Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 25 min ago
Peer-reviewedCC BY-NC-NDSignal Transduction and Targeted Therapy

Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications

  • Yuqing Liu1,2
  • Kun Zhu3
  • Weijun Peng4,5
  • Zhaoqian Liu6,7
  • Xiaoyuan Mao8,9
9 affiliations
  1. 1Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
  2. 2National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital, Central South University, Changsha, China
  3. 3Department of Pharmacology, Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China
  4. 4Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, China. [email protected]
  5. 5National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital, Central South University, Changsha, China. [email protected]
  6. 6Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics and National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Xiangya Hospital Central South University, Changsha, China. [email protected]
  7. 7Institute of Clinical Pharmacology and Engineering Research Center of Applied Technology of Pharmacogenomics of Ministry of Education, Central South University, Changsha, China. [email protected]
  8. 8Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics and National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Xiangya Hospital Central South University, Changsha, China. [email protected]
  9. 9Institute of Clinical Pharmacology and Engineering Research Center of Applied Technology of Pharmacogenomics of Ministry of Education, Central South University, Changsha, China. [email protected]
Open at sourcePDFDOICite

Abstract

The integration of multiomics technologies with artificial intelligence (AI) has become a transformative force in modern precision medicine, particularly within drug discovery. Multiomics approaches, including genome-wide association studies, transcriptomic profiling, proteomic interaction mapping, and metabolomic sequencing, provide unparalleled insights into the molecular dynamics of disease pathogenesis. Advanced AI methodologies, which leverage deep learning architectures, exhibit extraordinary capabilities in deciphering these intricate biological datasets, elucidating latent patterns, and constructing high-fidelity predictive models. The combined application of multiomics and AI has significant potential to accelerate target identification, streamline lead optimization processes, and enhance the precision of clinical trial designs. However, challenges persist, such as the need to harmonize disparate omics data streams, ensure reproducibility, and mitigate algorithmic biases. This review offers an in-depth analysis of multiomics applications across the drug development pipeline, covering target deconvolution, drug repositioning, and de novo compound discovery. It also explores the critical role of AI in drug discovery, focusing on virtual screening, pharmacokinetic modeling, and safety assessment frameworks. The fusion of multiomics with AI provides distinct advantages in hypothesis generation and data-driven discovery, opening new pathways for therapeutic innovation. By examining cases in oncology, neurodegenerative diseases, and cardiovascular conditions supported by robust technological infrastructures, this review presents a forward-thinking vision for future drug development. The convergence of these technologies not only enables comprehensive molecular understanding but also allows for more precise therapeutic interventions, marking the beginning of a new era in bench-to-clinic translational medicine.

Related

  1. Artificial Intelligence in the Discovery and Design of Ionic Liquids for Thermal Energy Applications.
    Pawan Chhipa, Zachariah S Baird, Dinis O Abranches +1
    Journal of chemical information and modelingPeer-reviewedCC BYFull textMaterials & polymersEurope PMC
  2. Integrating Artificial Intelligence Into Drug Discovery From Medicinal Plants: Current Applications and Infrastructural Challenges
    Amit Gangwal, Azim Ansari, Mohd Usman Mohd Siddique +3
    Chemical Biology & Drug DesignPeer-reviewedCC BY6 citedMedicinal chemistry & drug discoveryOpenAlex
  3. Integrating artificial intelligence and molecular simulation for peptide discovery: limitations, validation and decision-centered workflows
    Xu Wu, Wei Fu
    ChemRxivPreprintLicence not statedGeneral chemistryChemRxiv
  4. Artificial intelligence and machine learning-guided bio-orthogonal engineering of smart soft polymeric nanocarriers for precision drug delivery and translational nanomedicine
    Suman Basak
    Frontiers in Soft MatterPeer-reviewedCC BYFull text8 citedMaterials & polymersOpenAlex
  5. Accelerating Catalyst Discovery with Artificial Intelligence Using Molecular Dual-Atom Site Catalysts as a Case Study
    Denis Savchenko, Bruno Ina cio da Silva Roux Leite, Timmo-Henrik Pukk +3
    ChemRxivPreprintCC BYFull textMaterials & polymersChemRxiv

Cite

BibTeXRIS
BibTeX
@article{liu2026multiomics,
  title = {{Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications}},
  author = {Yuqing Liu and Kun Zhu and Weijun Peng and Zhaoqian Liu and Xiaoyuan Mao},
  journal = {Signal Transduction and Targeted Therapy},
  year = {2026},
  month = jun,
  doi = {10.1038/s41392-026-02631-6},
  url = {https://doi.org/10.1038/s41392-026-02631-6},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications
AU  - Yuqing Liu
AU  - Kun Zhu
AU  - Weijun Peng
AU  - Zhaoqian Liu
AU  - Xiaoyuan Mao
PY  - 2026
DA  - 2026/06/02
JO  - Signal Transduction and Targeted Therapy
DO  - 10.1038/s41392-026-02631-6
UR  - https://doi.org/10.1038/s41392-026-02631-6
AB  - The integration of multiomics technologies with artificial intelligence (AI) has become a transformative force in modern precision medicine, particularly within drug discovery. Multiomics approaches, including genome-wide association studies, transcriptomic profiling, proteomic interaction mapping, and metabolomic sequencing, provide unparalleled insights into the molecular dynamics of disease pathogenesis. Advanced AI methodologies, which leverage deep learning architectures, exhibit extraordinary capabilities in deciphering these intricate biological datasets, elucidating latent patterns, and constructing high-fidelity predictive models. The combined application of multiomics and AI has significant potential to accelerate target identification, streamline lead optimization processes, and enhance the precision of clinical trial designs. However, challenges persist, such as the need to harmonize disparate omics data streams, ensure reproducibility, and mitigate algorithmic biases. This review offers an in-depth analysis of multiomics applications across the drug development pipeline, covering target deconvolution, drug repositioning, and de novo compound discovery. It also explores the critical role of AI in drug discovery, focusing on virtual screening, pharmacokinetic modeling, and safety assessment frameworks. The fusion of multiomics with AI provides distinct advantages in hypothesis generation and data-driven discovery, opening new pathways for therapeutic innovation. By examining cases in oncology, neurodegenerative diseases, and cardiovascular conditions supported by robust technological infrastructures, this review presents a forward-thinking vision for future drug development. The convergence of these technologies not only enables comprehensive molecular understanding but also allows for more precise therapeutic interventions, marking the beginning of a new era in bench-to-clinic translational medicine.
SN  - 2059-3635
SN  - 2095-9907
ER  -