이전|다음

스마트 디지털 전환 관점에서 본 중의약 기술 이전 현황 및 발전 경로 고찰

  • role： First author第一作者
  • Affiliation：

    Technology Cooperation Center of Traditional Chinese Medicine， China Academy of Chinese Medical Sciences， Beijing 100700， China

  • Email：zhangjie@chian-tcm.com
  • Introduction：张杰，正高级技术经理人，从事中医药技术转移研究，E-mail：zhangjie@chian-tcm.com
ZHANG Jie1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Beijing Information Science and Technology University， Beijing 102206， China

  • Email：1095441416@qq.com
  • Introduction：徐静，从事大数据与人工智能研究与应用，E-mail：1095441416@qq.com
XU Jing2*,  
  • Affiliation：

    Technology Cooperation Center of Traditional Chinese Medicine， China Academy of Chinese Medical Sciences， Beijing 100700， China

ZHENG Guangwei1,  
  • Affiliation：

    Technology Cooperation Center of Traditional Chinese Medicine， China Academy of Chinese Medical Sciences， Beijing 100700， China

ZHANG Huayu1,  
  • Affiliation：

    Technology Cooperation Center of Traditional Chinese Medicine， China Academy of Chinese Medical Sciences， Beijing 100700， China

LIU Chang1,  
  • Affiliation：

    Technology Cooperation Center of Traditional Chinese Medicine， China Academy of Chinese Medical Sciences， Beijing 100700， China

WEN Xiaoxiao1,  
  • Affiliation：

    Technology Cooperation Center of Traditional Chinese Medicine， China Academy of Chinese Medical Sciences， Beijing 100700， China

PAN Xishui1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Technology Cooperation Center of Traditional Chinese Medicine， China Academy of Chinese Medical Sciences， Beijing 100700， China

  • Email：wangbin135@139.com
  • Introduction：王斌，研究员，博士生导师，从事中医药信息学研究，E-mail：wangbin135@139.com； *
WANG Bin1*

추상적인

중의약은 중국 문명의 독특한 자원으로서, 스마트 디지털 전환 배경 하에서 기술 이전에는 중대한 기회가 존재하는 동시에 이론 체계의 복잡성, 산업 체인의 길이 및 다차원 정책 제약 등의 특수한 도전 과제에 직면하여 “고부가가치-높은 진입장벽” 역설을 형성한다. 현재 중의약 기술 이전은 “이전하기를 원하지 않음, 이전할 용기가 없음, 이전할 능력이 없음”의 ‘삼불(三不)’ 곤경에 빠져있다. 과학 연구 평가 체계와 시장 간 괴리로 인해 성과 전환율이 저조하며, 권리 소유 불명확과 준수 위험이 혁신 동력을 억제하고, 전문화된 서비스 부재가 수급 불일치를 심화시킨다. 본 논문은 중의약 기술 이전의 특수성을 체계적으로 분석하고, 수디지털화 전환을 전사적 핵심 돌파구로 제안한다. 스마트 분류 시스템, 블록체인 추적 및 인공지능(AI) 진료 모델 등 기술 융합을 통해 중약 ‘재배-생산-서비스’ 생태계를 재구성한다. 표준화 체계 측면에서는 “경험 데이터화-데이터 표준화-표준 지능화”를 추진하여 ‘삼무일전(三无一全)’ 인증 체계로 품질 신뢰 문제를 해결한다. 정책 협력은 과학기술 성과 전환 메커니즘을 최적화하고, 지식재산권 증권화 및 위험 분담 모델을 탐색하여 연구 동력을 활성화해야 한다. 국제화 전략은 ‘일대일로’ 플랫폼을 기반으로 하여 도지 약재 브랜드 및 표준 수출을 추진하고, ‘기술+문화’ 이중 구동 모델을 구축해야 한다. 향후 국가급 데이터베이스 구축, 융합 인재 양성 및 국제 표준 상호 인정을 통해 ‘과학적 지능 제조’ 신 패러다임을 형성하여 중의약 현대화 및 글로벌 건강 거버넌스에 체계적 솔루션을 제공해야 한다.

