Amgen to Build Generative AI Models for Novel Human Data Insights and Drug Discovery

Generative AI is transforming drug research and development, enabling new discoveries faster than ever - and Amgen, one of the world's leading biotechnology companies, is tapping the technology to power its research.

Amgen will build AI models trained to analyze one of the world's largest human datasets on an NVIDIA DGX SuperPOD, a full-stack data center platform, that will be installed at Amgen's deCODE genetics' headquarters in Reykjavik, Iceland. The system will be named Freyja in honor of the powerful, life-giving Norse goddess associated with the ability to predict the future.

Freyja will be used to build a human diversity atlas for drug target and disease-specific biomarker discovery, providing vital diagnostics for monitoring disease progression and regression. The system will also help develop AI-driven precision medicine models, potentially enabling individualized therapies for patients with serious diseases.

Amgen plans to integrate the DGX SuperPOD, which will feature 31 NVIDIA DGX H100 nodes totaling 248 H100 Tensor Core GPUs, to train state-of-the-art AI models in days rather than months, enabling researchers to more efficiently analyze and learn from data in their search for novel health and therapeutics insights.

For more than a decade, Amgen has been preparing for this hinge moment we are seeing in the industry, powered by the union of technology and biotechnology, said David M. Reese, executive vice president and chief technology officer at Amgen. We look forward to combining the breadth and maturity of our world-class human data capabilities at Amgen with NVIDIA's technologies.

The goal of deCODE founder and CEO K ri Stef nsson in starting the company was to understand human disease by looking at the diversity of the human genome. He predicted in a recent Amgen podcast that within the next 10 years, doctors will routinely use genetics to explore uncommon diseases in patients.

This SuperPOD has the potential to accelerate our research by training models more quickly and helping us generate questions we might not have otherwise thought to ask, said Stef nsson.

Putting the Tech in Biotechnology Since its founding in 1996, deCODE has curated more than 200 petabytes of de-identified human data from nearly 3 million individuals.

The company started by collecting de-identified data from Icelanders, who have a rich heritage in genealogies that stretch back for centuries. This population-scale data from research volunteers provides unique insights into human diversity as it applies to disease.

deCODE has also helped sequence more than half a million human genomes from volunteers in the UK Biobank.

But drawing insights from this much data requires powerful AI systems.

By integrating powerful new technology, Amgen has an opportunity to accelerate the discovery and development of life-changing medicines. In March 2023, NVIDIA announced that Amgen became one of the first companies to employ NVIDIA BioNeMo, which researchers have used to build generative AI models to accelerate drug discovery and development. Amgen researchers have also been accessing BioNeMo via NVIDIA DGX Cloud, an AI supercomputing service.

Models trained in BioNeMo can advance drug discovery on multiple fronts, said Marti Head, executive director of computational and data sciences at Amgen. In addition to helping develop drugs that are more effective, they can also help avoid unwanted effects like immune responses, and new biologics can be made in volume.

By adopting DGX SuperPOD, Amgen is poised to gain unprecedented data insights with the potential to change the pace and scope of drug discovery.

The fusion of advanced AI, groundbreaking developments in biology and molecular engineering and vast quantities of human data are not just reshaping how we discover and develop new medicines - they're redefining medicine, Reese said.

Learn about NVIDIA's AI platform for healthcare and life sciences.

LINK:	https://blogs.nvidia.com/blog/genomics-ai-amgen-superpod/...
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