特朗普政府周三宣布了一项新计划，旨在重新设计临床试验的流程，目标是大幅缩短新药研发所需的时间和成本。
The Trump administration on Wednesday is launching an effort to reimagine the way clinical trials are designed, with a goal of drastically reducing the time and money it takes to develop new drugs.
重要性：该计划首次由媒体 Axios 报道，可能为重新构建药物研发流程提供范例，从而提升美国在全球生物技术竞争中的竞争力。
Why it matters: The program, shared first with Axios, could provide a template for reconfiguring the drug development process and boosting U.S. competitiveness in the global biotech race.
推动此次公告的官员：卫生部长小罗伯特·F·肯尼迪（Robert F. Kennedy, Jr.）以及美国卫生高级研究计划局（Advanced Research Projects Agency for Health, ARPA-H）局长艾丽西亚·杰克逊（Alicia Jackson）将在德克萨斯州奥斯汀市共同宣布这一新举措。美国医疗保险与医疗补助服务中心（CMS）主任梅赫梅特·奥兹（Mehmet Oz）和美国食品药品监督管理局（FDA）代理局长凯尔·迪亚曼塔斯（Kyle Diamantas）也将出席此次发布会。
Driving the news: Health Secretary Robert F. Kennedy, Jr. and Advanced Research Projects Agency for Health Director Alicia Jackson are unveiling the new effort in Austin, Texas. CMS Administrator Mehmet Oz and FDA Acting Commissioner Kyle Diamantas will also attend the announcement. The effort — dubbed the Simulation-augmented, Real-time Platform Adaptive Seamless Trials (SURPASS) program — features teams selected through a bidding process that will bring drug candidates through experimental clinical trial processes.
计划的具体内容：该计划被称为“模拟增强型、实时平台自适应无缝试验”（Simulation-augmented, Real-time Platform Adaptive Seamless Trials, SURPASS），其核心是通过招标机制选拔团队来负责新药的临床试验工作。获胜的团队将在五年内获得资金和支持。
How it works: The initiative under ARPA-H will begin by soliciting ideas from "teams" that include a drug sponsor. Winners will receive funding and support over five years.
运作方式：该计划首先会向包括药品研发方在内的多个团队征集创新方案。获胜团队将获得资金支持，并在五年内开展相关研究。ARPA-H 重点关注以下三个技术领域的创新：
- “无阶段临床试验”（Phaseless trials）：允许在更少的患者参与下更快地完成临床试验；
ARPA-H is looking for proposals that innovate in three technical areas: Phaseless trials that allow faster trials with fewer patients, the ability to analyze data in real time during the trial instead of than only when it ends, and using automation to reduce inefficiencies. Teams will also likely include medical centers or other clinical sites, biostatisticians, and companies that have the ability to predict drug outcomes via a computer.
- 实时数据分析：能够在试验过程中实时分析数据，而不仅仅是在试验结束后才进行分析；
The FDA has been included in the planning of the program, and "there won't be any surprises for regulators in this," said Daria Fedyukina, the program manager.
- 自动化应用：利用自动化技术减少研发过程中的低效率。
The big picture: One of the reasons China has become such a popular location for drug manufacturers is because it's much cheaper and faster to do early-stage clinical trials there.
FDA 的参与：美国食品药品监督管理局（FDA）也参与了该计划的规划工作。项目负责人达莉亚·费杜基娜（Daria Fedyukina）表示：“监管机构对此不会有任何意外。”
Experts and the biopharmaceutical community largely agree that in order to compete, the U.S. needs to streamline its trial processes.
背景信息：中国之所以成为药品制造商的热门选择地，其中一个重要原因在于：在中国进行早期临床试验的成本更低、耗时也更短。
Today, developing a drug can take longer than a decade and cost around $2 billion. More than 90% of drug candidates fail, according to HHS.
专家们以及整个生物制药行业普遍认为，为了在竞争中立于不败之地，美国需要简化其药物研发流程。目前，开发一种新药通常需要超过十年的时间，成本高达约20亿美元；根据美国卫生与公众服务部（HHS）的数据，超过90%的药物候选项目最终会失败。
What they're saying: "The goal is to develop the tech that is missing and blaze the trail of a new clinical trial paradigm," Fedyukina said. The program will require the development of "blueprints and standards that then can be deployed and used by all other trials in the U.S," she added.
Fedyukina表示：“我们的目标是开发那些目前还缺失的关键技术，并开创一种全新的临床试验模式。”她补充说：“该计划将制定相关‘蓝图’和标准，供美国所有临床试验项目参考和使用。”
While "it's hard to put a number to how much cost savings or time savings we can achieve," Fedyukina said, "there is no reason why we cannot target, let's say, a 10x reduction in the cost of clinical development for a drug."
虽然“很难准确预测我们能够节省多少成本或时间”，但Fedyukina认为：“完全没有理由不能将药物研发的成本降低10倍；也没有理由不能将研发周期缩短一半甚至更多。”
"There's no reason why we cannot cut timeline in half or more," she added. Details: ARPA-H is also announcing three related projects today aimed at improving the infrastructure around clinical trials.
此外，ARPA-H今天还宣布了三个相关项目，旨在改善临床试验的基础设施：
第一个项目旨在通过人工智能技术加快临床试验基地的建立速度，并为那些此前从未开展过临床试验的基地做好准备工作，从而使居住在附近医院的患者也能获得可能对他们有益的实验性药物；
One is focused on setting up more clinical trial sites, with the help of AI to speed up site activation and prepare sites that haven't held trials before. This will allow patients who live near hospitals that don't currently participate in clinical trials to gain access to experimental drugs they may benefit from.
另两个项目则专注于临床试验数据的管理，以及帮助患有复杂癌症的患者更好地利用自己的医疗数据、更有效地获取医疗服务。
The other two projects focus on clinical trial data infrastructure and helping patients with complex cancers benefit from their own data and better navigate the care system.
总之，这一切都还处于实验阶段，但如果成功的话，将会带来巨大的回报。
The bottom line: This is all an experiment, but if successful it could pay big dividends.