[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f1iiL3iix-GzC8xQ0pbRC73otY7kSHmsYKrdJRvfIres":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},1420,"电信、字节跑步进场，AI制药又迎来一批新“追求者”","\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">在刚刚结束的“服贸会”上，中国电信携手拜耳、恒瑞、艾昆纬等全球知名药企共同发布“AI药物研发公共服务平台”，标志着其正式入局AI制药领域。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">几乎是在同一天，字节跳动Protenix团队在AI制药的研究上也迎来突破性进展——PXDesign系统在6个不同蛋白质靶点的实验验证中，5个靶点实现了20%～73%的纳摩尔级结合物命中率，较AlphaProteo等先进方法提升了2～6倍的性能。接连两个重磅消息，很快点燃了行业热情，使得AI制药再度站上风口。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002F17fcc95a581248c2a58495fe41a2c611\u002F176007641613600.png\" width=\"890\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">图1.国内大厂入局AI制药时间及标志性事件\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">事实上，巨头跨界AI制药并非新鲜事，在最火热的2020～2021年，腾讯、百度、阿里巴巴、华为等都先后通过各种方式率先入局。以百度为例，创始人李彦宏亲自下场，并以个人出资的形式创立百图生科，目前该企业正在全力冲击上市。腾讯的布局同样较重，不仅推出自研平台“云深智药”，另外也先后加码了数十家AI制药企业，总投入金额超过50亿元。而在这些巨头的涌入下，AI制药一时风光无两。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">据智药局不完全统计，我国AI制药企业当前已达108家，行业已正式进入“百企时代”，这带动大额BD、天价投融资事件层出不穷，比如由诺奖得主David Baker创办的AI制药公司Xaira Therapeutics，种子轮即获10亿美元支持，这无不在证明这一行业的热度。但在另一边，AI制药行业同时也在渡劫，破产、裁员、砍管线、贱卖资产等新闻频繁发生，一场“大逃杀”正在席卷整个产业。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">而在截然不同的两种行业状态下，一个疑问当前已变得愈发响亮：对于这些响当当的跨界者来说，面对AI制药当前的复杂态势，他们又该何去何从？\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">大厂为何纷纷“豪赌”AI制药？\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">2025年4月，工业软件巨头西门子宣布斥资51亿美元收购生命科学数据公司Dotmatics，以此将其工业软件业务从传统制造业加速延伸至生命科学领域，并进一步推动AI制药领域的研发与产业化落地。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002F8ba25f9143bc4ff8a7420b5f14f6c89d\u002F176007641611368200.png\" width=\"693\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">图2.英伟达一年投资8家AI制药企业，数据来源：动脉橙\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这笔天价收购很快引发了全行业关注，但这并非个例，为抢滩AI制药，巨头们几乎都表现得尤为疯狂，比如英伟达，就曾在一年内连续投资8家AI制药企业，这甚至比很多投资机构的布局还要多。以腾讯、百度为代表的国内大厂虽然相对克制，但实质上也是倾其押注，创始人亲自下场、集团资源“AII IN”的案例不在少数。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px;\">那么，透过现象看本质，巨头争先扎堆AI制药，到底图什么？\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002Ff961aad60f6245feb675168c01befc12\u002F176007641624650000.png\" width=\"668\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">图3.2019-2028年我国AI制药市场规模及增速，图片来源：头豹研究院\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">对此，动脉网总结了三点，首先第一点当然是看中了AI制药广阔的市场前景。在摩根士丹利2024年发布的一份报告中指出，AI制药的全球市场规模短期已达500亿美元，并有可能继续上探。再聚焦到国内，根据头豹研究院数据，2025—2028年我国AI制药市场规模将由12.1亿元增加至58.6亿元，年复合增速高达68.3%。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这无疑是一块巨大的蛋糕，而在其背后，实际上是AI制药被寄予颠覆传统制药流程的厚望。据悉，传统药物研发深陷“双十困局”：一款新药的研发需要十年以上，且投入的研发资金高达十亿美元，但成功率只有1%，而AI制药则有望通过智能算法将靶点发现、分子设计、临床预测等环节的周期缩短50%以上，成本压缩至数千万美元，并把Ⅱ期临床成功率从传统模式的25%～30%提升至60%～70%。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">其次是在于AI制药当前已从概念验证阶段逐步进入价值释放期，众多前沿成果呼之欲出。2025年6月，由英矽智能研发的小分子药物Rentosertib（ISM001-055）正式公布IIa期临床试验数据，71名特发性肺纤维化（IPF）患者参与的中国多中心试验显示，每日服用60mg剂量组患者肺活量平均提升98.4毫升，而安慰剂组患者肺活量下降20.3毫升，这验证了全球首款进入II期临床实验AI药物的含金量。截至目前，我国已有超过10款AI药物处于临床II期，在抗肿瘤、自身免疫、神经系统疾病等领域已展现出巨大治疗潜力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">最后一点则是基于大厂与AI制药的产业适配性。众所周知，全球头部企业的掌门人们几乎都对生物技术充满了热情，而在这之中，AI制药无疑是最适配的领域，它将生物技术与AI等信息化手段相融合，让这些大佬在陌生的行业里看到了颇为熟悉的一面，因此在跨界时更得心应手，同时也更容易将自身资源和技术转化为对AI制药赛道的精准判断与高效布局。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">事实上，AI制药的发展其实也需要这些巨头的涌入，无论是像百度、腾讯这样的互联网大厂，还是诸如华为、英伟达这类信息化硬件生产企业，他们的算法能力和硬件设施对于AI制药的推进都有举足轻重的作用。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">对此，某资深投资人谈道，“巨头跨界绝非是一朝一夕，他一定是需要满足一些既定条件，比如这个市场足够大，并且还要有极高的落地可能性，最好是还能跟自己现有的技术和资源相结合，而这些AI制药都完全契合。所以，当巨头们在跨入AI制药时，才会表现得如此激进，甚至将其作为长久的战略部署。”\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">跨界结果如何：有人要上市，有人已变现\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">2025年5月，百图生科CEO刘维对外宣称，公司计划在未来一年半左右积极谋求在香港地区实现公开上市。三个月后，AI制药领域最大一笔BD交易诞生——晶泰科技宣布与DoveTree Medicines完成总订单规模约470亿港元的管线合作签约，作为被投，腾讯将因此获得一笔不错的回报。另外在研发层面，华为、字节跳动、阿里巴巴等都已在AI制药上实现了多项突破。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">不难看出，经过过去几年的深耕与沉淀，巨头们当前在AI制药领域都已进入收获期。那么，他们究竟做对了什么，未来在AI制药上还有哪些想象空间？为解答疑问，动脉网重点选择了三家代表性企业进行了分析。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">先以百度为例，作为唯一一家单独创立AI制药企业的大厂，百图生科当前已经迈入成熟期。截至目前，百图生科在药物研发、生物制造、医疗健康等关键领域，已成功实现200多个任务模型的State-of-the-Art表现，为全球范围内的300多家用户提供了优质服务，累计收获了超过20亿美元的总客户订单，有力地助力用户在AI全新蛋白设计、AI靶点发现、AI酶设计等前沿领域取得诸多突破性成果。