Analysis of the global registration status of clinical trials for artificial intelligence medical device_Journal of Biomedical Engineering

Authors：

LU Yan , CHEN Juan , ZHANG Ting , YAN Shu , XU Dongzi ,  OUYANG Zhaolian

Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020, P. R. China;

Corresponding author：

OUYANG Zhaolian, Email: zoeouyang@163.com

Keywords：

Artificial intelligence medical device; Clinical trial; Clinical research trends; International collaboration; Bibliometric analysis

DOI：

10.7507/1001-5515.202408035

Video：

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The rapid development of artificial intelligence technology is driving profound changes in medical practice, particularly in the field of medical device application. Based on data from the U.S. clinical trials registry, this study analyzes the global registration landscape of clinical trials involving artificial intelligence-based medical devices, aiming to provide a reference for their clinical research and application. A total of 2 494 clinical trials related to artificial intelligence medical devices have been registered worldwide, with participation from 66 countries or regions. The United States leads with 908 trials, while for other countries or regions, including China, each has fewer than 300 trials. Germany, the United States, and Belgium serve as central hubs for international collaboration. Among the sponsors, 63.96% are universities or hospitals, 22.36% are enterprises, and the remainder includes individuals, government agencies and others. Of all trials, 79.99% are interventional studies, 94.67% place no restrictions on participant gender, and 69.69% exclude children. The targeted diseases are primarily neurological and mental disorders. This study systematically reveals the global distribution characteristics and research trends of artificial intelligence medical device clinical trials, offering valuable data support and practical insights for advancing international collaboration, resource allocation, and policy development in this field.

