From Genome to Pharmacome: Current Status and Future Perspectives of Multi-Omics Integration in Traditional Chinese Medicine Research.

High-throughput sequencing and multi-omics are transforming Traditional Chinese Medicine (TCM) research from empirical descriptions toward data-driven mechanistic analyses. Unlike earlier systems pharmacology frameworks that relied primarily on static network topology and docking-based target prediction, current multi-omics approaches integrate genomic, transcriptomic, proteomic, and metabolomic data to capture dynamic, multi-scale biological responses. This review summarizes recent progress in four related areas: (i) genomic and epigenomic dissection of geo-authentic (Daodi) medicinal materials; (ii) biosynthetic pathway elucidation for major bioactive compound classes; (iii) synthetic biology platforms for heterologous production; and (iv) systems pharmacology integration for mechanism-of-action studies. We identify a central, recurrent gap: most published multi-omics analyses remain at the level of statistical association, and the biosynthetic and pharmacological pathways inferred from such data have not been validated at the causal level. To address this, we propose a tiered experimental validation framework-from biochemical target engagement through genetic perturbation to in vivo functional confirmation-and an iterative computational-experimental feedback loop. We further outline practical priorities for future work, including standardized data formats, community-endorsed metadata checklists, and coordinated DBTL pilot projects. By connecting descriptive multi-omics patterns to experimentally testable mechanistic models, TCM research can move toward precision-oriented medicine while preserving the multi-component character of traditional formulations.