AI制药产业发展瓶颈和对策  

作　　者：郭旭 王钤[1] 

机构地区：[1]中国医学科学院药用植物研究所,北京100193

出　　处：《中国科技产业》2023年第7期47-49,共3页Science & Technology Industry of China

基　　金：北京市科学技术委员会2022年技术转移建设专项(编号:20220481071)。

摘　　要：近年来,随着人工智能(AI)技术的不断成熟,其应用范围已扩展到图像识别、自动驾驶、城市管理以及新药研发领域,特别是AI辅助新药研发几乎是参与了从药物靶点发现到临床试验全流程。在新冠疫情期间,多款新药问世的背后也都有AI的贡献。传统药企、科技巨头及互联网新贵纷纷入局“AI制药”赛道。而AI制药在给药物研发带来变革的同时,其本身的发展也面临着很多瓶颈和问题。在后疫情时代,我国如何利用在AI领域已经取得的竞争优势,在AI制药的细分赛道上,实现对传统医药强国的弯道超车,需要产业主管部门在政策上,教育培训机构在人才供给上给与全方位的支持。In recent years,with the continuous maturity of artificial intelligence(AI)technology,its application scope has expanded to the fields of image recognition,autonomous driving,urban management,and new drug research and development.Especially,AI assisted new drug research and development has almost participated in the entire process from drug target discovery to clinical trials.During the COVID-19 pandemic,there were also contributions from AI behind the emergence of multiple new drugs.Traditional pharmaceutical companies,technology giants,and internet upstarts have all entered the"AI pharmaceutical"track.While AI Pharmaceuticals has brought changes to drug research and development,its own development also faces many bottlenecks and problems.In the post pandemic era,how does China utilize the competitive advantages it has already gained in the AI field to surpass traditional pharmaceutical powers in the segmented tracks of AI Pharmaceuticals?It requires comprehensive support from industry regulatory authorities in policies and education and training institutions in talent supply.

关 键 词：人工智能(AI) 制药 药物靶点 

分 类 号：F426.72[经济管理—产业经济] TP18[自动化与计算机技术—控制理论与控制工程]