Arc Institute and NVIDIA join forces to transform biomedical research

The Arc Institute and NVIDIA have announced a partnership to accelerate scientific research by developing advanced computational models for biomedical discovery. The collaboration combines Arc’s biology expertise with NVIDIA’s computing prowess to create powerful AI tools that could revolutionize how scientists study and treat complex diseases.

“The convergence of biology and artificial intelligence holds exciting promise to transform the way we do science,” said Silvana Konermann, Arc Co-Founder, Core Investigator, and Executive Director, in the announcement.

A growing field with massive investment

The partnership enters a rapidly expanding market for AI in biological research. AI investments surged to a record-breaking $100 billion in 2024, with venture capital firms directing over $100 billion toward AI startups, a substantial portion specifically targeting healthcare and biomedical applications.

This substantial investment reflects both the promise and competitive nature of the field. The Arc-NVIDIA collaboration joins several high-profile partnerships reshaping biomedical research, including Google DeepMind’s AlphaFold collaborations with various research institutions and Microsoft’s recent $2 billion investment in pharmaceutical AI partnerships.

From sequencing to AI: A brief history

The marriage of computing and biology has evolved dramatically since the 1990s Human Genome Project, which took about 13 years and nearly $2.7 billion to sequence the first human genome. By the time the project was completed in 2003, the cost to generate a second reference human genome sequence was estimated at around $50 million. Over the years, advancements in sequencing technology have continued to accelerate, reducing both the time and cost dramatically. 

Today, genome sequencing can be completed in a matter of weeks at a cost of approximately $600 per genome, with some record-breaking efforts achieving sequencing in as little as five hours.

This exponential improvement in speed and affordability has transformed patient care, enabling precision medicine approaches that tailor treatments to individual genetic profiles. For researchers, these advances have democratized access to genomic data, allowing labs of all sizes to pursue questions that were once restricted to elite institutions with massive budgets, accelerating the pace of discovery across the biomedical sciences.

The current AI revolution represents the next leap forward. What’s different now is that machines aren’t just processing data—they’re helping to design experiments and predict outcomes, fundamentally changing how biology is practiced.

Biology’s AI-powered transformation

The partnership centers on the premise that AI can help scientists navigate biological complexity in ways human researchers alone cannot.

“Generative AI has revolutionized our ability to model complex biology digitally, offering researchers a new instrument to scale science through machine learning. Combining Arc Institute’s researchers and NVIDIA’s AI experts, we are working to turn massive scientific datasets into invaluable scientific tools and insights.” said Anthony Costa, Director of Digital Biology at NVIDIA.

The partnership builds on Arc’s previous work with the Evo model, which can both predict and design at the level of DNA and across RNA and proteins in single-celled organisms.

Real-world applications for pressing diseases

The impact could be particularly significant for complex conditions that have resisted traditional research approaches. Neurodegenerative diseases like Alzheimer’s and Parkinson’s, with their multifaceted genetic and environmental components, are prime targets for AI-enabled research.

For rare diseases, where limited patient populations make traditional clinical trials challenging, computational models might help researchers identify drug repurposing opportunities or design targeted therapies based on genetic profiles. Cancer research, particularly precision oncology, stands to benefit from models that can predict how specific mutations might respond to different treatments.

Democratizing access to cutting-edge tools

Importantly, the Arc-NVIDIA partnership includes plans to make these advanced tools accessible beyond elite research institutions. By contributing to open-source frameworks and providing cloud access, the collaboration could help level the playing field in global biomedical research.

“By training these models on diverse biological data, we aim to discover emergent properties similar to those found in language, videos, and robotics. We’re enabling researchers to leverage complex generative models in ways that could unlock biological design at scales previously inaccessible to science,” said Brian Hie, an Arc Institute Innovation Investigator in Residence.

For researchers in smaller institutions or developing nations, access to such powerful computational tools could eliminate barriers that have historically limited participation in cutting-edge biomedical discovery.

Both organizations indicate they’ll share more details about their first collaborative outputs later this year, and the stakes are high—their partnership will help define the extent to which AI tools will revolutionize biomedical research in the coming decade.