Extracting insights from omics and other data modalities.
Download the new multi-modal & multi-omics E-book and learn how AWS can power the new era of data-driven personalized health with both native services and AWS Partner solutions.
Generating more holistic insights from your data
From research, to drug discovery, to the point of care, the unified analysis of various forms of medical and omics data is helping researchers and clinicians generate new insights and offer more personalized care.
To make it easier for healthcare and life sciences organizations to unify and analyze multiple data modalities, AWS for Health offers a curated portfolio of purpose-built AWS and AWS Partner solutions.
With AWS, health organizations can more easily unify siloed data, transform unstructured medical data, and conduct intensive querying and search.
Simplifying Muti-modal & Multi-omics with AWS for Health
Whether looking to build a bespoke solution or an out-of-the-box implementation, AWS for Health provides purpose-built services, industry tools, and partner solutions to help unify and analyze varying forms of medical data.
Unify disparate structured and unstructured datasets within a secure and compliant environment.
Customer stories
Advancing personalized healthcare using multi-modal data on AWS
Roche developed Apollo on AWS to streamline and scale multi-modal analysis, uniting real-world clinical trial, imaging, pathology, radiology, electronic health records (EHRs), wearables, and genomic data.
Roche reduced time to process EHR data from 2 days down to minutes, cost-efficiently scaled to store data from over 200,000 patients, and support 1,300 scientists across 40 Roche sites globally.
Philips’ oncology solution built on Philips Healthsuite and powered by AWS uses multimodal data to inform personalized cancer care
Philips’ oncology solution built on Philips Healthsuite and powered by AWS uses multimodal data to inform personalized cancer care.
Catalyzing the next generation of cancer care
Genomics England uses AWS to combine disparate data sets that were previously siloed and held in different formats and systems, across different health disciplines. Now, the organization uses AWS AI and ML to analyze the data in tandem, generating a more holistic picture of cancer.
DDRCC at Stanford University uses AWS for research in precision medicine leveraging multimodal data
To facilitate precision medicine research, DDRCC created a health management system for consumers which provides efficient data acquisition, storage, and near-real-time analysis capabilities for researchers using AWS.
DNAnexus & AWS power technology behind UK Biobank research analysis platform
DNAnexus leverages AWS to build and operate a scalable platform enabling approved users to securely view and analyze "soft copies" of UK Biobank's petabyte of biomedical database and research resources.
Build
Build end-to-end analysis workloads with Amazon Omics. And integrate additional data modalities with the Guidance for Multi-omics and Multi-modal Data Integration and Analysis on AWS.
Buy
AWS for Health technology and consulting partners offer out-of-the-box deployments and specialized IT consulting to help you quickly get up and running.
Build
Leverage AWS services and guidances to build bespoke solutions.
The lung cancer survival prediction solution powered by SageMaker JumpStart builds a multimodal ML model for predicting survival outcome of patients diagnosed with NSCLC. The multimodal model is trained on data derived from different modalities or domains, including medical imaging, genomic, and clinical data.
Accelerate research and innovation, risk analysis and solution development with third-party data sets on AWS Data Exchange. The Synthea synthetic patient generator models the medical history of synthetic patients covering every aspect of healthcare for a variety of secondary uses in academia, research, industry, and government.
To help healthcare and life sciences organizations build their own solutions, this AWS guidance provides a comprehensive framework detailing how to combine AWS services to build end-to-end workflows.
Featured AWS for Health partner Bioteam, a scientific IT consulting company with expertise in applying strategies, advanced technologies, and IT services, can help implement and customize this guidance to ingest and process customized datasets.
Buy
AWS for Health provides a curated portfolio of AWS Partner solutions designed to simplify the handling and analysis of multi-modal, multi-omics data.
DNAnexus offers a secure, scalable, and purpose-built cloud platform built on AWS that leverages multi-modal and multi-omic data to drive precision medicine insights.
Illumina Connected Analytics (ICA), a production bioinformatics platform deployed on AWS, delivers a comprehensive suite of data analysis and management tools. Integrating Illumina Correlation Engine with ICA streamlines searching public data sets for similar signatures in other biological samples enabling phenotypic exploration for multi-omic insights.
Philips HealthSuite Platform, built on AWS, makes it simpler for oncology teams to deliver personalized therapy to patients by integrating genomic data with other modalities like imaging, digital pathology, and clinical data.
The Lifebit Platform, powered by AWS, is an end-to-end solution enabling organizations to harness the power of large-scale, clinical-genomic data to drive research and clinical insights.
Resources
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.
Simplifying Multi-modal & Multi-omics Analysis with AWS for Health
Read how to prepare genomic, clinical, mutation, expression, and imaging data for large-scale analysis, and perform interactive queries using The Cancer Genome Atlas (TGCA) and The Cancer Imaging Archive (TCIA) as an example dataset. The ETL code provided in this guidance can be customized to ingest and transform additional datasets.
Fauna bio leverages AWS to harmonize multi-omic datasets and uncover genes relevant to human health
Watch Fauna Bio discussing how it created a platform hosted by AWS that allows users to choose among comparative genomics, transcriptomics, and epigenomics data; select affected tissues of interest; designate the type of therapy to potentially develop; and then see a visual map of resulting gene networks.
Integrate and derive insights from multi-modal health data
Learn how purpose-built health AI services like Amazon Omics, Amazon HealthLake and Amazon Comprehend Medical help healthcare and life science organizations store, query, and analyze health data to generate insights that accelerate decision-making and deliver better care.
AWS Online Tech Talks: Building data mesh architectures on AWS
Learn how to design, build, and operationalize a data mesh architecture on AWS, one that helps businesses navigate their data challenges, optimize analytics processes, and deliver insights to the business faster.
