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半年豪掷107亿美元，脂肪肝成下一个“黄金靶点”？_我的网站

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    Students from Xi'an University of Technology test a virtual reality-enabled emergency evacuation simulation system tailored for flood disasters on January 12, 2024. Photos: Courtesy of Xi'an University of TechnologyEditor's Note:
Extreme weather is increasingly a global challenge, and the key to addressing climate risks lies in earlier prediction, more precise action and smarter preparedness, with emerging technologies playing a vital role. The Global Times launches the "Climate Gambit" series, exploring how research teams are leveraging cutting-edge technologies, including artificial intelligence, high-performance computing and smart observation systems, to anticipate weather changes, enhance disaster early-warning and strengthen resilience against climate risks.
Inside a state key laboratory at Xi'an University of Technology, Northwest China's Shaanxi Province, there is a miniature but complete "water world" which simulated water channels, inland lakes and main rivers to recreate real flood scenarios and test their newly developed GPU Accelerated Surface Water Flow and Transport Model (GAST).
Known as a "super brain" for flood control, GAST can complete flood simulations involving more than 3 million computational units within 30 seconds, helping transform flood management from a reaction to emergency into active precautions since "flooding impacts can be predicted even before rainfall arrives."
At a time when extreme rainfall and summer flooding have become increasingly frequent, questions such as when the flooding will arrive, which roads may be submerged and when residents should evacuate have become increasingly important.
In an exclusive interview with the Global Times, Hou Jingming, a professor at Xi'an University of Technology and the leader of the research team, explained how the GAST model seeks to answer these questions by accurately predicting flood development and identifying vulnerable areas before disasters occur, and how the model helps authorities take preventive measures to reduce casualties and economic losses.
AI empowering 'flood drill'  
The water tank system in the lab was designed to create a controllable, repeatable and observable environment to simulate complex hydrological processes, including river flooding, urban water level changes, lake regulation, drainage pump operations and coordinated flood-control measures.
By adjusting variations such as upstream water inflow, rainfall intensity, downstream water levels and drainage conditions, scientists can recreate different flood scenarios. Meanwhile, water levels, flow speeds and other data are collected in real time and displayed on a digital twin platform.
"If a rainstorm and corresponding floods are an exam, GAST is like a 'drill,'" Hou said. "It can simulate how floods develop, where water will flow, which areas may be inundated and when river levels may rise, ensuring authorities are well but not overly prepared."
To answer the public's concern about "whether my neighborhood will be flooded when heavy rain arrives," the team developed new algorithms for urban surface water flow, including improvements in terrain slope and friction calculations.
These breakthroughs have improved simulation accuracy in complex urban environments. Compared with extensive monitoring data, GAST can keep simulation errors of key hydrodynamic factors within 15 percent. This means the model can provide not only general flood trends, but also quantitative information such as water depth, flow speed and inundation areas.
Combined with AI technologies, it can identify complex relationships between rainfall, water conditions, flood depth, flow velocity and affected areas, cutting simulations from hours in traditional methods to minutes or even seconds.
The faster calculation capability means that once meteorological authorities update forecasts, the model can quickly estimate flood risks in different parts of a city. 
"The earlier rainfall warnings are issued, the earlier we can identify potential flooding hotspots and high-risk areas," Hou said. "This saves valuable time for evacuation, traffic management and emergency deployment."
For smarter disaster response

