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AWS delivers the most comprehensive set of generative AI capabilities and industry-leading foundation models for healthcare and life sciences organizations.
Accelerate innovations with generative and agentic AI
Leading healthcare and life sciences organizations trust AWS when scaling their enterprise-wide generative AI because of our proven security commitment and industry expertise.
AI and machine learning for healthcare and life sciences on AWS (0:49)
With AWS, you have the right tools for the job. Whether you’re building AI-driven care experiences, creating novel proteins for drug discovery, or democratizing advanced data analytics through natural language queries—AWS offers a comprehensive set of AI capabilities from chips to foundation models to applications, enabling rapid AI innovation.
AWS brings together robust data management, purpose-built AI services, and industry expertise—so you can move from idea to impact, faster. Explore, prototype, and launch impactful AI solutions with our extensive expert support network, including the AWS Generative AI Innovation Center, AWS Partner Network, and AWS Professional Services.
AWS secures your AI future with enterprise-proven protection and reliability—trusted by millions of customers worldwide. AWS provides end-to-end data governance capabilities and more than 146 HIPAA-eligible services and supports 143 security standards and compliance certifications, including HIPAA/HITECH, GDPR, and HITRUST.
AI starts with trust
With AWS, your data remains yours when using generative AI, with rigorous controls to meet data sovereignty and data privacy requirements, while built-in guardrails support the integration of responsible AI and safety. This all runs on the most secure and extensive cloud infrastructure for healthcare and life sciences workloads.
Latest generative AI news in healthcare & life sciences
VIDEO
How EvolutionaryScale developed ESM3, its biological foundation model for proteins
EvolutionaryScale launched a milestone AI model, ESM3, capable of generating novel proteins. ESM3 generated a new Green Fluorescent Protein (GFP). It used Amazon SageMaker HyperPod in the early development of the model.
Aidoc secures landmark FDA clearance for first foundation model-powered clinical AI solution of its kind
Aidoc uses Amazon EC2 P-series instances to train ML models and execute inference processes. It recently secured a landmark FDA clearance for the first foundation model powered clinical AI solution of its kind, its CADt AI solution, specifically for rib fractures triage.
Clario collaborates with AWS to push new boundaries in clinical data analysis with generative AI
Clario’s proprietary generative AI platform orchestrates multiple large language models and deep learning models using AWS infrastructure to achieve best in class results.
Netsmart Reduces the Burden of Clinical Documentation with Generative AI Services on AWS
Learn how Netsmart is reducing the burden of clinical documentation for healthcare providers by building a technology solution that leverages AWS generative AI services.
GE HealthCare Unveils First-of-its-kind MRI Foundation Model
The industry’s first full-body 3D MRI research foundation model, is designed to enable developers to build applications for tasks such as image retrieval, classification, operational efficiency, and report generation.
Leveraging Amazon Bedrock to Accelerate Clinical Trials at AstraZeneca
As clinical trials grow more complex, identifying the right patients and optimizing trial sites is more critical than ever. AstraZeneca is transforming this process with Amazon Bedrock, using text-to-SQL and retrieval-augmented generation (RAG) to merge structured and unstructured data.
How EvolutionaryScale developed ESM3, its biological foundation model for proteins
EvolutionaryScale launched a milestone AI model, ESM3, capable of generating novel proteins. ESM3 generated a new Green Fluorescent Protein (GFP). It used Amazon SageMaker HyperPod in the early development of the model.
Aidoc secures landmark FDA clearance for first foundation model-powered clinical AI solution of its kind
Aidoc uses Amazon EC2 P-series instances to train ML models and execute inference processes. It recently secured a landmark FDA clearance for the first foundation model powered clinical AI solution of its kind, its CADt AI solution, specifically for rib fractures triage.
Clario collaborates with AWS to push new boundaries in clinical data analysis with generative AI
Clario’s proprietary generative AI platform orchestrates multiple large language models and deep learning models using AWS infrastructure to achieve best in class results.
Netsmart Reduces the Burden of Clinical Documentation with Generative AI Services on AWS
Learn how Netsmart is reducing the burden of clinical documentation for healthcare providers by building a technology solution that leverages AWS generative AI services.
