U.S. health systems are adopting digital health agents to leverage AI across the board, from the lab to the clinical setting.
The latest AI acceleration tools on display at the NVIDIA AI Summit in Washington, DC this week include NVIDIA NIM, a collection of cloud-native microservices that support the deployment and execution of AI models, and the NVIDIA NIM Agent, a catalog. Contains Blueprints. Pre-trained and customizable workflows.
These technologies are already being used in the public sector to advance the analysis of medical images, support the search for new treatments, and extract information from large PDF databases containing text, tables, and graphs.
For example, researchers at the National Cancer Institute, part of the National Institutes of Health (NIH), are developing a new model for medical image processing, including the VISTA-3D NIM foundational model for segmenting and annotating 3D CT images. We use several AI models built with NVIDIA MONAI. A team at NIH’s National Center for the Advancement of Translational Sciences (NCATS) is using NIM Agent Blueprints for generative AI-based virtual screening to reduce the time and cost of developing new drug molecules.
With NVIDIA NIM and NIM Agent Blueprints, healthcare researchers across the public sector can quickly start deploying cutting-edge, optimized AI models to accelerate their work. Pre-trained models are customizable based on your organization’s own data and can be continually refined based on user feedback.
NIM Microservices and NIM Agent Blueprints are available at ai.nvidia.com and can be accessed through various cloud service providers, global system integrators, and technology solution providers.
Building with NIM agent blueprints
Developers can experience and download dozens of NIM microservices and a growing set of NIM agent blueprints for free. These can be deployed into production using the NVIDIA AI Enterprise software platform.
The Generative Virtual Screening Blueprint for Drug Discovery integrates three NIM microservices to help researchers search and optimize libraries of small molecules and identify promising candidates that bind to target proteins. Helpful. The Multimodal PDF Data Extraction Blueprint uses NVIDIA NeMo Retriever NIM microservices to extract insights from enterprise documents, enabling developers to build powerful AI agents and chatbots. Digital Human Blueprint supports the creation of interactive AI-powered avatars for customer service. These avatars have potential applications in non-clinical aspects of patient care, such as telemedicine, scheduling appointments, filling out medical questionnaires, and managing prescriptions.
Two new NIM microservices for drug discovery are now available on ai.nvidia.com to help researchers understand how proteins bind to target molecules, a critical step in drug design. I did. Conducting much of this preclinical research digitally allows scientists to narrow down the pool of drug candidates before testing them in the lab, making the discovery process more efficient and less costly.
The AlphaFold2-Multimer NIM microservice allows researchers to accurately predict protein structures from sequences in minutes, reducing the need for time-consuming testing in the lab. The RFdiffusion NIM microservice uses generative AI to design novel proteins that are likely to bind to target molecules and thus become promising drug candidates.
NCATS accelerates drug discovery research
ASPIRE, an NCATS laboratory, is evaluating NIM agent blueprints for virtual screening and using RAPIDS, a suite of open-source software libraries for GPU-accelerated data science, to accelerate drug discovery research. Masu. Using the cuGraph library for graph data analysis and the cuDF library for data frame acceleration, researchers in the lab can map chemical reactions across a vast unknown chemical space.
The NCATS Informatics team reported that with NVIDIA AI, processes that would take hours on CPU-based infrastructure complete in seconds.
Large amounts of medical data, such as research papers, radiology reports, and patient records, are unstructured and locked up in PDF documents, making it difficult for researchers to quickly retrieve information.
The Genetic and Rare Disease Information Center, also run by NCATS, will explore using PDF data extraction blueprints to develop generative AI tools that will enhance the center’s ability to gather information from previously unsearchable databases. I’m doing it. These tools help answer questions from people affected by rare diseases.
“The center analyzes data sources across the National Library of Medicine, the Orphanet database, and other institutions and centers within the NIH to answer patient questions,” said Sam Michael, chief information officer at NCATS. ”. “AI-powered PDF data extraction makes it much easier to extract valuable information from previously unsearchable databases.”
Mi-NIM-al effort, maximum benefit: Start NIM
More startups, cloud service providers, and global system integrators are incorporating NVIDIA NIM microservices and NIM agent blueprints as part of their platforms and services, making it easier for federal healthcare researchers to get started.
Abridge, an NVIDIA Inception startup and NVentures portfolio company, recently won a contract from the U.S. Department of Veterans Affairs to help transcribe and summarize clinical appointments, reducing the burden on physicians to document each patient interaction. has been reduced.
The company uses NVIDIA TensorRT-LLM to accelerate AI inference and NVIDIA Triton Inference Server to deploy speech-to-text and content summarization models at scale. Some of these technologies are the same that power NIM microservices.
NIM agent blueprints for virtual screening are now available through AWS HealthOmics, a dedicated service that helps customers orchestrate biological data analysis.
Amazon Web Services (AWS) is a partner of the NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability Initiative (also known as the STRIDES Initiative). The STRIDES initiative aims to modernize the biomedical research ecosystem by reducing economic and process barriers to accessing commercial cloud services. NVIDIA and AWS are collaborating to make NIM agent blueprints widely accessible to the biomedical research community.
ConcertAI, another NVIDIA Inception member, is an oncology AI technology company focused on research and clinical standard of care solutions. The company integrates NIM microservices, NVIDIA CUDA-X microservices, and the NVIDIA NeMo platform into a suite of AI solutions for large-scale clinical data processing, multi-agent models, and clinical infrastructure models.
NVIDIA NIM microservices support ConcertAI’s high-performance, low-latency AI models through the CARA AI platform. Use cases include clinical trial design, optimization, and patient matching, as well as solutions that help improve standards of care and enhance clinical decision-making.
Deloitte, a global systems integrator, provides NIM agent blueprints for virtual screening to customers around the world. With Deloitte Atlas AI, the company can help its federal health agency customers easily use NIM to implement and deploy modern generative AI pipelines for drug discovery.
Experience NVIDIA NIM microservices and NIM agent blueprints today.
NVIDIA AI Summit focuses on healthcare innovation
At the NVIDIA AI Summit in Washington, NVIDIA leaders, customers, and partners will present more than 50 sessions focused on impactful work in the public sector.
Register for a free virtual pass to hear how medical researchers are accelerating innovation with AI powered by NVIDIA in the following sessions:
Federal Health Leadership Panel: The Growing Importance of AI in U.S. Government Health includes leaders from NVIDIA, NIH, U.S. Department of Health and Human Services, and more. “Boosting US Innovation and Competitiveness in AI-Enabled Healthcare and Biology” features Renee Wegrzyn, Director of the Health Advanced Research Projects Agency, and Rory Kelleher, Global Head of Life Sciences Business Development at NVIDIA. “Improving Translational Genomics Research with High-Speed Computing,” Justin Zook, co-leader of the Biomarker and Genome Sciences Group at the National Institute of Standards and Technology, and the National Cancer Institute’s Frederick National Cancer Institute computational Scientist Laura Egolf discusses using NVIDIA. Parabricks software for genomics research. “Building a Specialized Interactive Foundation Model for 3D CT Segmentation” features Baris Turkbey, senior clinician and director of MRI and artificial intelligence resources in the National Cancer Institute’s Division of Molecular Imaging, and Pengfei Guo, applied research scientist at NVIDIA. Featured by Mr.
Watch a special AI Summit talk from Bob Pette, VP of Enterprise Platforms at NVIDIA.
Check out our software product information notice.
