Analytical determination of meloxicam and tenoxicam: matrix-dependent challenges, emerging technologies, and sustainable future perspectives.

Abstract

Meloxicam (MLX) and tenoxicam (TNX) remain analytically important across pharmaceutical, biological, veterinary, and environmental applications, yet their reliable determination is strongly influenced by matrix complexity and drug-specific physicochemical behavior. This review moves beyond conventional method-centered summaries by critically comparing MLX and TNX across matrices and linking their physicochemical, pharmacokinetic, metabolic, and stability characteristics to analytical performance. Sample-preparation strategies, chromatographic and mass-spectrometric platforms, spectroscopic techniques, and electrochemical methods are evaluated for selectivity, sensitivity, matrix tolerance, robustness, sustainability, and practical applicability. Particular emphasis is placed on unresolved limitations in parent drug-metabolite-degradation product discrimination, matrix-effect control, method transferability, and harmonized validation. Importantly, the review integrates emerging chemometric optimization, artificial intelligence, machine learning, automated workflows, and Green and White Analytical Chemistry as converging directions for next-generation analysis. Future progress should shift from isolated improvements in detection sensitivity toward matrix-adaptive, digitally assisted, sustainability-aware analytical systems that integrate automated sample preparation, intelligent data interpretation, robust validation, and lifecycle-based performance assessment. This integrated perspective identifies priorities for transforming the determination of MLX and TNX from fragmented, matrix-specific methodologies into more transferable, intelligent, and sustainable analytical frameworks.