[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fmUNJwfy2IS1PzIosjpy0gC_Jk-4wZaXn-_nhOFiGBGw":3},{"code":4,"msg":5,"data":6},200,"操作成功",{"id":7,"title":8,"content":9,"digest":10,"source":10,"coverPath":11,"thumbsCoverPath":12,"isTop":13,"isShow":14,"baseClick":13,"clickCount":15,"createTime":16,"typeId":17,"isNewest":18,"newsInfoTypeRespVo":19,"voiceUrl":22,"voiceSize":23,"taskId":24,"releaseTime":25,"titleEn":26,"contentEn":27,"voiceUrlEn":28,"taskIdEn":29,"voiceSizeEn":30},1208,"AI如何参与制药？","\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\">近期，人工智能在制药领域的应用引起广泛关注，“AI制药”被认为可能会彻底改变药物发现和开发流程，并已在资本市场引发热潮。2024年上半年，全球AI制药融资有69起，投资额33.36亿美元。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">当前，全球AI制药领域吸引了谷歌、微软和亚马逊等科技巨头入局，同时头部药企辉瑞、强生、阿斯利康、默沙东都在积极布局相关研发领域。截至目前，中国AI制药企业也已超过百家。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">传统制药领域有个“双十定律”，即研发费用10亿美元，研发周期10年。最新数据显示，全球范围创新药平均研发成本约26亿美元。药企在高投入的同时，还得面临新药在临床试验阶段失败的高风险。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">新药研发是一个复杂且耗时的过程，一般分为几个主要阶段。药物发现阶段包括以下步骤，一是确定与疾病相关的生物分子或通路；二是找到能够与目标分子相互作用的候选药物；三是对初步筛选出的化合物进行优化。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">药物发现后，是新药的临床前研究、临床研究、监管审批，以及上市后监测。\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\">AI可以参与的就是药物发现阶段，通过归纳推理优化药物研发，利用算力加速筛选优化先导化合物。并且AI在后期流程也能发挥作用。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">目前，AI工具在药物发现阶段已取得一些成果。例如，谷歌旗下DeepMind的AlphaFold工具，通过预测蛋白质的三维结构，显著提高了药物发现效率。它利用深度学习算法，在分子生物学领域带来突破。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">实践表明，AI在药物筛选和优化中确实具有潜力，可大幅缩短药物发现过程，通过训练模型提高筛选成功率。当前多家科技巨头看好AI制药领域，它们的投资不仅推动了技术发展，还促进了AI技术在药物开发中的应用。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">2022年1月，工业和信息化部等九部门联合印发的《“十四五”医药工业发展规划》提到，要探索人工智能、云计算、大数据等技术在研发领域的应用，通过对生物学数据挖掘分析、模拟计算，提升新靶点和新药物发现效率。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">尽管AI在某些方面表现出色，但技术成果转化仍存在障碍。截至目前，还没有完全由AI研发的新药物成功进入市场。一方面是因为AI技术本身还处于发展阶段；另一方面还是前文所述的药物研发极为复杂，仍有很大不确定性。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(187, 187, 187);\">【新闻来源】中国经济周刊 \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Fai%E5%A6%82%E4%BD%95%E5%8F%82%E4%B8%8E%E5%88%B6%E8%8D%AF\u002Far-AA1KgdwD?ocid=msedgntphdr&cvid=67764a46dd014287b627707a75cbb518&ei=26\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">http:\u002F\u002Fu5a.cn\u002FtaeKx\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（本网转发此文章，旨在为读者提供更多的信息资讯，所涉内容不构成投资、消费建议。文章事实如有疑问，请与有关方核实，文章观点非本网观点，仅供读者参考。）\u003C\u002Fspan>\u003C\u002Fp>","","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002F6defc68741e744209280f2cb63e878ac\u002FAI领域.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fthumbs\u002F6defc68741e744209280f2cb63e878ac\u002FAI领域.jpg",0,1,205,"2025-08-12 17:36",2,false,{"id":17,"name":20,"enName":21},"芯位视野","Xinwei Vision","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3A122631ae-10ed-4470-b3c5-9b1b0411ff89%3A0.wav?Expires=1754998879&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=mghDxceq7EZc282yaFr%2Fj30Uvbg%3D",4916370,"122631ae-10ed-4470-b3c5-9b1b0411ff89","2025-08-12 17:30","How can AI participate in drug development?","\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\">Recently, the application of artificial intelligence in the pharmaceutical field has attracted widespread attention. \"AI drug development\" is considered to be able to completely change the process of drug discovery and development, and has already sparked a craze in the capital market. In the first half of 2024, there were 69 AI drug development financing cases with an investment of 3.336 billion US dollars.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Currently, the global AI drug development field has attracted tech giants such as Google, Microsoft, and Amazon, while top pharmaceutical companies such as Pfizer, Johnson & Johnson, AstraZeneca, and Merck are also actively investing in related R&D areas. As of now, Chinese AI drug development companies have exceeded one hundred.