Emerging Trends and Advancements in HPLC Technique: The Role of Nanotechnology, Machine Learning, and AI Optimization

High-performance liquid chromatography (HPLC) plays a central role in pharmaceutical and biomedical analysis owing to its exceptional separation efficiency, sensitivity, and versatility. It plays a crucial role in the separation, identification, and quantification of a broad range of compounds, including pharmaceuticals, endogenous biomolecules, metabolites, and biomarkers in complex biological matrices such as blood, plasma, urine, and tissue samples. Continuous advances in HPLC technique such as column technology, system configuration, and data processing have significantly expanded its separation capability, sensitivity, and efficiency. This review provides an overview of recent and emerging trends in HPLC with emphasis on multidimensional and multimodal strategies, advanced stationary-phase materials such as covalent organic frameworks, core-shell particles, and nanomaterial-modified phases. Additionally, the application of deep eutectic solvents as green and tunable mobile-phase components, and the integration of supercritical fluid chromatography as a complementary high-efficiency separation approach are discussed. Furthermore, the growing application of artificial intelligence AI and machine learning ML tools in HPLC method development and optimization is critically reviewed. This review also discusses future perspectives in HPLC, with emphasis on advances in stationary phases, miniaturization, and improved sustainability.