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Drug discovery is one of the most expensive failures in modern industry. Finding a single viable molecule can take a decade and cost billions, and most candidates still don\u2019t make it. A generation of AI startups has promised to fix that \u2014 most have made the problem less painful for researchers who are already technically sophisticated enough to use the tools.<\/p>\n
But SandboxAQ thinks the bottleneck isn\u2019t the models. It\u2019s the interface.<\/p>\n
The company has teamed up with Anthropic to integrate its scientific AI models directly into Claude \u2014 putting powerful drug discovery and materials science tools behind a conversational interface that requires no specialized computing infrastructure to use.<\/p>\n
Founded roughly five years ago as an Alphabet spinout, SandboxAQ counts Eric Schmidt, Google\u2019s former CEO, as its chairman. The company, which has raised more than $950 million from investors<\/a>, has built out a number of different business lines, including a cybersecurity business<\/a>, for instance.<\/p>\n One of the more unique things SandboxAQ does, however, is produce large quantitative models, or LQMs. These proprietary models are \u201cphysics-grounded,\u201d meaning they\u2019re 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.<\/p>\n \u201cTrained 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,\u201d the company said in a new release that strongly suggests Sandbox AQ isn\u2019t building another chatbot or code assistant \u2014 it\u2019s chasing the economy that AI is supposed to transform.<\/p>\n Chai Discovery<\/a> and Isomorphic Labs<\/a> \u2014 both well-funded bets on better models \u2014 have focused on the science. SandboxAQ is focused on who can actually use it. <\/p>\n \u201cFor the first time, we have a frontier [quantitative] model on a frontier LLM that someone can access in natural language,\u201d Nadia Harhen, SandboxAQ\u2019s general manager of AI simulation, told TechCrunch. Previously, users of SandboxAQ\u2019s LQMs would have had to provide their own digital infrastructure to run the models.<\/p>\n SandboxAQ\u2019s 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.<\/p>\n \u201cOur customers come to us because they\u2019ve tried all the other software out there, and the complexity of their problem is such that it didn\u2019t work or didn\u2019t yield positive results for them when that translation went to take place in the real world,\u201d said Harhen.<\/p>\n<\/div>\n When you purchase through links in our articles, we may earn a small commission<\/a>. This doesn\u2019t affect our editorial independence.<\/em><\/p>\n