GE HealthCare Unveils First-of-its-kind MRI Foundation Model
The industry’s first full-body 3D MRI research foundation model, is designed to enable developers to build applications for tasks such as image retrieval, classification, operational efficiency, and report generation.
Leveraging Amazon Bedrock to Accelerate Clinical Trials at AstraZeneca
As clinical trials grow more complex, identifying the right patients and optimizing trial sites is more critical than ever. AstraZeneca is transforming this process with Amazon Bedrock, using text-to-SQL and retrieval-augmented generation (RAG) to merge structured and unstructured data.
From R&D to clinical trials, life sciences organizations choose generative AI on AWS to improve efficiencies across the value chain. See below for some of the ways our life sciences customers are using generative AI today.
Therapeutic Target Identification and Validation
With generative AI, you can rapidly screen millions of potential drug candidates, simulate their interactions with target proteins, and evaluate their properties. AI agents with natural language interfaces democratize access to these computational tools and datasets, allowing researchers at all technical skill levels to use these resources and accelerate their research.
Clinical Trial Protocol Generation and Enhancement
Generative AI can help streamline clinical trial protocol development by integrating data from various sources and in different formats, suggest appropriate study designs, and incorporate best practices and regulatory guidelines. Generative AI can also help you easily gather insights from clinical data through natural language searches to inform clinical trial protocol generation.
With generative AI, you can generate synthetic defect images to supplement training data used by digital twins, simulate scenarios of different manufacturing conditions, and generate visual predictions of potential future defects.
With generative AI, developing regulated content can be streamlined and accelerated through natural language processing for compliant content generation and expanding your commercial, medical affairs, legal, and regulatory teams’ capabilities with enhanced data analysis, automated compliance checks, and comprehensive content validation.
Generative AI based self-service analytics solution empowers life sciences enterprise users to query real world evidence with natural language, which the tool converts to SQL queries. This allows users to quickly find answers to research questions, identify the most relevant information, draw insights, and discover trends.
With generative AI, sales teams can input free text and flag risks by applying various rules and concepts and surface high-risk classifications to the sellers, managers, or a third-party for validation. The recurring flagging and coaching of potential risks improve compliance, field training, and supplements sales manager efforts.
We are leveraging AI, which is estimated to deliver annual cost savings of $750M to $1B in the near term. Using AWS cloud services, Pfizer quickly deployed Vox, our internal generative AI, allowing colleagues to access large language models available in Amazon Bedrock and Amazon SageMaker.
— Lidia Fonseca, Chief Digital and technology Officer, Pfizer
VIDEO
Pfizer
Pfizer's Digital Transformation: Leveraging AWS and AI to Revolutionize Global Healthcare Delivery
BLOG
Clario
Learn how Clario harnesses the power of large language models using AWS to accelerate clinical document analysis.
From developing foundation models for radiology to creating generative AI tools that enhance health plan member experiences, healthcare organizations choose generative AI on AWS to improve workforce efficiencies and patient care. See below for some of the ways our healthcare customers are using generative AI today.
Clinician Task Automation
With generative AI, you can automate clinician tasks like referral letter generation, comprehensive patient history summarization, patient inbox draft generation, and medical coding automation all integrated into your EHR system.
Generative AI can improve image quality, detect anomalies and patterns, generate synthetic images for training and data augmentation, and provide decision support by highlighting areas of concern, suggesting potential diagnoses, and offering explainable insights into identified anomalies.
Generative AI can transcribe clinician-patient interactions, extract key details, and generate comprehensive notes integrated into EHR systems, which helps improve documentation efficiency and reduce administrative burden.
With generative AI, you can boost call center productivity by summarizing patient information, generating call summaries, and extracting key follow-up actions.
With generative AI, you can efficiently analyze documents and medial records related to prior authorization requests and claims to generate summaries, identify missing documentation, match claims to prior authorizations, and provide evidence-based recommendations for reviewers.
Learn how Solventum uses AWS HealthScribe to automate note-taking, alleviating documentation burden and allowing physicians to focus on patient interactions.
