Green and Rapid Quantification of Ciprofloxacin Hydrochloride and Tylosin Tartrate in Veterinary Formulation using UV Spectrophotometric Method: A Comparative Study of Nature-Inspired Algorithms for Feature Selection

Abstract

Rapid and accurate quantification of ciprofloxacin hydrochloride (CIP) and tylosin tartrate (TYZ) in veterinary formulations is crucial for ensuring product quality and therapeutic efficacy. This study introduces a green and cost-effective analytical method that combines the simplicity of UV spectrophotometry with the optimization power of nature-inspired algorithms for the simultaneous determination of CIP and TYZ in a tablet veterinary formulation. Fourteen nature-inspired algorithms were comparatively assessed using root average squared error (RASE), average absolute error (AAE), and the coefficient of determination (R²). The Corona virus optimization (CVO) algorithm and the Bat algorithm demonstrated superior performance for CIP and TYZ, respectively. The CVO algorithm, optimized for CIP, exhibited RASE, AAE, and R² values of 0.37, 0.27, and 0.998, respectively, for the calibration set, while the bat algorithm, tailored for TYZ, yielded RASE, AAE, and R² values of 0.54, 0.41, and 0.984. Test sets yielded RASE, AAE, and R² values of 0.55, 0.46, and 0.991 for CIP and 0.20, 0.15, and 0.995 for TYZ, respectively, confirming the algorithms predictive ability. Validation was performed using the accuracy profile approach. The limits of detection (LODs) were determined to be 0.86 μg mL⁻¹ for CIP and 0.36 μg mL⁻¹ for TYZ, while the limits of quantification (LOQs) were calculated as 2.88 μg mL⁻¹ for CIP and 1.21 μg mL⁻¹ for TYZ. The method environmental impact was comprehensively assessed using The Green Solvent Selection Tool (GSST), The National Environmental Methods Index (NEMI), a modified Eco-Scale, the Modified GAPI (MoGAPI), and a complementary whiteness evaluation via the RGBfast algorithm, confirming its eco-friendly profile. The proposed method demonstrated superior greenness, as reflected in its elevated GSST scores and favorable NEMI assessment. Specifically, the method achieved a modified Eco-Scale score of 84, a MoGAPI score of 81, and a whiteness index of 61, as determined by the RGBfast algorithm. These results confirm the method environmentally sustainable profile, reinforcing its suitability for green analytical applications. This novel approach offers significant advantages in terms of cost, speed, and environmental sustainability compared to conventional chromatographic techniques, paving the way for more efficient and greener analytical methods in pharmaceutical quality control. Furthermore, this study highlights the innovative integration of UV spectroscopy with nature-inspired algorithms, demonstrating significant advancements over conventional UV methodologies for pharmaceutical analysis.