Bioscience Evidence 2024, Vol.14, No.1, 16-23 http://bioscipublisher.com/index.php/be 16 Review and Progress Open Access Crossing Disease Boundaries: How AI Drives Rare Disease Drug Discovery Shunyi Chen Zhejiang Yuankang Medical Technology Co., LTD., Zhuji, 311800, China Corresponding author email: ssoy1@outlook.com Bioscience Evidence, 2024, Vol.14, No.1 doi: 10.5376/be.2024.14.0003 Received: 05 Jan., 2024 Accepted: 08 Feb., 2024 Published: 19 Feb., 2024 Copyright © 2024 Chen, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Chen S.Y., 2024, Crossing disease boundaries: how ai drives rare disease drug discovery, Bioscience Evidence, 14(1): 16-23 (doi: 10.5376/be.2024.14.0003) Abstract This article explores the challenges and prospects of using AI to advance rare disease drug discovery. With its complex genetic basis, rare diseases require precise diagnosis and personalized treatment approaches, necessitating further development of sequencing technologies, bioinformatics tools, and data analysis algorithms. Data collection and sharing pose challenges due to the limited number of rare disease patients. Collaboration and favorable policy environments are equally crucial to drive rare disease drug discovery, as international collaborative networks and supportive policies facilitate data and resource sharing and provide research and market support. Future trends include personalized medicine, application of AI technologies, and exploration of drug repurposing and combination therapies, which will drive innovation and progress in rare disease drug discovery. Keywords Rare disease; Artificial intelligence (AI); Technological challenges; Data sharing In the field of medicine, rare diseases have always been a thorny issue. Although their incidence rate in the total population is relatively low, rare diseases have brought huge social and medical challenges to patients and their families. Li et al. (2018) found that these challenges stem not only from the complexity and diversity of diseases, but also from the various difficulties in developing rare disease drugs. With the rapid development of artificial intelligence (AI) technology, new hope has been seen to overcome these challenges. Although the incidence rate of rare diseases is low, there are many kinds of rare diseases, covering a wide range of fields from genetic diseases to complex syndromes. These diseases are often accompanied by unique pathological mechanisms and clinical manifestations, making diagnosis and treatment exceptionally difficult. For many rare disease patients, the lack of effective treatment drugs and plans is the biggest challenge they face. In addition, due to the relatively small number of rare disease patients, the cost and resource investment of drug development are also greatly limited. At the same time, the rise of AI technology has brought revolutionary changes to the discovery of rare disease drugs (Chakravarty et al., 2021). AI has powerful data processing and analysis capabilities, which can extract valuable information from massive biomedical data and provide new ideas and methods for drug development. In the field of medical and health, AI has been widely applied in image recognition, disease prediction, personalized treatment, and other aspects, demonstrating a huge range of applications and potential. This study aims to explore how AI promotes the process and mechanism of rare disease drug discovery. Through in-depth research and analysis, it is hoped that the key role of AI technology in the development of rare disease drugs can be revealed, providing new ideas and methods for future drug development. At the same time, it is also hoped that this study will attract more attention and investment in the development of rare disease drugs, bringing more treatment options and hope to rare disease patients (Smith, 2022). This study not only has important scientific value, but also has profound social significance. I hope to contribute to the development of rare disease drug discovery and bring better treatment prospects to patients with rare diseases through efforts. 1 The Challenge of Discovering Rare Disease Drugs 1.1 Research and development costs and resource constraints The high cost of developing rare disease drugs is mainly due to the significant investment in clinical trials, drug production, and market promotion involved in the research and development process (Groft et al., 2021). The
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