Scientists can now access Evo 2, a foundation model that understands the genetic code for all domains of life. It was unveiled as the largest publicly available AI model for genomic data and was built on the NVIDIA DGX Cloud platform in a collaboration led by nonprofit biomedical research organization Arc Institute and Stanford University.
Evo 2 is available to global developers on the NVIDIA BioNeMo platform, including as an NVIDIA NIM microservice for AI deployment. Developers interested in fine-tuning Evo 2 on their proprietary datasets can download the model through the open-source NVIDIA BioNeMo Framework.
The model was trained on nearly 9 trillion nucleotides, the building blocks of DNA and RNA. According to the source, Evo 2 can be used in biomolecular research to predict the form and function of proteins from their genetic sequence, identify novel molecules for healthcare and industrial applications, and evaluate how gene mutations affect function.
“Evo 2 represents a major milestone for generative genomics,” said Patrick Hsu, Arc Institute cofounder and core investigator, and an assistant professor of bioengineering at the University of California, Berkeley. “By advancing our understanding of these fundamental building blocks of life, we can pursue solutions in healthcare and environmental science that are unimaginable today.”
The NVIDIA NIM microservice for Evo 2 enables users to generate a variety of biological sequences, with settings to adjust model parameters.
“Designing new biology has traditionally been a laborious, unpredictable and artisanal process,” said Brian Hie, assistant professor of chemical engineering at Stanford University, the Dieter Schwarz Foundation Stanford Data Science Faculty Fellow and an Arc Institute innovation investigator. “With Evo 2, we make biological design of complex systems more accessible to researchers, enabling the creation of new and beneficial advances in a fraction of the time it would previously have taken.”
Arc Institute was established in 2021 with $650 million from its founding donors. Its core investigators receive state-of-the-art lab space and funding for eight-year, renewable terms that can be held concurrently with faculty appointments with Stanford University, the University of California, Berkeley, and the University of California, San Francisco.
NVIDIA accelerated the project by giving scientists access to 2,000 NVIDIA H100 GPUs via NVIDIA DGX Cloud on AWS. The fully managed AI platform includes NVIDIA BioNeMo, which features optimized software in the form of NVIDIA NIM microservices and NVIDIA BioNeMo Blueprints.
Evo 2 can provide insights into DNA, RNA and proteins. Trained on a wide array of species across domains of life — including plants, animals and bacteria — the model can be applied to healthcare, agricultural biotechnology and materials science.
The model uses an architecture that can process lengthy sequences of genetic information, up to 1 million tokens. The source says this could help scientists better understand links between distant parts of an organism’s genetic code and the mechanics of cell function, gene expression and disease.
In healthcare and drug discovery, Evo 2 could help researchers identify gene variants tied to disease and design novel molecules that target those areas. Researchers from Stanford and the Arc Institute found that in tests with BRCA1, a gene associated with breast cancer, Evo 2 could predict with 90% accuracy whether previously unrecognized mutations would affect gene function.
In agriculture, the model could help researchers develop crops that are more climate-resilient or more nutrient-dense. The source also says Evo 2 could be applied to design biofuels or engineer proteins that break down oil or plastic.
Source: blogs.nvidia.com.
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