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">2024年10月，百图生科发布全模态生物大模型xTrimo V3，以2100亿参数量刷新全球最大规模的生命科学AI基础模型纪录。未来三年，百图生科计划将这一模型参数进一步扩展，并新增代谢组学、微生物组等模态，实现从分子到生态系统的全链条建模。对此，百图生科首席科学家李子青教授在接受媒体采访时表示，“百图正以‘基础大模型+垂直场景+开放生态’的三维战略，努力引领中国在全球生物计算竞争中占据制高点。”\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">不同于百度全身心扑在百图生科身上，腾讯在AI制药领域的布局更多元化，主要是两条腿走路：一条腿是依托于自研AI药物研发平台“云深智药（iDrug）”，另一条腿则是通过投资触角延伸AI制药全产业链。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">先说“云深智药（iDrug）”，这是腾讯推出的首个AI驱动的药物发现平台，能够将小分子药物筛选周期从数月大幅缩短至数天，目前已运行十余个药物研发项目，包括肿瘤、自免等疾病领域。另外在投资层面，截至目前，腾讯已在AI制药领域出手十余次，晶泰科技、英矽智能、信诺维、深势科技等都是其代表性标的，而通过投资，腾讯当前已形成“数据-算力-场景”的完整闭环。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在近日举行的“2025腾讯全球数字生态大会”上，腾讯AI制药技术负责人刘伟也谈到了对于未来的期待，“通过深入研究原子作用力与原子凝聚体结构，腾讯健康将让模型可适配上层各类药物研发场景，为不同模态药物研发提供基础支撑。比如在DNA和蛋白质结构预测上，腾讯将结合原子层面大模型与分子动力学模拟等计算方法，大幅提升从序列或结构预测结构效果，并将其逐步扩展到核酸药物研发以及RNA相关领域。”\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">最后再聚焦到字节跳动，相比于其他大厂，其入局时间相对较晚，但当前在AI制药领域也已兑现了诸多成果。比如在内部层面，其依托于AIDD团队自主研发的AI驱动一体化药物发现平台，当前已在肿瘤、神经疾病等领域筛选出多个具有潜力的临床前候选化合物；另外在外部合作环节，字节通过战略投资与生物科技公司深度绑定，在靶点发现和分子生成等关键环节展现出巨大潜力，已成功推动多款药物进入IND申报阶段。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002F1be5b54d73be458c9ac05f563872220f\u002F176007641639504200.png\" width=\"830\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">图4.海外大厂入局AI制药时间及标志性事件\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">当然，海外巨头们也没闲着，在AI制药领域同样收获颇丰。以谷歌为例，2025年7月，其旗下专注于药物研发的神秘机构Isomorphic Labs即将启动由AI设计的首次新药人体试验，这标志着AI制药从概念验证迈向实际应用的重要一步；同样是在7月，微软研究院AI for Science团队携手柏林自由大学、莱斯大学推出BioEmu，首次把扩散生成模型做成可规模化的“蛋白平衡系综模拟器”，单张消费级GPU跑几十分钟，就能得到过去需要超级计算机跑十万小时的蛋白动力学情报，且预测蛋白稳定性与实验误差不到1 kcal\u002Fmol。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">由此可见，在跨界AI制药这条艰难的道路上，巨头们并非只有“财大气粗”的噱头，而是带着各自的技术护城河正在向里程碑加速迈进。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">AI制药冰火两重天，跨界者还需要更多耐心\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">据动脉网不完全统计，2025年1-8月，我国AI制药领域已完成超10起BD交易，总交易金额高达300亿美元，阿斯利康、赛诺菲、礼来、辉瑞等MNC都曾先后押注。巨额资金的涌入以及头部药企的加码，无不在证明这仍然是一个充满想象力的赛道。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002F88835df890a24487a307b8974ca18ab4\u002F176007641650922700.png\" width=\"665\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">图5.2025年已完成的AI制药领域代表性BD交易\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">但在另一边，AI制药领域又在不断地传出破产、裁员、管线失败等消息，行业“泡沫”正在一个接一个戳破。2024年9月，AI制药龙头Recursion和Exscientia宣布合并，这是AI制药目前为止最大的一笔并购，但在外界看来，这场并购更像是老牌AI制药公司的抱团取暖，根据财报显示，2024年Recursion净亏损4.637亿美元，同比增长41.3%；而Exscientia在收购之前账上只有1.78亿美元，这已不足支撑其平稳度过2024年。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">而在这种“冰火两重天”的市场态势之下，实际上也是在说明，AI制药行业已经从幻想阶段走向了务实，更看重技术落地的真实价值与商业可持续性。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">对此，某专项投资人谈道，“AI制药领域正在进入一个预期过高之后的修正阶段，大家逐渐意识到，当初对AI+生命科学的想法过于乐观，这实际上是一个相当漫长的过程，而在此之前，行业不得不思考自我‘供血’的问题。于是，大家都将注意力聚焦聚焦到了在研管线的临床验证和商业变现上。”\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这意味着，一批跨界者也将迎来新的行业挑战。一方面是要更加专注于自身成果的研发和临床落地，比如要在技术上不断创新，进一步提高研发效率，或者将自身AI技术运用到更多临床场景，并加速兑现。而这都需要巨头们更高层级的重视和参与，同时也要在组织形式上做出改变。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">另一方面则是在商业环节，巨头们需要找到最适合自身的商业模式，并快速变现。据悉，目前国内AI制药公司对应的商业方向主要有三个：Biotech（创新药企）、CRO（研发外包服务机构）和SaaS（软件工具型公司），在这之中，Biotech是当下国内最主流的商业路径，即通过AI快速产生临床前管线，然后推进至临床阶段，再对外授权转让，从而获得首付款、里程碑付款和销售分成。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">2023年10月，百图生科获得赛诺菲10亿美元大单，这验证了这一商业模式的可行性，而在迈过MNC的合作门槛之后，百图生科顺势迈入增长快车道。而在BD交易持续火热的当下，不少AI制药企业都在加速向MNC展示自身能力，这对于一批跨界者来说同样如此。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">事实上，AI制药兼具了快和慢的两面性，一面是AI技术的唯快不破，另一面则是制药行业的十年磨一剑，这种矛盾性决定了AI制药行业的发展绝非易事。但挑战即机遇，对于一批跨界者来说，AI制药的黄金时代其实才刚刚拉开序幕，未来想要脱颖而出，还需要拿出更强的硬实力，以及更多的耐心。\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>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(187, 187, 187);\">【新闻来源】动脉网 \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.jiemian.com\u002Farticle\u002F13442645.html\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fwww.jiemian.com\u002Farticle\u002F13442645.html\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\u002F10\u002F026b4df5f0f0424ba3e1141d43349fb9\u002FAI领域.