Building an accurate flood prediction model also requires integrating large amounts of urban data other than weather forecasts, including urban terrain, drainage networks and infrastructure information.
For example, a model developed for Xi'an incorporates geographic data and drainage system information collected from relevant authorities and field surveys. After receiving rainfall forecasts, the system can quickly calculate possible flooding scenarios, showing when and where waterlogging may occur and highlighting vulnerable roads and areas through visual maps.
To demonstrate how the super brain works in case of possible flooding, the laboratory has set a virtual reality area where visitors can experience a simulated urban flooding evacuation in the Xiaozhai area of Xi'an. Wearing VR headsets, participants can see water levels gradually rising and follow emergency instructions to move toward higher ground.
The entire technological package has already been applied in real-world flood prevention.
    A 3D live-scene display lab in Xi'an that oversees stormwater drainage performance in Hengshui, North China's Hebei Province Photos: Courtesy of Xi'an University of Technology
During Typhoon Muifa in 2022, Haishu district in Ningbo, East China's Zhejiang Province, recorded a regional rainfall of 367 millimeters. Using GAST as its core technology, the local flood forecasting platform integrated weather forecasts, AI algorithms and real-time monitoring data to provide rolling three-hour flood risk predictions.
Post-event assessments showed that predicted risks at most locations matched actual flooding conditions. The average relative error between predicted and observed maximum water depths was 13 percent.
The GAST model was also integrated into a smart rain and flood management platform in Qinhan new city area in Xianyang of Shaanxi, and during a rainstorm warning in July 2022, the platform provided continuous monitoring and forecasts. Based on the results, local authorities shifted from routine inspections to targeted monitoring of flood-prone areas and optimized emergency drainage operations.
The model is also being applied to mountain torrent prevention, as it can simulate rapidly changing flows in complex terrain and, combined with machine learning, complete forecasts within seconds. For reservoirs and rivers, it supports sudden and gradual dam-break simulations.
In June 2026, the model was presented at a national symposium on flood risk mapping achievements. The technology has since been applied by water resources, emergency management and urban development authorities, expanding from Shaanxi to multiple provinces and regions across China.
Looking ahead, the research team is developing a framework that further keeps up with the pace focusing on AI technologies. "Currently, the system operates based on weather forecast, therefore, AI will increase efficiency by using historical cases and real-time monitoring data to correct errors and update forecasts dynamically," Hou said.
。    早在2023年底的时候，我们就曾推断：脂肪肝将是减肥药后的下一个千亿战场。如今MNC正用真金白银，让这一推断渐渐落地。

二 |                    10月9日，诺和诺德突然宣布重磅交易，以52亿美元收购Akero Therapeutics公司，获得后者研发的FGF21类似物Efruxifermin。这是一款每周注射一次的治疗代谢功能障碍相关脂肪性肝炎（MASH）的创新药物，目前已经进入到临床III期。                   值得注意的是，FGF21药物并非诺和诺德一家的心头好，这已经是半年内第三起针对FGF21靶点的大型交易。此前葛兰素史克（GSK）和罗氏早已相继入局，分别以20亿美元和35亿美元收购了同类靶点资产。医药行业上一次出现如此盛况还是在GLP-1靶点爆发之时。                   FGF21，这个曾经默默无闻的靶点，正迅速成为代谢性疾病治疗领域的黄金赛道。                   代谢冠军的关键拼图                    FGF21全称成纤维细胞生长因子21，是一种主要由肝脏分泌的代谢调节激素，能够调控葡萄糖、脂质和能量代谢参与机体稳态的维持。                   作为FGF超家族中的内分泌成员，与其他促增殖型生长因子截然不同，它不依赖肝素发挥作用，却能精准锚定代谢调节的核心通路，是代谢疾病的“全能调节者”。                   从生物学机制来看，FGF21需与靶器官表面的FGFR1、FGFR2或 FGFR3受体，以及共受体β-Klotho形成三元复合物，才能激活下游信号通路，而β-Klotho主要分布在肝脏、脂肪组织、胰腺等代谢关键器官，这让FGF21的作用范围天然聚焦于代谢紊乱相关组织。

三 |                    在生理状态下，当身体处于饥饿、高脂饮食等应激场景时，肝脏和脂肪组织会分泌FGF21，通过促进脂肪分解、增强胰岛素敏感性、调节糖脂代谢等方式维持能量稳态；而在肥胖、2型糖尿病、非酒精性脂肪性肝病（NAFLD）等病理状态下，FGF21的表达或功能会出现异常，这也是其能成为治疗靶点的生物学依据。                   图：FGF21结构，来源：国泰海通证券                    尽管原理较为清晰，但FGF21的成药之路却充满波折。天然FGF21蛋白半衰期极短，仅为1—2小时，且在体内易被蛋白酶降解，需频繁注射才能维持药效，这让它长期停留在实验室阶段难以商业化落地。

