From static compromise to dynamic design: a polarity modulation paradigm for multiclass veterinary drug residue analysis in complex foods.

The determination of multiclass veterinary drug residues in food is fundamentally constrained by the irreconcilable conflict between the extremely broad polarity of analytes and the dynamic, heterogeneous nature of complex matrices. Current mainstream sample preparation methods typically rely on static, compromise-driven conditions that limit optimal recovery for polarity-extreme compounds. This review articulates a paradigm shift by establishing the "Dynamic Polarity Window" (DPW) as a framework for rational design. Unlike static methods, DPW enables programmable polarity adjustment across pretreatment stages to match analyte-specific requirements. We critically evaluate conventional techniques through this polarity-centric lens and synthesize a toolkit of programmable strategies-encompassing solvent engineering, salting-out, pH/temperature levers, and microenvironment control-guided by physicochemical parameters. This framework enables the transition from passive, universal extraction to active, on-demand separation, enhancing selectivity and robustness. We finally outline key future directions to bridge the prediction-experiment gap, develop sustainable solvents, and integrate automation for robust residue analysis.