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002Fthumbs\u002F026b4df5f0f0424ba3e1141d43349fb9\u002FAI领域.jpg",0,1,53,"2025-10-13 22:14",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%3A857fda52-3bc6-4cce-9271-86ad40fd80a3%3A0.wav?Expires=1761124727&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=mKSYKr5mTmLtYb%2Fmz8qc3PZX%2FdU%3D",25121932,"857fda52-3bc6-4cce-9271-86ad40fd80a3","2025-10-13 22:08","Telecom, ByteDance enter the field, AI drug development again attracts a batch of new \"pursuers\"","\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">At the recently concluded \"China International Service Trade Fair\", China Telecom has jointly launched the \"AI Drug Development Public Service Platform\" with global renowned pharmaceutical companies such as Bayer, Hengrui, and IQVIA, marking its official entry into the AI drug development field.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Almost on the same day, the Protenix team of ByteDance also made breakthrough progress in AI drug development research - PXDesign system achieved hit rates of 20% to 73% at 5 out of 6 different protein target points in experimental verification, which is 2 to 6 times more efficient than advanced methods such as AlphaProteo. These two major news quickly ignited industry enthusiasm, making AI drug development once again stand at the forefront.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002F17fcc95a581248c2a58495fe41a2c611\u002F176007641613600.png\" width=\"890\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">Figure 1. Time of major domestic companies entering AI drug development and landmark events\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In fact, it's not a new thing for giants to cross over into AI drug development. During the hottest years of 2020-2021, Tencent, Baidu, Alibaba, Huawei, and others all entered the field in various ways. Taking Baidu as an example, its founder Li Yanhong personally got involved and established Baidu Biomedical Research with his own investment. The company is now fully preparing for an IPO. Tencent's layout is also quite heavy, not only launching its self-developed platform \"Yunshen Zhiyao\", but also investing in dozens of AI drug development companies, with total investment exceeding 5 billion yuan. With the influx of these giants, AI drug development was once at its peak.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">According to incomplete statistics by Zhiyaoyao, there are currently 108 AI drug development companies in China, and the industry has officially entered the \"hundred companies era\", which has led to frequent large-scale BD deals and high-value investment and financing events. For example, Xaira Therapeutics, an AI drug development company founded by Nobel laureate David Baker, received 1 billion US dollars in support in its seed round, which proves the heat of this industry. However, on the other hand, the AI drug development industry is also going through difficulties, with frequent news of bankruptcy, layoffs, pipeline cuts, and asset sales, and a \"big kill\" is sweeping through the entire industry.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Under these completely different industry conditions, a question has become increasingly loud: For these well-known cross-industry players, facing the current complex situation of AI drug development, what should they do?\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Why are big companies betting heavily on AI drug development?\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In April 2025, industrial software giant Siemens announced a $5.1 billion acquisition of life science data company Dotmatics, thus accelerating its industrial software business from traditional manufacturing to the life sciences field and further promoting R&D and industrialization in the AI drug development field.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002F8ba25f9143bc4ff8a7420b5f14f6c89d\u002F176007641611368200.png\" width=\"693\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">Figure 2. NVIDIA invested in eight AI drug development companies in one year, data source: Arterial Orange\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">This huge acquisition quickly attracted attention throughout the industry, but it is not an isolated case. In order to seize the AI drug development market, giants have shown particularly crazy behavior, for example, NVIDIA, which has invested in eight AI drug development companies within a year, even more than many investment institutions' layouts. Although domestic giants such as Tencent and Baidu are relatively restrained, they actually bet everything, with cases where founders personally get involved and the group resources \"AII IN\" being common.