키워드

중의약; 스마트 중의약; 기술 이전; 과학기술 성과; 성과 평가

References

  1. 1.
    LAM W C，LYU A P，BIAN Z X.ICD-11：Impact on traditional Chinese medicine and world healthcare systems［J］.Pharm Med，2019，33（5）：373-377.
  2. 2.
    REDDY B，FAN A Y.Incorporation of complementary and traditional medicine in ICD-11［J］.BMC Med Inform Decis Mak，2021，21（S6）：381.
  3. 3.
    LIANG D，ZHANG H.Research on technology transfer promoting industrial upgrading and transformation［J］.Taiyuan Sci Technol，2024，45（12）：9-11.
  4. 4.
    NIU P，TAN Y.Development status and practical experience of international technology transfer and cooperation：Taking Sichuan province as an example［J］.Decis Mak Consul，2024（3）：49-52.
  5. 5.
    LI Y W，CHI Y H，ZHU M T，et al.Efficacy of Kegan Liyan oral liquid vs.Lianhuaqingwen capsules for patients with mild COVID-19：A double-blinded，randomized，controlled，non-inferiority trial［J］.Front Med，2025，12：1531370.
  6. 6.
    WANG K，GAO Y H，WANG G，et al.Network pharmacology study on the intervention mechanism of Lianhuaqingwen capsule in COVID-19 inflammation［J］.J Yantai Univ：Nat Sci Eng Ed，2022，35（4）：413-420.
  7. 7.
    WEI Z K，HAN Q，XUE Q L，et al.Analysis of quality traceability system for Chinese medicinal materials in Hebei Province［J］.Co-Oper Econom Sci，2021（2）：110-112.
  8. 8.
    CHEN J F，GUO C H，WEI W."Internet plus traditional Chinese medicine"：Reconstructing the development model of the entire industrial chain of traditional Chinese medicine［J］.China Soft Sci，2016（6）：26-38.
  9. 9.
    JIA C L，ZHAO K J，ZHANG F，et al.Construction and application of quality traceability system for Chinese medicine decoction pieces［J］.Mod Chin Med，2024，26（6）：1092-1098.
  10. 10.
    CUI T，HE J J，HE H，et al.Research on tongue image features based on deep learning［J］.J Med Inform，2024，45（7）：81-87.
  11. 11.
    LIU J Y，LAI H H，PAN B，et al.Application prospects and challenges of generative artificial intelligence in the standardization research of traditional Chinese medicine［J］.Shanghai J Tradit Chin Med，2025，59（4）：1-7，54.
  12. 12.
    CHEN Z J，PENG W Q，ZHANG D Z，et al.Application，challenges and prospects of large language models in the field of traditional Chinese medicine［J］.Med J Peking Union Med Coll Hosp，2025，16（1）：83-89.
  13. 13.
    BAI L L，ZHANG H X，PAN X L.Analysis of the development status and industrial trends of intelligent acupuncture devices［J］.Lishizhen Med Mater Med Res，2024，35（9）：2239-2243.
  14. 14.
    ZHANG C C，YANG G.Discussion on the current situation，problems and countermeasures of endangered Chinese medicinal materials management［J］.Chin J Chin Mater Med，2025，50（14）：4081-4088.
  15. 15.
    XIE Y M，WANG L X.Clinical and social value of traditional Chinese medicine research：On the transformation of scientific and technological achievements of traditional Chinese medicine［J］.J Tradit Chin Med，2015，56（24）：2079-2082.
  16. 16.
    ZHAO Y H，WANG C N，LI H J.Research on countermeasures for the transformation of scientific and technological achievements related to traditional Chinese medicine［J］.Chin Med Manag Sci，2024，14（3）：107-111.
  17. 17.
    CAI X J，TIAN N，YANG J L.Analysis of the dilemma and countermeasures in the internationalization process of Pien Tze Huang［J］.Chin Foreign Entrepreneurs，2018（21）：230.
  18. 18.
    WANG X W，ZHAO X S，TANG S S.Inhibitory effects of EGb761 on the expression of matrix metalloproteinases （MMPs） and cartilage matrix destruction［J］.Cell Stress Chaperones，2015，20（5）：781-786.
  19. 19.
    LIU W，CHENG X M，GENG D M，et al.Interpretation of SCHWABE company's Ginkgo biloba preparation patent portfolio［J］.China J Chin Mater Med，2014，39（17）：3384-3388.
  20. 20.
    LI X.Influencing factors，evolution，and strategies for improving the quality of traditional Chinese medicine patents：An empirical study based on patent invalidation cases［J］.Ann Med，2024，56（1）：2422571.
  21. 21.
    ZHANG Z H，LI R R，CHEN Y，et al.Integration of traditional，complementary，and alternative medicine with modern biomedicine：The scientization，evidence，and challenges for integration of traditional Chinese Medicine［J］.Acupunct Herb Med，2024，4（1）：68-78.
