Healthcare has always been one of NVIDIA’s bigger bets. And now, exactly on the one-year anniversary of BioNeMo cloud, the company has introduced a set of over 25 new generative AI-powered microservices to empower healthcare organisations globally across various domains, such as drug discovery, medical technology (MedTech), and digital health, at the much-awaited NVIDIA GTC 2024.
Additionally, BioNeMo now contains new foundational models for various tasks in drug discovery, such as analysing DNA sequences, predicting protein structure changes caused by drug interactions, and identifying cell functions from RNA data.
“Healthcare is inherently complicated. We aim to make it easier for researchers who can fine-tune these models on proprietary data, run AI model inference through web browsers or cloud APIs, and access pre-trained models for drug development,” Kimberly Powell, VP of healthcare, NVIDIA, had told AIM earlier.
Over 25 Generative AI Microservices
These microservices, accessible on any cloud platform, offer specialised capabilities like imaging, natural language processing, speech recognition, and digital biology simulation.
The suite includes NVIDIA NIM AI models optimised for healthcare applications and industry-standard APIs for easy integration into cloud-native solutions. Additionally, software development kits and tools like Parabricks, MONAI, NeMo, Riva, and Metropolis are now available as NVIDIA CUDA-X microservices to accelerate drug discovery, medical imaging, and genomics analysis workflows.
NVIDIA NIM Healthcare Microservices, a part of this suite, offer optimised inference for various models in imaging, MedTech, drug discovery, and digital health. They include models for generative chemistry, protein structure prediction, molecular interaction analysis, and 3D segmentation. These microservices provide significant speed improvements for tasks like genomic analysis, with over 50 times faster variant calling than traditional methods.
“For the first time in history, we can represent the world of biology and chemistry in a computer, making computer-aided drug discovery possible,” said Powell, during the conference.
Healthcare giants like Amgen, Astellas, DNA Nexus, and Iambic Therapeutics leverage these microservices to improve drug discovery and antibody design using generative AI.
New Foundational Model for Protein Structure Prediction
NVIDIA’s BioNeMo has expanded its capabilities to include new foundation models for various tasks in drug discovery, such as analysing DNA sequences, predicting protein structure changes caused by drug interactions, and identifying cell functions from RNA data.
Among these new foundation models are DNABERT for genomics analysis and scBERT for single-cell RNA sequencing. EquiDock is another model that predicts protein interactions, which is crucial for evaluating the effectiveness of drugs.
These models, along with microservices, are accessible through NVIDIA NIM microservices. Microservices like DiffDock and ESMFold within NVIDIA NIM provide insights into drug candidate structures and protein folding based on amino acid sequences. MolMIM generates drug candidates tailored to user-defined properties and specific protein targets. Soon, these models will also be available on AWS HealthOmics to analyse biological data.
Alphabet has been leading the race of protein prediction with AlphaFold. In November last year, Alphabet-backed Isomorphic Labs and Google DeepMind launched the updated version of AlphaFold 2, which can now predict structures from nearly all molecules in the Protein Data Bank (PDB), including small molecules, proteins, nucleic acids, and molecules with post-translational modifications.
NVIDIA & Johnson & Johnson to Use AI in Surgery
Besides developing over 25 generative AI microservices for healthcare, the company has teamed up with Johnson & Johnson MedTech, a pharmaceutical technology leader, to integrate AI into surgery to improve operating room efficiency and clinical decision-making.
The partnership will let the former deploy AI-powered applications and real-time insights. By leveraging NVIDIA’s IGX and Holoscan platforms, J&J MedTech can process data securely from various devices in the operating room, enhancing surgical outcomes. As a common computing platform, it also facilitates the deployment of third-party models and applications.
J&J MedTech and NVIDIA are working to streamline the development and deployment of AI applications in the operating room. The latter’s Holoscan accelerates creating real-time AI applications for medical use cases, leveraging NVIDIA IGX’s high-speed data streaming capabilities.
By analysing device, patient, and surgical data, AI-powered applications can provide valuable insights to surgeons during procedures, potentially reducing cognitive load and enhancing care delivery.