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px;\">So, looking beyond the phenomenon, why do giants rush into AI drug development?\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002Ff961aad60f6245feb675168c01befc12\u002F176007641624650000.png\" width=\"668\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">Figure 3. The scale and growth rate of China's AI drug development market from 2019 to 2028, data source: Head豹 Research Institute\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">According to Arterial Orange, the three points are as follows. First, of course, the AI drug development market prospects are broad. According to a report released by Morgan Stanley in 2024, the global market size of AI drug development has reached 50 billion USD in the short term and may continue to rise. Focusing on the domestic market, according to data from Head豹 Research Institute, the scale of China's AI drug development market will increase from 1.21 billion yuan to 5.86 billion yuan between 2025 and 2028, with an annual compound growth rate of as high as 68.3%.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">This is undoubtedly a huge cake, and behind it, AI drug development is expected to revolutionize the traditional drug development process. It is reported that traditional drug development is stuck in the \"double ten dilemma\": it takes more than ten years to develop a new drug, and the R&D funds required are as high as ten billion dollars, but the success rate is only 1%. However, AI drug development has the potential to shorten the cycle of target discovery, molecular design, and clinical prediction by more than 50%, reduce costs to tens of millions of dollars, and increase the II phase clinical success rate from 25% to 30% in traditional models to 60% to 70%.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Secondly, AI drug development has gradually entered the value release period from the concept verification stage, and many cutting-edge achievements are about to emerge. In June 2025, the small molecule drug Rentosertib (ISM001-055) developed by Insilico Medicine officially published IIa phase clinical trial data. A multi-center trial in China involving 71 patients with idiopathic pulmonary fibrosis (IPF) showed that the average lung capacity of patients in the 60mg dose group increased by 98.4 ml, while the lung capacity of patients in the placebo group decreased by 20.3 ml, which verified the value of the world's first AI drug entering the II phase clinical trial. As of now, there are more than 10 AI drugs in clinical II phase in China, showing great therapeutic potential in areas such as anti-tumor, autoimmune, and neurological diseases.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The last point is based on the industrial compatibility of big companies and AI drug development. As is known to all, the leaders of global top enterprises are almost all passionate about biotechnology, and among them, AI drug development is undoubtedly the most compatible field. It combines biotechnology with information technology such as AI, allowing these bosses to see a rather familiar side in an unfamiliar industry, so they can be more skilled when crossing industries, and it is also easier to convert their own resources and technology into accurate judgment and efficient layout for the AI drug development sector.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In fact, the development of AI drug development also needs the involvement of these giants. Whether it is internet giants like Baidu and Tencent or information technology hardware manufacturers such as Huawei and NVIDIA, their algorithm capabilities and hardware facilities play a crucial role in promoting AI drug development.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Regarding this, a senior investor said, \"Crossing over by giants is not a sudden event. It must meet some predetermined conditions, such as the market being large enough and having a high possibility of landing, preferably also being able to combine with their existing technology and resources. These AI drug developments completely fit. Therefore, when giants enter AI drug development, they show such an aggressive attitude, even considering it as a long-term strategic deployment.