OptiSyn: an interpretable, multi-omics–driven graph convolutional network framework for synergy-oriented drug combination design in disease treatment

The suggested AI-driven formula design approach provides new insights into combinatorial therapy approaches for AS while also conforming to the TCM theory of Jun-Chen-Zuo-Shi principle. The significant potential of combining contemporary bioinformatics and AI techniques with traditional medicine is demonstrated by this study, which could facilitate efficient and mechanistically informed disease therapy.

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Publication Details

Journal
Chinese Medicine
Published
2026-03-24
DOI
https://doi.org/10.1186/s13020-026-01385-1
Primary Topic
Medicinal Plant Pharmacodynamics Research
Type
article
Field-Weighted Citation Impact
0.00
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article

OptiSyn: an interpretable, multi-omics–driven graph convolutional network framework for synergy-oriented drug combination design in disease treatment

Chinese Medicine
Medicinal Plant Pharmacodynamics Research
article

OptiSyn: an interpretable, multi-omics–driven graph convolutional network framework for synergy-oriented drug combination design in disease treatment

article en

Abstract

The suggested AI-driven formula design approach provides new insights into combinatorial therapy approaches for AS while also conforming to the TCM theory of Jun-Chen-Zuo-Shi principle. The significant potential of combining contemporary bioinformatics and AI techniques with traditional medicine is demonstrated by this study, which could facilitate efficient and mechanistically informed disease therapy.

Chinese MedicineVol. 21(1)
Fujian University of Traditional Chinese Medicine (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), China Academy of Chinese Medical Sciences (CN)
Good health and well-being
Openalex Percentile: Top 9%
Medicinal Plant Pharmacodynamics Research
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