Accelerate access to and insights from your first-party, third-party, and multi-modal data with the most comprehensive set of data capabilities and deepest set of artificial intelligence (AI) and machine learning (ML) services.
Introducing AWS HealthScribe
HealthScribe is a HIPAA-eligible service empowering healthcare software vendors to build applications that automatically generate clinical notes by analyzing patient-clinician conversations. Health Scribe combines speech recognition and generative artificial intelligence (AI).
Unlock the full potential of your healthcare and life sciences data with AWS
Organizations in the heavily-regulated healthcare and life sciences industries – from biopharmas to healthtechs to providers and payors – need to accelerate time to diagnosis and insights, increase the pace of innovation, and bring differentiated therapeutics to market faster with an end-to-end data strategy. AWS provides a centralized hub for innovation and collaboration on a global level, connecting you with the data and machine learning tools you need, and partners you can trust, all while keeping health and life sciences data secure and private.
AWS Health Data Portfolio aligns purpose-built AWS Services and AWS Partner solutions to business needs, ranging from secure data transfer, aggregation, and storage to data analytics, collaboration, sharing, and governance. With generative AI and purpose-built machine learning services, you can easily integrate cutting-edge technologies into your existing workflows to accelerate innovations and fuel new discoveries.
Better business and patient outcomes with data
AWS helps healthcare and life sciences organizations store, transform, access, and analyze multiple types and modes of data to optimize drug discovery, disease prevention, diagnosis, and treatment.
Increase productivity & efficiency
Accelerate time to answers
Security & compliance
Leverage generative AI
Responsible use of AI
AWS Health Data Portfolio features purpose-built AWS Services designed to help you innovate faster and improve patient outcomes.
Explore AWS reference architectures
Facilitate secure collaboration with a scalable data foundation that makes it easier to search, share, discover, and analyze data at-scale across organizational boundaries.
Ingest, classify, and securely share clinical datasets at-scale across organizational boundaries to uncover insights from disparate datasets to improve clinical operations and clinical development.
Derive predictive commercial insights by applying analytics across operational data, securely and at-scale.
Prepare genomic, clinical, mutation, expression, and imaging data for large-scale analysis and perform interactive queries against a data lake.
Pfizer deploys an efficient, scalable, and automated method to run custom-built digital biomarkers on trial participants’ wearable device data from large global clinical trials.
Using AWS to build a solution that is scalable, flexible, secure, and reproducible. GxP compliant, serverless, event-based architecture that allows for full automation of the pipeline and facilitates parallel processing.
How Evolvere Biosciences performs macromolecule design on AWS
Learn how Evolvere Biosciences is able to build and deploy its protein design platform on AWS using AWS CloudFormation and AWS CodeBuild running algorithms such as AlphaFold and OpenFold.
Boehringer Ingelheim establishes data-driven foundations using AWS to accelerate the launch of new medicines
Learn how Boehringer Ingelheim is transforming its ability to develop breakthrough treatments with its Dataland solution built on AWS.
How Moderna and Takeda accelerate drug research using real-world data
Moderna and Takeda explains why they adopted AWS Data Exchange and Amazon Redshift as integral components of their real-world data (RWD) strategy to source, evaluate, subscribe to, and use RWD from data providers.
GE Healthcare builds One Data Platform on AWS, scales to support 20,000+ business users
GE Healthcare turns to AWS to build the One Data Platform, an internal infrastructure powered by a data lake on Amazon S3 and other AWS services to ingest, store, and process petabytes of data, collect machine data from over four million medical devices worldwide, and provide near-real-time data to over 40 downstream systems.
Unlock greater insights with multi-modal & multi-omics data integration & analysis
Did you know leveraging multi-modal data domains―genomics, clinical, and imaging―can yield 34% accuracy improvements in predictive capabilities over a singular data domain such as genomics?
The new multi-modal & multi-omics E-book identifies several real-world customer case studies leveraging MMMO data meshes, detailing approaches to simplify building or deploying out-of-the box solutions to turn data into an asset and drive more data-driven decision making.
AWS re:Invent 2022 - Building data mesh architectures on AWS
Learn how to design, build, and operationalize a data mesh architecture on AWS so you can navigate data challenges, optimize analytics processes, and deliver insights to the business faster.
Guidance for Protein Folding on AWS
This Guidance helps researchers run a diverse catalog of protein folding and design algorithms on AWS Batch, adding support for new protein analysis algorithms while optimizing cost and maintaining performance.
Gilead accelerates development of enterprise search tool using machine learning on AWS
Learn how Gilead built a scalable enterprise search tool in less than a year that uses AI & ML to provide predictive analytics and find important documents, knowledge, and data across both structured and unstructured data from up to nine enterprise systems, reducing search times by roughly 50%.
Rush University System for Health creates a population health analytics platform on AWS
Learn how Rush University System for Health (RUSH) developed a comprehensive picture of patient risk using AWS HealthLake, resulting in advancing health equity through data interoperability and advanced analytics.
Meet Large Language Models
Dr. Werner Vogels Amazon CTO, sits down with AWS Distinguished Scientists Sudipta Sengupta and Dan Roth to demystify large language models (LLMs)
Building the Brain Knowledge Platform with the Allen Institute for Brain Science
Hear how the Allen Institute is using the cloud to build the Brain Knowledge Platform (BKP) for the U.S. National Institutes of Health (NIH) BRAIN Initiative Cell Atlas Network (BICAN).