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">Cross-industry results: Some want to go public, some have already monetized\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In May 2025, CEO Liu Wei of Baidu Biomedical Research announced that the company plans to actively seek a public listing in Hong Kong within about one and a half years. Three months later, the largest BD transaction in the AI drug development field was born - BeiTech announced a pipeline cooperation agreement with DoveTree Medicines with a total order size of about 47 billion HKD. As an investment, Tencent will thus gain a good return. In addition, in terms of R&D, Huawei, ByteDance, and Alibaba have already achieved multiple breakthroughs in AI drug development.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">It is not difficult to see that after several years of deep cultivation and accumulation, the giants have now entered the harvest period in the AI drug development field. So what have they done right? What are the future possibilities for AI drug development? To answer these questions, Arterial Orange has focused on analyzing three representative companies.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Taking Baidu as an example, as the only major company that has separately established an AI drug development company, Baidu Biomedical Research has now entered a mature stage. As of now, Baidu Biomedical Research has successfully achieved state-of-the-art performance in over 200 task models in key areas such as drug development, biomanufacturing, and healthcare, providing high-quality services to more than 300 users worldwide, and has accumulated over 2 billion US dollars in total customer orders, effectively helping users achieve many breakthroughs in cutting-edge fields such as AI new protein design, AI target discovery, and AI enzyme design.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In October 2024, Baidu Biomedical Research released the full-modal biological large model xTrimo V3, setting a new record for the largest-scale life science AI foundation model globally with 210 billion parameters. Over the next three years, Baidu Biomedical Research plans to further expand the model parameters and add modalities such as metabolomics and microbiome, achieving end-to-end modeling from molecules to ecosystems. Regarding this, Professor Li Ziqing, Chief Scientist of Baidu Biomedical Research, said in an interview with the media, \"Baidu is striving to lead China to take the leading position in the global bio-computing competition with its three-dimensional strategy of 'basic large model + vertical scenarios + open ecology.'\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Unlike Baidu, which has fully devoted itself to Baidu Biomedical Research, Tencent's layout in the AI drug development field is more diversified, mainly taking two approaches: one is relying on its self-developed AI drug development platform \"Yunshen Zhiyao (iDrug)\", and the other is extending the AI drug development industry chain through investment.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">First, \"Yunshen Zhiyao (iDrug)\" is Tencent's first AI-driven drug discovery platform, which can significantly shorten the small molecule drug screening cycle from months to days. It has been running more than ten drug development projects, including the fields of tumors and autoimmune diseases. In addition, in the investment aspect, as of now, Tencent has made more than a dozen investments in the AI drug development field, with companies such as BeiTech, Insilico, Sinovac, and DeepMind being representative targets. Through investments, Tencent has currently formed a complete closed-loop of \"data - computing power - scenario\".