ReviewChinese medicine2026
Development and application of artificial intelligence in traditional Chinese medicine research and development.
Review in Chinese medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Beyond transparency: why Traditional Chinese Medicine (TCM) need explainable artificial intelligence (XAI).Chinese medicine · 2026Review
- Rethinking Nature's Pharmacy: AI Era and Natural Product Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Artificial Intelligence in Traditional Chinese Medicine: Unraveling Herbal Medicine's Mechanisms.Research (Washington, D.C.) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThe integration of artificial intelligence (AI) into traditional Chinese medicine (TCM) research and development offers promising solutions to longstanding challenges in the field. These challenges include the complexity of TCM formulations, variability in quality control, and hurdles in global market acceptance. The unique synergy between AI technologies and TCM principles creates opportunities to enhance research efficiency, standardization, and innovation. AIM OF REVIEW: This review aims to explore the applications and impact of AI across three critical stages of TCM development: drug design, pharmaceutical manufacturing, and market access. By summarizing the advancements and limitations in these areas, the review identifies the transformative potential of AI and proposes future directions for integrating AI with emerging technologies to advance TCM research and development (R&D). KEY SCIENTIFIC CONCEPTS OF REVIEW: AI has transformative potential in TCM development, addressing key challenges across various stages. In drug design, AI accelerates the identification of active compounds, optimizes formula composition, and models pharmacodynamic relationships to enhance innovation efficiency and precision. During pharmaceutical manufacturing, AI contributes to process optimization, quality control, and the standardization of TCM products, ensuring stable and scalable production. For market access, although no TCM developed by AI has entered the clinic, AI has played a role in comprehensive safety and efficacy assessments and simplified regulatory compliance in other drugs. By leveraging these advances and reviewing limitations, AI promotes the need to develop more integrated, more efficient, and more utilized methods in TCM R&D.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.