Omics approaches, such as (meta) genomics for DNAs, transcriptomics for RNAs, proteomics for proteins, metabolomics for small hydrophilic compounds, and lipidomics for tiny lipophilic molecules, all aim to assess the entire composition of a particular biochemical group. Recent advancements in medical research and our understanding of biological systems have been made possible by omics, a high-throughput method for comprehending the genome, transcriptome, proteome, and metabolome. Advanced omics methods have been used to research numerous cancer immunotherapies, including multi-omics, single-cell omics, and conventional omics. These initiatives may enhance researchers' capacity to weigh the advantages and disadvantages of taking part in extensive trials of herbal remedies. The evolution of prostate cancer, the onset of diabetes, or the prognosis of survival from sepsis are just a few examples of how metabolic profile can be utilised to provide information regarding the cause, diagnosis, or progression of a disease. Systems biology methods called OMICS, which integrate data from genomes, transcriptomics, proteomics, and metabolomics, are frequently used to fully reflect the molecular profiles in mechanistic studies of medicinal plants. The omics methods, including genomes, transcriptomics, proteomics, and metabolomics, are at the forefront of high-throughput approaches. Genomes, transcriptomes, proteomes, metabolomes, and other omics datasets produced from different MPs have been described, and associated bioinformatic databases and tools have been created. For examining MPs, integrated analysis of multi-omics datasets is incredibly thorough. Results from multi-omics datasets offer a theoretical foundation for stable biotransformation of desired secondary metabolites using synthetic biology, as well as a platform for developing MP species with high yield, good quality, and disease resistance through molecular breeding.