创新链/学科链/研发链/产业链

新药研发前沿动态 / 医药领域趋势进展

梁礼, 邓成龙, 张艳敏, 滑艺, 刘海春, 陆涛, 陈亚东. 人工智能在药物发现中的应用与挑战[J]. 药学进展, 2020, 44(1): 18-27.
引用本文: 梁礼, 邓成龙, 张艳敏, 滑艺, 刘海春, 陆涛, 陈亚东. 人工智能在药物发现中的应用与挑战[J]. 药学进展, 2020, 44(1): 18-27.
LIANG Li, DENG Chenglong, ZHANG Yanmin, HUA Yi, LIU Haichun, LU Tao, CHEN Yadong. Application and Challenges of Artificial Intelligence in Drug Discovery[J]. Progress in Pharmaceutical Sciences, 2020, 44(1): 18-27.
Citation: LIANG Li, DENG Chenglong, ZHANG Yanmin, HUA Yi, LIU Haichun, LU Tao, CHEN Yadong. Application and Challenges of Artificial Intelligence in Drug Discovery[J]. Progress in Pharmaceutical Sciences, 2020, 44(1): 18-27.

人工智能在药物发现中的应用与挑战

Application and Challenges of Artificial Intelligence in Drug Discovery

  • 摘要: 新药研发存在周期长、费用高和成功率低等特点。人工智能技术是近些年来的热点技术之一,在很多领域都有非常广泛的应用,多种人工智能方法已经成功应用于药物的发现过程。综述总结了常用机器学习方法和深度学习方法在药物研发领域中的应用,同时也提出了人工智能存在的问题和面临的挑战。整体而言,人工智能技术在药物研发领域发展潜力巨大,将为医药发展带来新的机遇和希望。

     

    Abstract: The development of new drugs usually requires a long time and huge cost with low rate of success. Artificial intelligence (AI), which is one of the hottest technologies in recent years, has been widely used in many fields. A variety of AI-based methods have been successfully applied to the discovery of drugs. This paper summarizes the applications of common machine learning and deep learning methods in the field of drug research and development, and raises the problems and challenges for artificial intelligence. With its great potential in the field of drug research and development, artificial intelligence will bring new opportunities and promising future for the development of medical and pharmaceutical sciences.

     

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