San Diego-based Scripps Research was recently awarded 14 million computing hours, which will supercharge the speed of foundational research for vaccines, antibody therapies and small molecule drug discovery.<\/p>\n
This state-of-the-art computing power comes from the Jen-Hsun and Lori Huang Foundation, the personal philanthropy of Nvidia\u2019s co-founder and his wife. This gift is equivalent to tens of millions of dollars, according to some estimates.<\/p>\n
But the gift wasn\u2019t made purely out of generosity. Scripps\u2019 trove of deep scientific data may be worth equal, if not more, to its AI partners.<\/p>\n
The multitrillion-dollar pitch to Wall Street by AI behemoth Anthropic leans on the biological discoveries and new treatments its models could one day produce. But without good data, the models can\u2019t make those discoveries, and Nvidia can\u2019t sell more chips.<\/p>\n
The Jen-Hsun and Lori Huang Foundation\u2019s grant solves both problems at once. With Anthropic\u2019s AI model Claude, and 14 million hours of free computing power, Scripps can speed up the science it was already doing.<\/p>\n
But what if one of Scripps\u2019 competitors uses Anthropic\u2019s models, allowing the San Diego institution\u2019s intellectual property to be accessed by anyone with model access?<\/p>\n
\u201cWe want to maximize impact for exploration and discovery,\u201d said Andrew Ward, a professor at Scripps Research who is leading the project. \u201cWe need credit, of course, but it\u2019s not exactly what we\u2019re chasing,\u201d he said. Ward is more focused on biological discovery, he says.<\/p>\n
Today, early discovery looks like a lengthy sequence of trial and error. But all that guesswork could be done in minutes with the new grant.<\/p>\n
Scripps is using the 14 million hours to build two new tools for its researchers: a virtual human immune system and a map of the \u201cdark\u201d proteome.<\/p>\n
The first, which Scripps calls a \u201cVirtual Germinal Center,\u201d mimics how the body learns to fight a threat. Immune cells repeatedly mutate their antibodies and keep the ones that fight the \u201cbad guy\u201d best.<\/p>\n
This process normally takes weeks of educated guesswork, according to Ward.<\/p>\n
Professor Bryan Briney of Scripps Research is training AI on millions of real antibody sequences and structures to simulate that process on a computer, so researchers can test vaccine ideas and find promising antibody treatments before ever stepping into the lab.<\/p>\n
The second tackles the elusive proteins in our body. Simply put, proteins are the \u201cworkers\u201d in our body that execute tasks laid out by DNA.<\/p>\n
Thousands of proteins constantly flex and shape shift, so traditional 2D photo modeling can\u2019t capture them, and drug designers miss the brief pockets where a medicine could latch on.<\/p>\n
Professor Stefano Forli of Scripps Research is also planning to use the new computing hours. His team will simulate these proteins moving under body-like conditions to catch those fleeting pockets, turning \u201cundruggable\u201d proteins into potential drug targets.<\/p>\n
For Ward, the new project has meant thinking about infinity.<\/p>\n
The question came up over coffee in Palo Alto last summer. Eric Jensen, chief operating officer of the Jen-Hsun and Lori Huang Foundation, asked Ward what he would do with unlimited computing power.<\/p>\n
\u201cThink bigger,\u201d Jensen urged. \u201cIf we had infinity, what will that look like?\u201d<\/p>\n
It was difficult to imagine a world of no boundaries when all of Ward\u2019s research had existed within the confines of money and time.<\/p>\n
They discussed how to build foundation models for deep biology that every scientist could use. He characterized it as a democratization of knowledge that felt almost Promethean.<\/p>\n
A few days later, on Oct. 19, the Huang Foundation granted Scripps 14 million computing hours.<\/p>\n
Ward acknowledges that the models Scripps hopes to develop are far from perfect.<\/p>\n