  22. 22.
    ZHANG J，ZHANG Z M.The challenges of ethical review in clinical research of traditional Chinese medicine［J］.Evid Based Complementary Altern Med，2021，2021：6754985.
  23. 23.
    RUAN J H，ZHANG W N，HU Z P.The connection between academic achievements and market demand：The role and practice of technology and innovation in knowledge transfer［J］.Edelweiss Appl Sci Technol，2024，8（6）：6165-6175.
  24. 24.
    ALKHAZALEH R，MYKONIATIS K，ALAHMER A.The success of technology transfer in the industry 4.0 era：A systematic literature review［J］.J Open Innov Technol Mark Complex，2022，8（4）：202.
  25. 25.
    SHEN C L.How to transform 600 traditional Chinese medicine achievements in one year［N］.China Sci Daily，2024-01-22（04）.
  26. 26.
    SHI S H，CHEN L X，ZHENG Y X，et al.Research on the current situation and countermeasures of patent management in traditional Chinese medicine universities from the perspective of achievement transformation：Taking 6 universities as examples［J］.Chin Univ Sci Technol，2025（3）：65-70.
  27. 27.
    ZHANG X L，CHEN Y M.WU Jiannong：Straightening the backbone of traditional Chinese medicine scientific research［J］.Chin Hosp CEO，2025，21（2）：58-59.
  28. 28.
    FANG J G.Hangzhou：Leading residents from "healthier" to "happier"［J］.China Health，2025（4）：12-14.
  29. 29.
    XINHUA NET."AI traditional Chinese medicine" prescribes！ Nanjing University of Chinese Medicine research team launches "Huanghuang Jingfang AI-assisted diagnosis and treatment system"［EB/OL］.（2025-03-14）.［2025-02-20］..
  30. 30.
    TIAN G H，QIAN K，LI X Y，et al.Can a holistic view facilitate the development of intelligent traditional chinese medicine？A survey［J］.IEEE Trans Comput Soc Syst，2023，10（2）：700-713.
  31. 31.
    LI Y L，FAN J，CHENG X L，et al.New revolution for quality control of TCM in industry 4.0：Focus on artificial intelligence and bioinformatics［J］.Trac Trends Anal Chem，2024，181（PB）：118023.
  32. 32.
    GONG A J，GUO L B，YU Y，et al.Spectrum-image dual-modality fusion empowered accurate and efficient classification system for traditional Chinese medicine［J］.Inf Fusion，2024，101：101981.
  33. 33.
    WU B，ZHANG L L，GUO Y A，et al.Research on the construction of TCM syndrome differentiation model for cancer pain based on artificial intelligence［J］.China Arch Tradit Chin Med，2025，43（3）：19-23，260.
  34. 34.
    WANG X Y，XIE Y，YANG X J，et al.Internet-based healthcare knowledge service for improvement of Chinese medicine healthcare service quality［J］.Healthcare，2023，11（15）：2170.
  35. 35.
    ZHAO W B，WANG B Y，LI S.Network pharmacology for traditional Chinese medicine in era of artificial intelligence［J］.Chin Herb Med，2024，16（4）：558-560.
  36. 36.
    LI D N，HU J，ZHANG L，et al.Deep learning and machine intelligence：New computational modeling techniques for discovery of the combination rules and pharmacodynamic characteristics of traditional Chinese medicine［J］.Eur J Pharmacol，2022，933：175260.
  37. 37.
    KE Z P，LIU M X，LIU J，et al.The application of artificial intelligence in the research and development of traditional Chinese medicine［J］.Int J Drug Discov Pharmacol，2024，3（1）：100001.
  38. 38.
    WANG Y Q，HU K F，HU C J.Application and development of systems biology in the field of computer-aided drug design［J］.Chin J Chin Mater Med，2023，48（11）：2868-2875.
  39. 39.
    FAN Z R.Exploration and thinking on the concept of ecological planting of genuine medicinal materials to promote high-quality development of rural industries［J］.Sichuan Agric Sci Technol，2024（9）：120-122.
  40. 40.
    WANG Y，GUO Y，LIU H，et al.Quantitative analysis of national medicine strategic policies towards internationalization of traditional Chinese medicine［J］.Tran Soc Sci，Edu Human Res，2023，1：151-158.
  41. 41.
    CHU X L，SUN B Z，HUANG Q C，et al.Quantitative knowledge presentation models of traditional Chinese medicine （TCM）：A review［J］.Artif Intell Med，2020，103：101810.

더 읽기

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website