TY - JOUR
KW - Artificial intelligence
KW - Drug development
KW - Drug Discovery
KW - Humans
AU - Kang Zhang
AU - Xin Yang
AU - Yifei Wang
AU - Yunfang Yu
AU - Niu Huang
AU - Gen Li
AU - Xiaokun Li
AU - Joseph C. Wu
AU - Shengyong Yang
AB - Drug development is a complex and time-consuming endeavor that traditionally relies on the experience of drug developers and trial-and-error experimentation. The advent of artificial intelligence (AI) technologies, particularly emerging large language models and generative AI, is poised to redefine this paradigm. The integration of AI-driven methodologies into the drug development pipeline has already heralded subtle yet meaningful enhancements in both the efficiency and effectiveness of this process. Here we present an overview of recent advancements in AI applications across the entire drug development workflow, encompassing the identification of disease targets, drug discovery, preclinical and clinical studies, and post-market surveillance. Lastly, we critically examine the prevailing challenges to highlight promising future research directions in AI-augmented drug development.
BT - Nature Medicine
DA - 2025-01
DO - 10.1038/s41591-024-03434-4
IS - 1
LA - eng
N2 - Drug development is a complex and time-consuming endeavor that traditionally relies on the experience of drug developers and trial-and-error experimentation. The advent of artificial intelligence (AI) technologies, particularly emerging large language models and generative AI, is poised to redefine this paradigm. The integration of AI-driven methodologies into the drug development pipeline has already heralded subtle yet meaningful enhancements in both the efficiency and effectiveness of this process. Here we present an overview of recent advancements in AI applications across the entire drug development workflow, encompassing the identification of disease targets, drug discovery, preclinical and clinical studies, and post-market surveillance. Lastly, we critically examine the prevailing challenges to highlight promising future research directions in AI-augmented drug development.
PY - 2025
SP - 45
EP - 59
T2 - Nature Medicine
TI - Artificial intelligence in drug development
VL - 31
SN - 1546-170X
ER -