内容来源：https://techcrunch.com/2026/05/18/sandboxaq-brings-its-drug-discovery-models-to-claude-no-phd-in-computing-required/

内容总结：

AI制药新突破：SandboxAQ联手Anthropic，手机就能做药物研发

过去，新药研发堪称现代工业最烧钱的“豪赌”——一款候选分子从发现到上市往往耗时十年、耗资数十亿美元，且失败率极高。尽管AI初创公司蜂拥而至，但大多只是让本就精通技术的科研人员用起来更顺手，并未真正改变“高门槛”的核心痛点。

近日，从谷歌剥离五年的AI公司SandboxAQ宣布与Anthropic达成合作，直接将科学AI模型嵌入Claude对话界面。这意味着，科研人员无需搭建任何专业计算基础设施，只需像日常聊天一样，就能调用强大的药物发现与材料科学工具。

SandboxAQ由谷歌前CEO埃里克·施密特担任董事长，累计融资超9.5亿美元，业务横跨网络安全等多个领域。但其最独特之处在于打造了“大型定量模型”——这些模型基于物理定律而非文本模式运行，能够执行量子化学计算、模拟分子动力学和微观反应动力学，在实验室动手之前就预判候选分子的真实表现。

“这不再是另一个聊天机器人或代码助手。”SandboxAQ在新闻稿中强调，LQMs瞄准的是生物制药、金融服务、能源和先进材料等合计超50万亿美元的“定量经济”——这才是AI真正应该变革的领域。

与专注于模型优化的同行不同，SandboxAQ的突破口在于“谁能用”。其AI模拟业务总经理纳迪娅·哈亨表示：“这是首次将前沿定量模型接入前沿大语言模型，用户用自然语言就能使用。”以往，客户必须自建数字基础设施才能运行LQMs，而现在，只需对话即可。

目前，SandboxAQ的客户主要是大型药企和工业公司的计算科学家、研究科学家和实验人员。他们往往在尝试过所有其他软件后仍无果而终，最终求助于SandboxAQ——因为那些复杂问题，在现实转化时从未给出过理想的答案。

中文翻译：

药物发现是现代工业中成本最高的探索之一。找到一种可行的分子可能需要十年时间，耗资数十亿美元，而大多数候选分子最终仍无法成功。一代人工智能初创公司曾承诺要改变这一现状——其中大多数只是让研究人员在技术层面上的痛苦有所减轻，而这些人本就已具备足够熟练的技术来使用这些工具。

但SandboxAQ认为，瓶颈并不在于模型，而在于交互界面。

该公司已与Anthropic合作，将其科学人工智能模型直接集成到Claude中——通过一个无需专用计算基础设施即可使用的对话式界面，提供强大的药物发现和材料科学工具。

SandboxAQ大约在五年前从Alphabet分拆出来，谷歌前首席执行官埃里克·施密特担任其董事长。这家公司已从投资者那里筹集了超过9.5亿美元，并建立了多个业务线，其中包含一项网络安全业务。

然而，SandboxAQ更为独特之处在于其开发的大型定量模型（LQMs）。这些专有模型“以物理学为基础”，意味着它们建立在物理世界的规则之上，而非文本模式。它们能够进行量子化学计算，并模拟分子动力学和微观动力学——即研究化学反应在分子层面如何展开的学科。这一点至关重要，因为它能让研究人员在任何人踏入实验室之前，就了解候选分子可能的行为表现。

“LQMs基于真实世界的实验室数据和科学方程进行训练，是为定量经济打造的人工智能模型。这一经济领域涵盖生物制药、金融服务、能源和先进材料，规模超过50万亿美元，”该公司在一份新闻稿中表示，这强烈表明SandboxAQ并非在构建另一个聊天机器人或代码助手——它瞄准的是人工智能理应去变革的经济领域。

专注于更优模型的Chai Discovery和Isomorphic Labs——两者均有雄厚资金支持——都将重心放在了科学本身。而SandboxAQ则聚焦于谁能够真正使用这些模型。

“我们首次在一个前沿大语言模型上搭载了前沿定量模型，用户可以通过自然语言进行访问，”SandboxAQ人工智能模拟业务总经理纳迪亚·哈亨告诉TechCrunch。此前，SandboxAQ的LQMs用户需要自备数字基础设施才能运行这些模型。

SandboxAQ的客户通常是计算科学家、研究科学家或实验人员。这些人大多任职于大型制药或工业企业，正在寻找能够成为适销产品的新材料。

“客户之所以找到我们，是因为他们尝试过市面上所有其他软件，而当这些方案需要在现实世界中转化时，其问题的复杂性导致它们要么行不通，要么无法为他们带来积极的结果，”哈亨说道。

英文来源：

Drug discovery is one of the most expensive pursuits in modern industry. Finding a single viable molecule can take a decade and cost billions, and most candidates still don’t make it. A generation of AI startups has promised to fix that — most have made the problem less painful for researchers, who are already technically sophisticated enough to use the tools.
But SandboxAQ thinks the bottleneck isn’t the models. It’s the interface.
The company has teamed up with Anthropic to integrate its scientific AI models directly into Claude — putting powerful drug discovery and materials science tools behind a conversational interface that requires no specialized computing infrastructure to use.
Founded roughly five years ago as an Alphabet spinout, SandboxAQ counts Eric Schmidt, Google’s former CEO, as its chairman. The company, which has raised more than $950 million from investors, has built out a number of different business lines, including a cybersecurity business.
One of the more unique things SandboxAQ does, however, is produce large quantitative models, or LQMs. These proprietary models are “physics-grounded,” meaning they’re built on the rules of the physical world rather than patterns in text. They can run quantum chemistry calculations and simulate both molecular dynamics and microkinetics, the study of how chemical reactions unfold at the molecular level. That matters because it tells researchers how candidate molecules are likely to behave before anyone sets foot in a lab.
“Trained on real-world lab data and scientific equations, LQMs are AI models engineered for the quantitative economy, a $50+ trillion sector spanning biopharma, financial services, energy, and advanced materials,” the company said in a news release that strongly suggests Sandbox AQ isn’t building another chatbot or code assistant — it’s chasing the economy that AI is supposed to transform.
Chai Discovery and Isomorphic Labs — both well-funded bets on better models — have focused on the science. SandboxAQ is focused on who can actually use it.
“For the first time, we have a frontier [quantitative] model on a frontier LLM that someone can access in natural language,” Nadia Harhen, SandboxAQ’s general manager of AI simulation, told TechCrunch. Previously, users of SandboxAQ’s LQMs would have had to provide their own digital infrastructure to run the models.
SandboxAQ’s customers tend to be computational scientists, research scientists, or experimentalists. Generally, these people work at large pharmaceutical or industrial companies and are searching for new materials that can become marketable products.
“Our customers come to us because they’ve tried all the other software out there, and the complexity of their problem is such that it didn’t work or didn’t yield positive results for them when that translation went to take place in the real world,” said Harhen.