四 |                    直到近年蛋白质工程技术的突破，才彻底改写了它的命运。通过PEG化修饰，可将其半衰期延长至数天，实现每周一次给药，被罗氏收购的89bio公司的pegozafermin便采用了这一技术；而Akero的Efruxifermin则通过氨基酸序列突变优化蛋白结构，在增强稳定性的同时，还保留了天然FGF21的多靶点调节能力。这些技术改进让FGF21从“实验室分子”中脱颖而出，也为其在MASH治疗中崭露头角奠定了基础。                   当前MASH治疗格局中，GLP-1类药物（如诺和诺德的司美格鲁肽）和THRβ激动剂（如Madrigal的Rezdiffra）虽已获批用于F2-F3期中重度肝纤维化患者，但二者均存在局限：GLP-1对晚期肝纤维化效果有限，THRβ激动剂则无法覆盖肝硬化患者。

五 |                    对比之下，FGF21类药物则展现出全疾病阶段覆盖的潜力。以Akero的Efruxifermin为例，其公布的IIb期临床数据显示，经过96周治疗，F2—F3期MASH患者的肝纤维化改善率接近50%，F4期肝硬化患者的改善率也达到29%，远超安慰剂组的24%和11%；更重要的是，它在改善肝纤维化的同时，还能降低甘油三酯、提升高密度脂蛋白胆固醇，对心血管代谢指标产生正向调节，这恰好弥补了其他疗法的短板。

六 |                    正因为在MASH治疗领域的独特优势，FGF21成为填补GLP-1与THRβ激动剂空白的“第三极”，也让FGF21从曾经的“冷门靶点”，一跃成为跨国药企争相布局的黄金赛道。此外，临床前研究显示，FGF21类药物在改善非酒精性脂肪性胰腺炎（NAFP）、肥胖合并代谢紊乱等疾病中也有积极表现，适应症边界还将进一步扩大。                   MNC的必争之地                    FGF21靶点的科学机制与治疗潜力背后，是不言而喻的巨大商业价值。                   作为全球增长最快的代谢性肝病，MASH的发病与肥胖、2型糖尿病高度关联，据弗若斯特沙利文报告，2030年全球患病人数将达4.9亿人，对应的药物市场规模将攀升至322亿美元，这一规模与当年GLP-1爆发前的市场预期相当。                   随着Madrigal旗下全球首个MASH治疗药物Rezdiffra的商业化放量持续超预期，其开辟的市场空间正吸引越来越多MNC入局。当前已获批的GLP-1类药物与THRβ激动剂均局限于F2—F3期患者，无法覆盖占比约20%的F4期肝硬化群体，而FGF21类药物逆转肝硬化的独特疗效，恰好填补了这一临床空白。这种不可替代的治疗价值，让其商业化前景被业内广泛看好，也使其成为MNC争相抢夺的核心资产。                   2025年5月，GSK率先行动，以总额高达20亿美元的现金对价收购了Boston Pharmaceuticals的核心资产，FGF21类似物Efimosfermin alfa。该药最初由诺华研发，通过Fc融合蛋白技术将半衰期延长至21天，实现每月一次给药，显著优于竞品的周给药方案。

七 |                    对于在GLP-1赛道布局相对滞后的GSK而言，Efimosfermin alfa的加入迅速填补了其在MASH领域的空白。GSK还计划将其与在研siRNA疗法GSK4532990联用，以覆盖脂肪性肝病（SLD）的更晚期阶段，形成“抗纤维化+基因调控”的互补组合，在细分市场建立竞争优势。                   紧随GSK之后，罗氏也在今年9月高调宣布，以最高35亿美元的价格收购生物制药公司89bio，获得其核心资产FGF21类药物pegozafermin。

八 | 该药采用独特的糖基PEG化技术，优化了其生物活性和半衰期，目前已进入III期临床阶段。                   罗氏近年来在减重药物领域连续布局：2023年12月，以31亿美元收购了美国制药公司Carmot Therapeutics（GLP-1双靶点激动剂）；2025年3月，又同意以53亿美元获得丹麦Zealand Pharma公司一款在研创新减重疗法的相关权益。此次将Pegozafermin收入囊中，将加强其在心血管、肾脏及代谢性疾病领域的产品组合，并为其现有在研项目的潜在联合用药方案打开空间。                   随着FGF21资产不断被收购，业绩遭遇拐点的诺和诺德也终于坐不住了。2025年10月，诺和诺德宣布以最高52亿美元的价格收购美国生物技术公司Akero Therapeutics，获得其FGF21类似物Efruxifermin。

