Introducing AWS HealthScribe
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.
Deeper insights
Gain longitudinal and 360 views of patient, product, and customer journeys.
Increase productivity & efficiency
Increase productivity and efficiency through seamless automation of routine tasks.
Accelerate time to answers
Faster time to insights and evidence generation.
Security & compliance
Federated, secure multi-party data collaborations for research.
Leverage generative AI
More easily access and securely customize the right Foundation Models while safeguarding data.
Responsible use of AI
Foster trust and encourage safe use of AI in the clinical settings
AWS services
AWS Health Data Portfolio features purpose-built AWS Services designed to help you innovate faster and improve patient outcomes.
More AWS services
Explore AWS reference architectures
Data Mesh on AWS
Facilitate secure collaboration with a scalable data foundation that makes it easier to search, share, discover, and analyze data at-scale across organizational boundaries.
Clinical Data Repository on AWS
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.
Commercial Analytics on AWS
Derive predictive commercial insights by applying analytics across operational data, securely and at-scale.
Multi-modal Data on AWS
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.
Customer stories and case studies
Merck builds clinical data layer on AWS
Matt Studney, Senior Vice President at Merck Research Labs, showcases how his team created a clinical data layer on AWS that brings together clinical and operational data across studies into a single platform, accelerating processes through purposeful applications of automation.
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Vyaire Uses AWS Data Exchange to Keep the World Breathing Better
To be able to make better, data-based decisions utilizing both first-and-third-party data, Vyaire runs its analytics on Amazon Web Services (AWS) and utilizes AWS Data Exchange to find, subscribe to, and use third-party data.
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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.
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How Novo Nordisk built a modern data architecture on AWS
Novo Nordisk is building a data and analytics solution using AWS, built around of the core tenets of the data mesh—decentralized domain ownership of data, data as a product, self-service data infrastructure, and federated computational governance.
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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.
Additional resources
AWS Life Sciences Symposim: Watch the Keynote
More than 1,000 industry leaders from all corners of the life sciences industry converged in New York City for the seventh annual AWS Life Sciences Symposium to discuss the latest advancements in Life Sciences technology. Together, we explored what’s working (and what’s not) with generative AI, and dove into how leading life sciences companies are building for agentic AI success.
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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.
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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%.
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150 Models and Counting: Your Guide to Generative AI Models for Healthcare and Life Sciences
Amazon Web Services (AWS) Marketplace offers the largest curated catalog of healthcare and life sciences AI models and pre-approved enterprise procurement to streamline deployment at scale, quicken discovery of industry-specific models, and integrate quickly into clinical, research, or operational pipelines.
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Accelerating Life Sciences Innovation with Agentic AI on AWS
See how life sciences organizations are using agentic AI on AWS to streamline complex workflows, enhance collaboration, and accelerate research outcomes.
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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).
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