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Design and implementation strategies for rare disease clinical research in the digital intelligence era

Published on Aug. 29, 2025Total Views: 41 times Total Downloads: 11 times Download Mobile

Author: SUN Fengyu 1, 2# CAO Borui 3# CHEN Nana 4 ZHONG Xinwen 4 HOU Yan 4 PENG Zhihang 2, 5

Affiliation: 1. Center for Drug Evaluation of the National Medical Products Administration, Beijing 100076, China 2. Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China 3. School of Statistics, Capital University of Economics and Business, Beijing 100070, China 4. Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China 5. National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, China

Keywords: Rare diseases Clinical research Digital intelligence Artificial intelligence Study design

DOI: 10.12173/j.issn.1005-0698.202502099

Reference: SUN Fengyu, CAO Borui, CHEN Nana, ZHONG Xinwen, HOU Yan, PENG Zhihang. Design and implementation strategies for rare disease clinical research in the digital intelligence era[J]. Yaowu Liuxingbingxue Zazhi, 2025, 34(8): 908-916. DOI: 10.12173/j.issn.1005-0698.202502099.[Article in Chinese]

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Abstract

Clinical research on rare diseases has always faced multiple challenges in clinical research design and implementation due to small sample sizes of patients, high heterogeneity, and limited research resources. The rapid development of digital intelligence technology has provided innovative solutions for rare disease research. This article systematically explores the current status and response strategies of clinical research on rare diseases in the digital intelligence age. On the one hand, the efficiency of rare disease research has been optimized through adaptive design, mixed trial mode, and precision medicine stratification methods. On the other hand, solutions based on digital technology have been proposed to address the practical challenges of recruitment difficulties and underrepresentation of rare disease clinical research patients, data management and technical barriers, and insufficient coverage of natural medical history and baseline databases through digital intelligence technology. By combining international collaboration, intelligent screening, and remote experiments, a multidisciplinary collaboration and international cooperation, adaptive design, digital data platform, and patient-centered remote research model have been constructed as the core implementation strategies. Typical cases demonstrate that digital intelligence technology not only effectively shortens the drug development cycle, but also significantly enhances patient benefits, providing a replicable practical paradigm for global rare disease research. The practice of digital platforms represented by the International Rare Disease Research Alliance and the China Rare Disease Diagnosis and Treatment Collaboration Network has further verified the feasibility and promotional value of the digitalization path. In summary, digital intelligence technology has shown considerable promise in overcoming the clinical research challenges of rare diseases and accelerating the development of treatment plans, providing systematic references for researchers, regulatory agencies, and patient organizations. It is expected to drive the clinical research of rare diseases towards a more efficient and accurate future.

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