九 | 该药III期SYNCHRONY研究预计于2026年二季度读出数据，较竞品具备先发优势，也与自研的NN9499形成互补之势。                   图：全球领先FGF21管线一览，来源：国盛证券                    这笔交易是其新任首席执行官Mike Doustdar自7月上任以来的首个重大交易，也是其继宣布裁撤 9000个岗位后推出的重要动作，体现了其“简化结构、减少重复、集中资源”的战略决心。在面对礼来等竞争对手压力时，诺和诺德积极拓展司美格鲁肽联合疗法，希望找到新的业绩增长点，以巩固其代谢领域的霸主地位。                   这三笔交易共同体现了MNC的战略逻辑：通过收购成熟后期资产快速切入FGF21赛道，依托自身管线资源实现协同效应。MNC拼命在百亿级MASH市场中抢占先机，而这种布局也让FGF21靶点的竞争逐渐白热化。                   新的赶超机会？                    跨国药企在FGF21靶点上的密集布局与重金投入，预示着这一靶点极有可能复刻GLP-1的成功路径，成为下一代代谢疾病治疗的基石。                   与GLP-1类似，FGF21不仅靶向明确的巨大临床需求，更可突破单一疾病边界，向减重、心血管保护、血脂代谢等领域延伸。

十 | 独特的抗纤维化能力，尤其在对晚期肝硬化（F4期）患者的逆转效应上，构建了难以替代的临床价值与市场壁垒。其“代谢调控”与“组织修复”的双重机制，为未来GLP-1与FGF21的联合疗法奠定基础，这也是FGF21估值飙升的核心逻辑。

十一 |                    在跨国药企抢占FGF21靶点的浪潮中，中国药企凭借前瞻性的布局与差异化的研发策略，正成为FGF21赛道上不可忽视的力量。

十二 | 与跨国药企聚焦单靶点FGF21类似物不同，国内企业更聚焦于通过多靶点激动剂探索协同增效的潜力。

十三 |                    东阳光药的HEC88473是一款GLP-1/FGF21双靶点激动剂，通过将两种代谢调节机制结合，在改善糖脂代谢的同时展现出抗肝纤维化潜力。2024年11月，东阳光药就HEC88473与Apollo Therapeutics达成了总价高达9.38亿美元的海外授权协议。

十四 | 该药在国内已进入II期临床，早期研究数据显示其在降低肝脏脂肪含量和改善血糖控制方面具有显著疗效。                   同时，中国生物制药子公司正大天晴通过与安源医药达成合作协议，获得后者AP025和AP026在中国和部分亚洲地区的独家合作与许可协议，BD总金额最高为3.42亿元另加个位数销售分成。其中AP025为单靶点FGF21，目前处于国内II期阶段；AP026为FGF21/GLP-1双靶点药物，目前处于国内申报临床阶段。

十五 |                    除已经实现BD的东阳光药、安源医药外，华东医药亦是FGF21靶点的重要参与者。

十六 | 华东医药旗下控股子公司道尔生物研发的DR10624，是一款靶向FGF21R、GLP-1R和GCGR的长效三靶点激动剂。这种“多靶点覆盖”的设计，使DR10624成为FGF21赛道中极具差异化的候选药物。

十七 |                    该药物已在海外完成针对肥胖合并高甘油三酯血症的Ib/IIa期研究，并正在中国推进针对代谢相关脂肪性肝病的II期临床试验。2025年5月公布的Ib/IIa期临床数据显示，DR10624治疗12周后最优剂量组肝脏脂肪含量降幅达到79%，显著优于安慰剂组的26%。                   展望未来，FGF21赛道的交易热潮预计将持续升温。

十八 | 巨大的MASH市场容量以及明确的联合疗法方向，将继续推动MNC们对该领域优质资产的追逐。

十九 | 考虑到目前全球范围内进入临床后期的FGF21资产仍属稀缺资源，那些已经通过早期临床数据验证了概念、并进入II期及以上阶段的在研药物，无疑将成为下一波资本角逐的焦点。                   FGF21靶点的百亿并购狂潮，是GLP-1传奇在代谢领域的延续与升华。

| 从司美格鲁肽到替尔泊肽，GLP-1类药物从降糖药跃升为全球“药王”，彻底点燃了全球药企对代谢疾病赛道的热情与期待。

| 而中国药企凭借在多靶点药物上的抢先布局，有潜力在这场全球竞赛中实现追赶，甚至超越。                   本文来自微信公众号：医曜，作者：青栎。

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