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">The traditional pharmaceutical industry has a \"double ten rule,\" meaning that the research and development cost is 1 billion US dollars, and the research and development cycle is 10 years. The latest data shows that the average R&D cost for innovative drugs globally is about 2.6 billion US dollars. While pharmaceutical companies invest heavily, they also face a high risk of failure in the clinical trial stage of new drugs.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Drug development is a complex and time-consuming process, generally divided into several main stages. The drug discovery phase includes the following steps: first, identify the biological molecules or pathways related to the disease; second, find candidate drugs that can interact with the target molecule; third, optimize the compounds initially screened out.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">After drug discovery, comes preclinical research, clinical research, regulatory approval, and post-market monitoring of the new drug.\u003C\u002Fspan>\u003Cstrong style=\"font-size: 18px;\">What AI can participate in is the drug discovery phase, optimizing drug R&D through inductive reasoning, accelerating the screening and optimization of lead compounds by utilizing computing power. Moreover, AI can also play a role in later processes.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Currently, AI tools have achieved some results in the drug discovery phase. For example, the AlphaFold tool from DeepMind, a subsidiary of Google, significantly improves the efficiency of drug discovery by predicting the three-dimensional structure of proteins. It uses deep learning algorithms and brings breakthroughs in the field of molecular biology.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Practical experience shows that AI indeed has potential in drug screening and optimization, which can greatly shorten the drug discovery process and improve the success rate of screening by training models. Currently, many technology giants are optimistic about the AI drug development field. Their investments not only promote technological development but also promote the application of AI technology in drug development.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">In January 2022, the \"14th Five-Year Plan for the Pharmaceutical Industry Development\" issued by nine departments including the Ministry of Industry and Information Technology mentioned that it is necessary to explore the application of technologies such as artificial intelligence, cloud computing, and big data in the R&D field. By mining and analyzing biological data and simulating calculations, it aims to improve the efficiency of discovering new targets and new drugs.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\">Although AI performs well in some aspects, there are still obstacles to the transformation of technological achievements. Up to now, no completely AI-developed new drug has successfully entered the market. On one hand, because AI technology itself is still in the development stage; on the other hand, as mentioned earlier, drug development is extremely complex, and there is still great uncertainty.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(187, 187, 187);\">[News Source] China Economic Weekly \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.msn.cn\u002Fzh-cn\u002Fnews\u002Fother\u002Fai%E5%A6%82%E4%BD%9C%E5%8F%82%E4%B8%8E%E5%88%B6%E8%8D%AF\u002Far-AA1KgdwD?ocid=msedgntphdr&cvid=67764a46dd014287b627707a75cbb518&ei=26\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">http:\u002F\u002Fu5a.cn\u002FtaeKx\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（This article is reprinted by this website to provide readers with more information. The content does not constitute investment or consumption advice. If there are any questions about the facts in the article, please verify with the relevant parties. The views in the article are not the views of this website and are for reference only.）\u003C\u002Fspan>\u003C\u002Fp>","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3A932fdc66-a58e-4f23-b9fd-95e92a99515f%3A0.wav?Expires=1774838499&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=qigZRGQVWeqOzHLXcRAcoEw0H2Y%3D","932fdc66-a58e-4f23-b9fd-95e92a99515f",7051704]