A Survey of Large Language Model for Drug Research and Development

Drug research and development (drug R&D) is a sophisticated, cost-intensive, and time-consuming procedure with historically low success rates. The advent of Artificial Intelligence (AI) technologies has introduced innovative methods into drug R&D, particularly by leveraging AI...

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Main Authors: Huijie Guo, Xudong Xing, Yongjie Zhou, Wenjiao Jiang, Xiaoyi Chen, Ting Wang, Zixuan Jiang, Yibing Wang, Junyan Hou, Yukun Jiang, Jianzhen Xu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10930479/
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author Huijie Guo
Xudong Xing
Yongjie Zhou
Wenjiao Jiang
Xiaoyi Chen
Ting Wang
Zixuan Jiang
Yibing Wang
Junyan Hou
Yukun Jiang
Jianzhen Xu
author_facet Huijie Guo
Xudong Xing
Yongjie Zhou
Wenjiao Jiang
Xiaoyi Chen
Ting Wang
Zixuan Jiang
Yibing Wang
Junyan Hou
Yukun Jiang
Jianzhen Xu
author_sort Huijie Guo
collection DOAJ
description Drug research and development (drug R&D) is a sophisticated, cost-intensive, and time-consuming procedure with historically low success rates. The advent of Artificial Intelligence (AI) technologies has introduced innovative methods into drug R&D, particularly by leveraging AI capabilities. Large language models (LLMs), a breakthrough in generative AI, have revolutionized drug discovery. With their extensive datasets, numerous parameters, and strong multitasking abilities, LLMs have significantly improved efficiency across various related domains, providing unparalleled support to drug R&D. These models have facilitated a deeper understanding of intricate disease mechanisms and the identification of novel therapeutic strategies, ushering in a new era in drug development and clinical applications. As a result, the advancement of LLMs is poised to drive significant transformations in drug R&D, emphasizing the importance of effectively leveraging this technology. This review provides insights into the architecture and characteristics of LLMs, explores their applications in drug R&D, and highlights their research implications in bioinformatics data, including proteins, genes, and chemical compounds. Furthermore, it investigates the practical strategies of LLMs in drug discovery, drug repositioning, and clinical inquiries, presenting an innovative approach to research and future advancements in this field.
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spelling doaj-art-29c2862f905047c2812ec982defb461e2025-08-20T01:50:33ZengIEEEIEEE Access2169-35362025-01-0113511105112910.1109/ACCESS.2025.355225610930479A Survey of Large Language Model for Drug Research and DevelopmentHuijie Guo0https://orcid.org/0009-0005-9967-4316Xudong Xing1https://orcid.org/0000-0002-3081-1694Yongjie Zhou2Wenjiao Jiang3Xiaoyi Chen4Ting Wang5Zixuan Jiang6Yibing Wang7Junyan Hou8Yukun Jiang9Jianzhen Xu10Information Construction Management Office, China Pharmaceutical University, Nanjing, Jiangsu, ChinaState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, ChinaCollege of Science, China Pharmaceutical University, Nanjing, Jiangsu, ChinaCenter for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, ChinaCollege of Science, China Pharmaceutical University, Nanjing, Jiangsu, ChinaState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, ChinaState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, ChinaState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, ChinaState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, ChinaState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, ChinaCollege of Science, China Pharmaceutical University, Nanjing, Jiangsu, ChinaDrug research and development (drug R&D) is a sophisticated, cost-intensive, and time-consuming procedure with historically low success rates. The advent of Artificial Intelligence (AI) technologies has introduced innovative methods into drug R&D, particularly by leveraging AI capabilities. Large language models (LLMs), a breakthrough in generative AI, have revolutionized drug discovery. With their extensive datasets, numerous parameters, and strong multitasking abilities, LLMs have significantly improved efficiency across various related domains, providing unparalleled support to drug R&D. These models have facilitated a deeper understanding of intricate disease mechanisms and the identification of novel therapeutic strategies, ushering in a new era in drug development and clinical applications. As a result, the advancement of LLMs is poised to drive significant transformations in drug R&D, emphasizing the importance of effectively leveraging this technology. This review provides insights into the architecture and characteristics of LLMs, explores their applications in drug R&D, and highlights their research implications in bioinformatics data, including proteins, genes, and chemical compounds. Furthermore, it investigates the practical strategies of LLMs in drug discovery, drug repositioning, and clinical inquiries, presenting an innovative approach to research and future advancements in this field.https://ieeexplore.ieee.org/document/10930479/Large modelartificial intelligencetransformerdrug research and development
spellingShingle Huijie Guo
Xudong Xing
Yongjie Zhou
Wenjiao Jiang
Xiaoyi Chen
Ting Wang
Zixuan Jiang
Yibing Wang
Junyan Hou
Yukun Jiang
Jianzhen Xu
A Survey of Large Language Model for Drug Research and Development
IEEE Access
Large model
artificial intelligence
transformer
drug research and development
title A Survey of Large Language Model for Drug Research and Development
title_full A Survey of Large Language Model for Drug Research and Development
title_fullStr A Survey of Large Language Model for Drug Research and Development
title_full_unstemmed A Survey of Large Language Model for Drug Research and Development
title_short A Survey of Large Language Model for Drug Research and Development
title_sort survey of large language model for drug research and development
topic Large model
artificial intelligence
transformer
drug research and development
url https://ieeexplore.ieee.org/document/10930479/
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