This review focuses on the advancements in integrated multi-omics techniques for drug-target identification. It highlights the shift from single-omics to multi-omics approaches due to the limitations of single-omics in fully explaining complex causal relationships between drugs and phenotypes. The review covers the development history of omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, and their roles in drug-target identification. It discusses the integration of these omics data through correlation and enrichment analyses, emphasizing the importance of multi-omics in understanding biological processes and regulatory mechanisms. The review also explores classical multi-omics integration methods, such as integrating transcriptome and proteomics, transcriptome and metabolomics, and proteomics and metabolomics. Additionally, it introduces single-cell multi-omics technology, which provides more detailed insights into cell heterogeneity and functional differences, and spatial multi-omics, which localizes gene expression within tissues. The review concludes by discussing the challenges and future prospects of multi-omics analyses in drug-target identification, particularly in the context of transcriptome and proteome integration.This review focuses on the advancements in integrated multi-omics techniques for drug-target identification. It highlights the shift from single-omics to multi-omics approaches due to the limitations of single-omics in fully explaining complex causal relationships between drugs and phenotypes. The review covers the development history of omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, and their roles in drug-target identification. It discusses the integration of these omics data through correlation and enrichment analyses, emphasizing the importance of multi-omics in understanding biological processes and regulatory mechanisms. The review also explores classical multi-omics integration methods, such as integrating transcriptome and proteomics, transcriptome and metabolomics, and proteomics and metabolomics. Additionally, it introduces single-cell multi-omics technology, which provides more detailed insights into cell heterogeneity and functional differences, and spatial multi-omics, which localizes gene expression within tissues. The review concludes by discussing the challenges and future prospects of multi-omics analyses in drug-target identification, particularly in the context of transcriptome and proteome integration.