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Integration of Nvidia’s microservices and AWS will enable healthcare and life sciences companies to tackle complex challenges in drug discovery and digital health.
US chip giant Nvidia yesterday (2 May) announced the integration of its NIM cloud-native microservices with Amazon Web Services (AWS), in what is a significant development for the advancement of digital health and drug discovery.
VP of healthcare for the company Kimberly Powell made the announcement at the AWS Life Sciences Leader Symposium in Boston.
The collaboration represents a potentially transformative leap for the healthcare sector as it will give access to a vast collection of AI tools, including “foundation models for drug discovery, medical imaging and genomics, backed by enterprise-grade security and support”.
Professionals can access NIM through Amazon SageMaker, where they will have the power to prepare data and build, train and deploy machine learning models.
Additionally, NIMs can be utilised across AWS HealthOmics, a purpose-built service for biological data analysis.
In a blog post yesterday, Nvidia’s Lyndi Wu wrote that “easy access to NIM will enable the thousands of healthcare and life sciences companies already using AWS to deploy generative AI more quickly, without the complexities of model development and packaging for production.
“It will also help developers build workflows that combine AI models across different modalities, such as amino acid sequences, MRI images and plain-text patient health records.”
Companies are already benefitting from the cross-collaboration and convergence of AI and healthcare, include the biotech Amgen, which “used the BioNeMo framework to train generative models for protein design, and are exploring the potential use of BioNeMo with AWS”.
The platform also offers “optimised large language models for conversational AI and visual generative AI models for avatars and digital humans,” enhancing care by answering patients’ queries and providing clinicians with relevant logistics.
In March, the high-flying software company revealed powerful new GPU architecture called Blackwell to enable AI training and real-time large language model inference for models containing up to 10trn parameters.
Commenting on the announcement, Powell said, “Putting generative AI into the hands of drug discoverers accelerates exploring the universe of drugs and predicts which have the best efficacy, safety and manufacturability, all in silico.
“Researchers can deploy a growing catalog of Nvidia NIM generative AI models with AWS HealthOmics, delivering powerful AI drug discovery solutions with unparalleled speed, scalability and flexibility.”
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Updated 17:17pm, 3 May 2024: This article was updated to add a quote from VP of healthcare Kimberly Powell.
