simultaneous quantification of DXM and PRD within binary veterinary formulations. The method synergistically combines UV spectroscopy with dimension reduction algorithms (DRAs), representing a significant advancement in pharmaceutical analysis. A comprehensive evaluation of seventeen DRAs was conducted using four distinct performance metrics: mean squared error (MSE), mean absolute error (MAE), median absolute error (MedAE), and coefficient of determination (R²). Among the assessed algorithms, mini-batch sparse principal component analysis demonstrated superior predictive accuracy for this specific analytical challenge. The developed method was validated using the accuracy profile approach, yielding results that confirm its satisfactory accuracy. An ecological impact assessment was conducted using five greenness evaluation tools: the Green Solvent Selection Tool (GSST), National Environmental Methods Index (NEMI), Green Certificate modified Eco-Scale, carbon footprint analysis, and the Modified GAPI (MoGAPI). In addition, whiteness was evaluated with Red-Green-Blue 12 (RGB 12) algorithms. The proposed method showed elevated GSST scores and a greener profile according to NEMI. The calculated carbon footprint was 0.0006 kg CO₂ equivalent per sample, with a Green Certificate modified Eco-Scale score of 84, a MoGAPI score of 81, and a whiteness assessment of 90.1 by the RGB12 algorithm. Statistical comparison between the proposed spectrophotometric method and a previously reported HPLC method for pharmaceutical dosage form analysis revealed no statistically significant differences at the 95 % confidence level. This study underscores the innovative combination of UV spectroscopy with dimension reduction algorithms, presenting substantial improvements over traditional UV techniques for drug analysis. This method enhances both the efficiency and accuracy of active ingredient determination in pharmaceutical dosage forms while also supporting environmental sustainability.