\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">At the recent \"2025 Tencent Global Digital Ecology Conference\", Liu Wei, head of Tencent's AI drug development technology, also talked about his expectations for the future, \"By deeply studying atomic forces and atomic aggregates structures, Tencent Health will make the model adaptable to various upper-level drug development scenarios, providing foundational support for different modalities of drug development. For example, in DNA and protein structure prediction, Tencent will combine atomic-level large models with molecular dynamics simulation and other computational methods to greatly improve the effect of structural prediction from sequences or structures, and gradually expand it to nucleic acid drug development and RNA-related fields.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Finally, focusing on ByteDance, compared to other major companies, its entry time is relatively late, but it has already achieved many results in the AI drug development field. For example, internally, its AIDD team has independently developed an AI-driven integrated drug discovery platform, which has currently identified multiple promising preclinical candidate compounds in areas such as tumors and neurological diseases. In external cooperation, ByteDance has deepened its ties with biotechnology companies through strategic investments, demonstrating significant potential in key areas such as target discovery and molecular generation, and has successfully advanced multiple drugs into IND application stages.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002F1be5b54d73be458c9ac05f563872220f\u002F176007641639504200.png\" width=\"830\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">Figure 4. Time of overseas giants entering AI drug development and landmark events\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Of course, overseas giants haven't been idle either, and they have also gained a lot in the AI drug development field. For example, Google's mysterious institution Isomorphic Labs is about to launch the first human trial of a drug designed by AI in July 2025, marking an important step in AI drug development from concept verification to practical application. Similarly, in July, the AI for Science team of Microsoft Research collaborated with Berlin Free University and Rice University to launch BioEmu, the first scalable \"protein equilibrium ensemble simulator\" using diffusion generative models. With a single consumer-grade GPU, it can obtain protein dynamics information that used to require supercomputers to run for ten thousand hours in just a few dozen minutes, and the predicted protein stability and experimental error are less than 1 kcal\u002Fmol.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">As can be seen, on this difficult path of cross-industry AI drug development, giants are not just about \"having a lot of money,\" but are accelerating towards milestones with their own technological moats.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">AI Drug Development: A Tale of Two Sides, Cross-industry Players Need More Patience\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">According to incomplete statistics by Arterial Orange, in January to August 2025, more than 10 BD transactions were completed in China's AI drug development field, with a total transaction amount reaching 30 billion USD. MNCs such as AstraZeneca, Sanofi, Eli Lilly, and Pfizer have all invested in turn. The influx of massive capital and the acceleration of leading pharmaceutical companies prove that this is still a highly imaginative sector.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F10\u002F88835df890a24487a307b8974ca18ab4\u002F176007641650922700.png\" width=\"665\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-center\">\u003Cem class=\"ql-lineHeight-1-75\" style=\"color: rgb(187, 187, 187);\">Figure 5. Representative BD Transactions in the AI Drug Development Field Completed in 2025\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">However, on the other hand, the AI drug development field continues to report news of bankruptcy, layoffs, and failed pipelines, and the industry \"bubble\" is being burst one after another. In September 2024, the AI drug development leader Recursion and Exscientia announced a merger, which is the largest merger in AI drug development so far. However, from the outside, this merger seems more like a group of old AI drug development companies huddling together for warmth. According to the financial statements, Recursion had a net loss of 463.7 million USD in 2024, an increase of 41.3% year-on-year; while Exscientia had only 178 million USD on its books before the acquisition, which is insufficient to sustain its smooth operation in 2024.