Article(id=1308816766172754368, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308816657934541639, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2025-1370, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1763481600000, receivedDateStr=2025-11-19, revisedDate=1765382400000, revisedDateStr=2025-12-11, acceptedDate=null, acceptedDateStr=null, onlineDate=1789975833695, onlineDateStr=2026-09-21, pubDate=1768147200000, pubDateStr=2026-01-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789975833695, onlineIssueDateStr=2026-09-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789975833695, creator=13701087609, updateTime=1789975833695, updator=13701087609, issue=Issue{id=1308816657934541639, tenantId=1146029695717560320, journalId=1189982191388893191, year='2026', volume='61', issue='1', pageStart='1', pageEnd='320', issueExtLink='null', onlineDate='null', pubDate='1768147200000', pubDateStr='2026-01-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789975807888, creator='13701087609', updateTime=1789984282344, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308852202421191556, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308816657934541639, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308852202421191557, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308816657934541639, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=157, endPage=162, ext={EN=ArticleExt(id=1308816766386663874, articleId=1308816766172754368, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Research approach for discovering active molecules in classic traditional Chinese medicine formulas based on the "originating from clinic-returning to clinic" strategy, columnId=1190335348648547107, journalTitle=Acta Pharmaceutica Sinica, columnName=Reviews, runingTitle=null, highlight=null, articleAbstract=

Analyzing the molecular mechanisms of classic traditional Chinese medicine (TCM) formulas is essential for interpreting TCM principles through modern scientific frameworks, and serves as a cornerstone for establishing dominant disease categories of TCM. However, the lack of correlation with disease progression characteristics and clinical efficacy has become a scientific issue in this field that requires urgent resolution. To address this issue, this paper employs the classic formulas "Yuquan Pill" and "Xiaoke Prescription" for the treatment of "Xiaoke", a dominant disease in TCM, as a demonstration. Adhering to an "originating from clinic-returning to clinic" strategy, omics integrated with generative artificial intelligence is employed to identify active molecules and their biological associations in the formula, thereby uncovering integrated feature PANEL of disease progression and outcomes. This approach bridges the "clinical-basic" gap, enabling the characterization of emergent pharmacodynamic features that arise from metabolic network oscillations and chaotic dynamics. It reveals the synergistic principles of active molecules and their biological mechanisms in classic formulas. Returning to clinical practice, the focus is on validating the active molecules and discovering novel multi-component formulas with superior efficacy to that of classical formulas. This approach establishes a new paradigm for clearly elucidating and comprehensively clarifying the complex active molecules in classic TCM formulas.

, authors=Ying ZHANG¹, Zhen-zhen LIU², Ai-ting WANG¹, Jiang-lan LONG², Hao Lܳ, Ke-jun DENG^{3, *}, Hao LIN^{3, *}, Dan YAN^{1, 2, *}, authorsList=Ying ZHANG, Zhen-zhen LIU, Ai-ting WANG, Jiang-lan LONG, Hao LÜ, Ke-jun DENG, Hao LIN, Dan YAN, authorCompany=null, correspAuthors=Ke-jun DENG, Hao LIN, Dan YAN, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2026 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1308816768467038666, articleId=1308816766172754368, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=“源于临床-归于临床”策略发现经典名方作用分子的研究思路, columnId=1190335349655180086, journalTitle=药学学报, columnName=综述, runingTitle=null, highlight=null, articleAbstract=

经典名方作用分子解析, 是注重现代科学解读中医药学原理的重要命题, 也是构筑中医优势病种的重要基石。然而, “缺乏关联疾病演变特征、缺乏关联临床疗效”, 已成为该领域亟待解决的科学问题。为此, 以中医优势病种“消渴”与经典名方“玉泉丸”、“消渴方”为示范, 遵循“源于临床-归于临床”策略, 利用融入生成式人工智能的生命组学, 从临床切入识别经典名方作用分子及其生物关联, 挖掘疾病演变与转归的整合特征PANEL; 以此联通“临床-基础”, 剖析基于代谢网络振荡与混沌的药效涌现特征, 揭示经典名方作用分子协同规律及其生物机制; 回归临床验证其作用分子并发现药效优于经典名方的多成分新复方; 构建“说明白、讲清楚”经典名方作用分子的研究新范式。

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