Shuyi Chen

Research Institute of Life Science, Jiyang College of Zhejiang A&F University, Zhuji, 311800, China
Author    Correspondence author
Biological 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

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.

Chen S.Y., 2024, Crossing disease boundaries: how ai drives rare disease drug discovery, Bioscience Evidence, 14(1): 21-28 (doi: 10.5376/be.2024.14.0003)

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.

Rare disease; Artificial intelligence (AI); Technological challenges; Data sharing