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Startups, Researchers, and Pharma Adopting NVIDIA BioNeMo

NVIDIA Clara Discovery collection of Frameworks and Applications

A wave of experts in biotech and pharma are adopting NVIDIA BioNeMo to support drug discovery research.

  • AstraZeneca and NVIDIA have used the Cambridge-1 supercomputer to develop the MegaMolBART model included in the BioNeMo LLM service. The global biopharmaceuticals company will use the BioNeMo framework to help train some of the world’s largest language models on datasets of small molecules, proteins, and, soon, DNA.
  • Researchers at the Broad Institute of MIT and Harvard are working with NVIDIA to develop next-generation DNA language models using the BioNeMo framework. These models will be integrated into Terra, a cloud platform co-developed by the Broad Institute, Microsoft, and Verily that enables biomedical researchers to share, access, and analyze data securely and at scale. The AI models will also be added to the BioNeMo service’s collection.
  • The OpenFold consortium plans to use the BioNeMo framework to advance its work developing AI models that can predict molecular structures from amino acid sequences with near-experimental accuracy.
  • Peptone is focused on modeling intrinsically disordered proteins — proteins that lack a stable 3D structure. The company is working with NVIDIA to develop versions of the ESM model using the NeMo framework, on which BioNeMo is also based on. The project, which is scheduled to run on NVIDIA’s Cambridge-1 supercomputer, will advance Peptone’s drug discovery work.
  • Evozyne, a Chicago-based biotechnology company, combines engineering and deep learning technology to design novel proteins to solve long-standing challenges in therapeutics and sustainability.

“The BioNeMo framework is an enabling technology to efficiently leverage the power of LLMs for data-driven protein design within our design-build-test cycle,” said Andrew Ferguson, co-founder and head of computation at Evozyne. “This will have an immediate impact on our design of novel functional proteins, with applications in human health and sustainability.”

“As we see the ever-widening adoption of large language models in the protein space, being able to efficiently train LLMs and quickly modulate model architectures is becoming hugely important,” said Istvan Redl, machine learning lead at Peptone, a biotech startup in the NVIDIA Inception program. “We believe that these two engineering aspects — scalability and rapid experimentation — are exactly what the BioNeMo framework could provide.”

Sign up for early access to the NVIDIA BioNeMo LLM service or BioNeMo framework. For hands-on experience with the MegaMolBART chemistry model in BioNeMo, request a free lab from NVIDIA LaunchPad on training and deploying LLMs.

Discover the latest in AI and healthcare at GTC, running online through Thursday, Sept. 22. Registration is free. 

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