Learn how Philips' cloud- and AI-enabled integrated diagnostics portfolio aims to unify workflows, improve access to critical insights, and drive better outcomes for patients.
Learn how HippocraticAI is using AWS to build its large language model (LLM) that power AI agents capable of natural, real-time conversations with patients.
Learn how Solventum uses AWS HealthScribe to automate note-taking, alleviating documentation burden and allowing physicians to focus on patient interactions.
Learn how Philips' cloud- and AI-enabled integrated diagnostics portfolio aims to unify workflows, improve access to critical insights, and drive better outcomes for patients.
Learn how HippocraticAI is using AWS to build its large language model (LLM) that power AI agents capable of natural, real-time conversations with patients.
Using AWS, our goal at Tufts Medicine is not only to redefine healthcare but to reinvent the way that it is delivered.
— Dr. Shafiq Rab Chief Data Officer, System Chief Information Officer and Executive Vice President, Tufts Medicine
Tools to build and scale generative AI applications
Innovate faster with new capabilities, a choice of industry-leading foundation models (FMs), and infrastructure that pushes the envelope to deliver the highest performance while lowering costs. Explore more generative AI tools
Find additional resources to educate you on generative AI on AWS for healthcare and life sciences.
AWS MACHINE LEARNING BLOG
Evaluate healthcare generative AI applications using LLM-as-a-judge on AWS
Learn how to use Amazon Nova and the newly released RAG evaluation feature for Amazon Bedrock Knowledge Bases, to assess how well healthcare RAG applications retrieve and use medical information to generate accurate, contextually appropriate responses.
Revolutionizing Real-World Evidence: How Generative AI Can Simplify Data Exploration
Learn how modern approaches, notably using Generative AI technology and modern data services can help us explore Real World Data (RWD) such as electronic health records or health insurance claims to simplify RWE generation.
How healthcare payers and plans can empower members with generative AI
Learn how generative AI can enhance the member experience by providing a more intuitive and user-friendly interface, but also has the potential to reduce call volumes and operational costs for healthcare payers and plans.
Amazon Bedrock Guardrails enhances generative AI application safety with new capabilities
Amazon Bedrock Guardrails detects harmful multimodal content with up to 88% accuracy, helps filter sensitive information, and helps prevent hallucinations. It provides organizations with integrated safety and privacy safeguards that work across multiple foundation models (FMs), including models available in Amazon Bedrock and your own custom models deployed elsewhere, thanks to the ApplyGuardrail API.
Evaluate healthcare generative AI applications using LLM-as-a-judge on AWS
Learn how to use Amazon Nova and the newly released RAG evaluation feature for Amazon Bedrock Knowledge Bases, to assess how well healthcare RAG applications retrieve and use medical information to generate accurate, contextually appropriate responses.
Revolutionizing Real-World Evidence: How Generative AI Can Simplify Data Exploration
Learn how modern approaches, notably using Generative AI technology and modern data services can help us explore Real World Data (RWD) such as electronic health records or health insurance claims to simplify RWE generation.
How healthcare payers and plans can empower members with generative AI
Learn how generative AI can enhance the member experience by providing a more intuitive and user-friendly interface, but also has the potential to reduce call volumes and operational costs for healthcare payers and plans.
Amazon Bedrock Guardrails enhances generative AI application safety with new capabilities
Amazon Bedrock Guardrails detects harmful multimodal content with up to 88% accuracy, helps filter sensitive information, and helps prevent hallucinations. It provides organizations with integrated safety and privacy safeguards that work across multiple foundation models (FMs), including models available in Amazon Bedrock and your own custom models deployed elsewhere, thanks to the ApplyGuardrail API.
Evaluate healthcare generative AI applications using LLM-as-a-judge on AWS
Learn how to use Amazon Nova and the newly released RAG evaluation feature for Amazon Bedrock Knowledge Bases, to assess how well healthcare RAG applications retrieve and use medical information to generate accurate, contextually appropriate responses.
.70b2625f73315a6a1e18c508f861b287ad8471da.jpeg "Netsmart Reduces the Burden of Clinical Documentation with Generative AI Services on AWS")
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