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28.	Surianarayanan C, Lawrence J J, Chelliah P R, et al. Convergence of artificial intelligence and neuroscience towards the diagnosis of neurological disorders—a scoping review. Sensors. 2023, 23(6): 3062.
29.	Calderone A, Latella D, Bonanno M, et al. Towards transforming neurorehabilitation: the impact of artificial intelligence on diagnosis and treatment of neurological disorders. Biomedicines. 2024, 12(10): 2415.
30.	Yan W J, Ruan Q N, Jiang K. Challenges for artificial intelligence in recognizing mental disorders. Diagnostics. 2023, 13(1): 2.
31.	彭亮, 刘枭寅. 人工智能医疗器械典型产品注册情况分析. 中国食品药品监管, 2024(2): 16-23.
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1. Sami F. Optimize electric automation control using artificial intelligence (AI). Optik, 2022, 271: 170085.
2. Diakiw S M, Hall J M M, VerMilyea M, et al. An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos. Reprod Biomed Online, 2022, 45(6): 1105-1117.
3. Zhou E, Shen Q, Hou Y. Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review. Front Pharmacol, 2024, 15: 1181183.
4. Suriyaamporn P, Pamornpathomkul B, Patrojanasophon P, et al. The artificial intelligence-powered new era in pharmaceutical research and development: a review. AAPS PharmSciTech, 2024, 25(6): 188.
5. Kulkarni S, Seneviratne N, Baig M S, et al. Artificial intelligence in medicine: where are we now?. Acad Radiol, 2020, 27(1): 62-70.
6. 梁宏, 王雅文. 人工智能医疗器械的临床应用现状. 医疗卫生装备, 2024, 45(2): 74-81.
7. 秦锋, 袁久洪. 人工智能在泌尿疾病诊断中的应用现状与趋势. 生物医学工程学杂志, 2020, 37(2): 230-235.
8. Woo J H, Kim E C, Kim S M. The current status of breakthrough devices designation in the United States and innovative medical devices designation in Korea for digital health software. Expert Rev Med Devic, 2022, 19(3): 213-228.
9. Lim K, Heo T Y, Yun J. Trends in the approval and quality management of artificial intelligence medical devices in the Republic of Korea. Diagnostics (Basel), 2022, 12(2): 355.
10. Beckers R, Kwade Z, Zanca F. The EU medical device regulation: implications for artificial intelligence-based medical device software in medical physics. Phys Med, 2021, 83: 1-8.
11. Park C W, Seo S W, Kang N, et al. Artificial intelligence in health care: current applications and issues. J Korean Med Sci, 2020, 35(42): e379.
12. Zinchenko V, Chetverikov S, Akhmad E, et al. Changes in software as a medical device based on artificial intelligence technologies. Int J Comput Assist Radiol Surg, 2022, 17(10): 1969-1977.
13. He J, Baxter S L, Xu J, et al. The practical implementation of artificial intelligence technologies in medicine. Nat Med, 2019, 25(1): 30-36.
14. Herington J, McCradden M D, Creel K, et al. Ethical considerations for artificial intelligence in medical imaging: data collection, development, and evaluation. J Nucl Med, 2023, 64(12): 1848-1854.
15. Ciccarelli M, Giallauria F, Carrizzo A, et al. Artificial intelligence in cardiovascular prevention: new ways will open new doors. J Cardiovasc Med, 2023, 24(Suppl 2): e106-e115.
16. Jindal A, Sumodhee D, Brandao-de-Resende C, et al. Usability of an artificially intelligence-powered triage platform for adult ophthalmic emergencies: a mixed methods study. Sci Rep, 2023, 13(1): 22490.
17. Gong E J, Bang C S, Lee J J. Edge artificial intelligence device in real-time endoscopy for classification of gastric neoplasms: development and validation study. Biomimetics. 2024, 9(12): 783.
18. Liu Y, Yu W, Dillon T. Regulatory responses and approval status of artificial intelligence medical devices with a focus on China. npj Digital Medicine, 2024, 7(1): 255.
19. Maccaro A, Stokes K, Statham L, et al. Clearing the fog: a scoping literature review on the ethical issues surrounding artificial intelligence-based medical devices. J Pers Med. 2024, 14(5): 443.
20. Fakhri F, Mohammadi M, Eybpoosh S, et al. Iran's research prioritization: are we meeting the goals? A study based on clinical trial registry data. PLoS One, 2024, 19(4): e301414.
21. Saberwal G. The need for a new keyword - "Trial registry-metaresearch" - to track certain uses of clinical trial registry records. Trials, 2023, 24(1): 190.
22. Yu T, Yang X, Clark J, et al. Accelerating evidence synthesis for safety assessment through ClinicalTrials. gov platform: a feasibility study. BMC Med Res Methodol, 2024, 24(1): 165.
23. Al-durra M, Nolan R P, Seto E, et al. Prospective registration and reporting of trial number in randomised clinical trials: global cross sectional study of the adoption of ICMJE and Declaration of Helsinki recommendations. BMJ, 2020, 369: m982.
24. 白丽娜, 苗华丽, 李婉玲, 等. 基于ClinicalTrials. gov的强直性脊柱炎临床试验注册特点研究. 中国新药杂志, 2023, 32(22): 2284-2292.
25. 张保寅, 杨文辉, 刘青蓝, 等. 基于ClinicalTrials. gov数据库的子宫内膜异位症临床研究多维度分析. 中国临床药理学与治疗学, 2024, 29(5): 520-526.
26. 王韧, 周诗洁, 郭锦材. 基于Clinicaltrials. gov平台的口腔鳞状细胞癌临床研究注册特点分析. 口腔医学研究, 2023, 39(12): 1080-1084.
27. Hsiehchen D, Espinoza M, Hsieh A. The cooperative landscape of multinational clinical trials. PLoS One, 2015, 10(6): e130930.
28. Surianarayanan C, Lawrence J J, Chelliah P R, et al. Convergence of artificial intelligence and neuroscience towards the diagnosis of neurological disorders—a scoping review. Sensors. 2023, 23(6): 3062.
29. Calderone A, Latella D, Bonanno M, et al. Towards transforming neurorehabilitation: the impact of artificial intelligence on diagnosis and treatment of neurological disorders. Biomedicines. 2024, 12(10): 2415.
30. Yan W J, Ruan Q N, Jiang K. Challenges for artificial intelligence in recognizing mental disorders. Diagnostics. 2023, 13(1): 2.
31. 彭亮, 刘枭寅. 人工智能医疗器械典型产品注册情况分析. 中国食品药品监管, 2024(2): 16-23.
32. Nelson B J, Zeng R, Sammer M B K, et al. An FDA guide on indications for use and device reporting of artificial intelligence-enabled devices: significance for pediatric use. J Am Coll Radiol, 2023, 20(8): 738-741.
33. Herington J, Mccradden M D, Creel K, et al. Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance. J Nucl Med, 2023, 64(10): 1509-1515.

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