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Under this \"two sides of the coin\" market situation, it actually indicates that the AI drug development industry has moved from fantasy to reality, paying more attention to the real value of technological implementation and commercial sustainability.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Regarding this, a special investor said, \"The AI drug development field is entering a correction phase after excessive expectations. People gradually realize that their initial optimism about AI plus life sciences was too optimistic. This is actually a very long process, and before that, the industry had to think about self-\"blood supply\" issues. Therefore, everyone has focused their attention on clinical validation and commercial monetization of the pipeline under development.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">This means that a batch of cross-industry players will face new industry challenges. On one hand, they need to focus more on their own research and clinical implementation, such as continuously innovating in technology, further improving R&D efficiency, or applying their AI technology to more clinical scenarios and accelerating realization. This requires higher-level attention and participation from the giants, and also changes in organizational forms.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">On the other hand, in the commercial aspect, the giants need to find the most suitable business model and quickly monetize. According to the information, the current commercial directions of domestic AI drug development companies mainly include three types: Biotech (innovative drug companies), CRO (research and development outsourcing service providers), and SaaS (software tool companies). Among these, Biotech is currently the most mainstream commercial path in China, i.e., rapidly generating preclinical pipelines through AI, then advancing to the clinical stage, and then licensing and transferring to obtain upfront payments, milestone payments, and sales shares.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In October 2023, Baidu Biomedical Research received a 1 billion USD order from Sanofi, which validated the feasibility of this business model. After passing the MNC cooperation threshold, Baidu Biomedical Research smoothly entered a growth track. At present, with the continued popularity of BD transactions, many AI drug development companies are accelerating to demonstrate their capabilities to MNCs, which is also the case for a batch of cross-industry players.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In fact, AI drug development has both fast and slow aspects. One is the speed of AI technology, and the other is the decade-long effort of the pharmaceutical industry. This contradiction determines that the development of the AI drug development industry is by no means easy. But challenges are opportunities. For a batch of cross-industry players, the golden age of AI drug development has just begun. In the future, to stand out, they need to show stronger hard power and more patience.\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>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(187, 187, 187);\">[News Source] Arterial Orange \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.jiemian.com\u002Farticle\u002F13442645.html\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fwww.jiemian.com\u002Farticle\u002F13442645.html\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（This article is reposted by this site to provide readers with more information and news. The content does not constitute investment or consumption advice. If there are any doubts about the facts of the article, please verify with the relevant parties. The views of the article are not the views of this site and are for reference only.）\u003C\u002Fspan>\u003C\u002Fp>","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3Ad3f47eff-5bc5-45be-a192-f551cc4c321f%3A0.wav?Expires=1774838460&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=s3tSZmS9uVT3bg5NuTbc5uslxTw%3D","d3f47eff-5bc5-45be-a192-f551cc4c321f",18186366]