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May 9, 2026Chinese Herbal Medicines0 citationsOpen Access

From empiricism to precision: SHINE strategy in anti-fibrotic drug discovery

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WHW Z HuangZCZhaotong Cong

Key Points

  • This research investigates the effectiveness of the SHINE framework in enhancing anti-fibrotic drug discovery by integrating traditional Chinese medicine and modern technologies.
  • Proposed operationalization of the SHINE framework through tissue-directed intelligent screening and physiologically based pharmacokinetic modeling.
  • Incorporation of artificial intelligence and multi-omics technologies in the drug discovery process.
  • The SHINE framework effectively integrates traditional Chinese medicine with modern science, showing promise in accelerating drug discovery.
  • Successful application of spatial metabolomics in quantifying drug distribution parameters related to fibrotic tissues.

Abstract

Fibrosis contributes substantially to global morbidity and mortality, while approved agents such as pirfenidone and nintedanib ( Table 1 ) primarily delay disease progression rather than reverse established scarring ( King et al., 2014 ). This persistent therapeutic gap has renewed interest in alternative sources of anti-fibrotic leads. Traditional Chinese medicine (TCM) formulas represent a vast and clinically validated repository of multi-component therapies, yet conventional reductionist drug discovery paradigms have struggled to fully harness their complexity. In this context, Xin et al. propose the smart herbal-based innovation and translational engine (SHINE), an integrative framework that bridges TCM theory with artificial intelligence (AI), multi-omics technologies, and biosynthetic engineering to accelerate anti-fibrotic drug discovery ( Xin et al., 2025 ). The SHINE framework specifically operationalizes this integration through tissue-directed intelligent screening, physiologically based pharmacokinetic (PBPK) modeling, and spatial metabolomics, thereby translating the TCM concept of “meridian tropism” into quantifiable distribution parameters.

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Cite This Study

Huang et al. (2026) studied this question.

synapsesocial.com/papers/69fed03cb9154b0b82877447https://doi.org/10.1016/j.chmed.2026.05.002
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  1. 1Systems pharmacology of traditional Chinese medicine in fibrosis: From multi-target mechanisms to translational validation2026 · 1 citations
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  3. 3Network Pharmacology-Driven Sustainability: AI and Multi-Omics Synergy for Drug Discovery in Traditional Chinese Medicine2025 · 44 citations
  4. 4From skin scar to systemic fibrosis: Open Targets evidence and the limits of canonical anti-fibrotic axis-based cross-disease hypothesis (an EMB-3 in silico case)2026
  5. 5From skin scar to systemic fibrosis: Open Targets evidence and the limits of canonical anti-fibrotic axis-based cross-disease hypothesis (an EMB-3 in silico case)2026