Integrated counter current separation and omics approaches for discovery of bioactive compounds from medicinal plants

Medicinal plants provide an important source of structurally varied bioactive metabolites with medicinal potential; however, their effective extraction, characterization, and standardization present considerable analytical challenges. Counter-current separation (CCS) methods, such as centrifugal partition chromatography (CPC) and high-speed counter-current chromatography (HSCCC), represent advanced liquid-liquid chromatographic approaches that minimize irreversible adsorption of samples. A systematic literature search was performed in PubMed/MEDLINE, Scopus, Web of Science Core Collection, ScienceDirect and Google Scholar using pre-defined search terms related to counter-current separation, six omics domains, artificial intelligence/machine learning, molecular networking, network pharmacology, regulatory systems, and industrial translation. We screened relevant studies using pre-defined eligibility criteria and thematically synthesized them according to methodological development, analytical integration, evidence maturity, regulatory relevance, and translational potential. These methods enable the effective purification of bioactive natural compounds, ensuring high recovery rates. Simultaneously, the development of metabolomics, transcriptomics, proteomics, genomics, lipidomics, and glycomics has significantly advanced the research on natural products, enabling detailed molecular profiling and systems-level biological interpretation. This review critically considers the use of CCS in combination with multi-omics technologies for the discovery of bioactive compounds from medicinal plants. Special attention is paid to solvent-system design, AI-aided process optimization, molecular networking, chemometric analysis, and bioactivity-guided fractionation strategies. In addition, the use of CCS in quality control, phytopharmaceutical standardization, and industrial-scale production is discussed. Integration of CCS with omics technologies, artificial intelligence (AI), and network-based analytical approaches offers a complementary platform for the enhancement of the discovery, prioritization, isolation, and characterization of bioactive natural products. These integrated workflows can facilitate candidate identification, structural characterization, mechanistic investigation and biological validation in early translational research. However, it should be kept in mind that the identification of a bioactive compound or fraction is not the same as drug discovery or therapeutic development. Further pharmacological, toxicological, pharmacokinetic, manufacturing, regulatory and clinical investigations are required for a purified natural product or botanical preparation to advance toward therapeutic development.