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  • 3M Health Information Systems (HIS) Case Study

    By going all in on AWS, 3M Health Information Systems (HIS) provisions compute resources in minutes instead of weeks, develops and deploys software in one week instead of six, and innovates faster. 3M HIS enables customers to efficiently document, code, classify, store, and measure healthcare delivery with integrated software and services, enabling complete, compliant, and accurate payments. 3M HIS customers also analyze the total cost, quality, and outcomes for patients and populations, using 3M data-analytics applications. 3M HIS runs several advanced applications on AWS.

  • Avizia Case Study

    By adopting the AWS Cloud, Avizia ensures its telehealth solution is compliant with regulations and delivers high performance and availability to more than 400 healthcare customers. The company is a global telemedicine provider with a cloud-based platform that provides business intelligence, medical workflow, and secure collaboration tools through web applications, mobile apps, and connected hardware. Avizia deploys Amazon RDS for PostgreSQL as its relational database engine to provide the redundancy the company needs to serve customers around the world.

  • AWS Case Study: Arterys

    Arterys offers a medical imaging solution that enables radiologists and cardiologists to improve the process of diagnosing and staging cardiovascular disease in patients. The company is using AWS to render, analyze, and store multi-dimensional models of MRI scans each producing 5 to 10 GB of data. By using AWS, the company can render multi-dimensional models of the heart across all device types in 10 minutes or less instead of the 90-minute industry standard, and scale the platform to handle its growing storage needs.

  • AWS Case Study: Bristol-Myers Squibb

    When Bristol-Myers Squibb (BMS) needed a cost-effective solution to host research data for scientists, the global biopharmaceutical company decided to use AWS to build a secure, self-service portal. As a result, BMS can take advantage of on-demand capacity to keep costs low and run clinical trial simulations 98% faster than its previous environment.

  • AWS Case Study: Claritas Genomics

    After spinning out from its parent company, Claritas Genomics needed a low-cost IT environment for its clinical diagnostics laboratory. The company took advantage of AWS Security and Compliance to build a genetics platform that met HIPAA requirements. By using AWS, Claritas has lowered its IT costs by 30% per month, so it can invest its limited resources in the business instead of IT.

  • AWS Case Study: Corporate Governance Risk

    Corporate Governance Risk Pty Ltd (CGR), developer of a web-based risk management application, found that moving to the AWS Cloud gave the company a competitive edge to deliver services to its European clients in seconds with virtually zero downtime.

  • AWS Case Study: DNAnexus

    DNAnexus delivers a platform as a service for genomic researchers at more than 100 enterprises across the globe. To support large-scale genomic studies, the company turned to AWS for its high-performance compute and storage to run the DNAnexus genome informatics and data management platform. On AWS, DNAnexus scales to tens of millions of core hours of analysis and stores petabytes of data in a HIPAA-compliant environment.

  • AWS Case Study: Healthdirect Australia

    Healthdirect Australia uses AWS to deliver services quickly across the entire country, including remote areas, while controlling costs and supporting a 300 percent growth in one year in the number of unique visitors to its websites. The public company provides a range of health and related services, information, and advice, and operates Australia’s National Health Services Directory. It uses a range of AWS products to support its web presence and deliver information to doctors, clinics and hospitals, and consumers.

  • AWS Case Study: Lingit

    After creating software that helps individuals with dyslexia, Lingit turned to Atbrox, a Norwegian-based company focusing on data mining/data analysis and cloud-based solutions, to assist with up to terabyte-sized structured sets of texts.

  • AWS Case Study: MedStar Health

    MedStar Health, the largest not-for-profit healthcare system in Maryland and the Washington, D.C., region, wanted to offer patients an easy way to search for doctors, medical services, and locations, and to make appointments. To deliver a patient-first experience, the healthcare system decided to combine its disparate websites into a single, searchable portal using AWS. By creating a centralized patient engagement portal on AWS, MedStar has dramatically increased website availability and page download speeds, while lowering monthly operating costs for the portal by more than 40 percent.

  • AWS Case Study: Orion Health

    Orion Health is one of the leading global providers of health information exchange (HIE) and healthcare integration solutions. The company engaged APN consulting partner Logicworks to help build Cal INDEX, a California statewide HIPAA-compliant HIE using AWS. By using AWS, Orion Health can scale its platform to handle millions of patient records.

  • AWS Case Study: Penn State

    Penn State’s Biological Engineering Department wanted to make its research results widely available to scientists. Penn State uses AWS to host and distribute its research design methods, optimization algorithms, and results with 6,000 scientists all over the world. By using AWS, Penn State has allowed researchers to design more than 50,000 synthetic DNA sequences.

  • AWS Case Study: Philips uses Redshift for Big Data

    Philips is a Dutch diversified technology company with sales and services available in more than 100 countries. The company’s U.S. healthcare division used Attunity CloudBeam, available on the AWS Marketplace, to upload 37 million records from an on-premises database to the AWS Cloud in just 90 minutes. By hosting its data on AWS, Philips can optimize any size data set within two hours, allowing its consultants and analysts to provide solutions quickly to its customers.

  • AWS Case Study: Siemens

    Siemens Healthcare Diagnostics’ mission is to deliver better patient care at a lower cost. With AWS, Siemens has built an analytics platform to help caretakers personalize patient treatment plans through companion diagnostics testing. AWS provides Siemens with tools like AWS CloudTrail, Amazon CloudWatch, Auto Scaling, AWS CloudFormation, and AWS Identity and Access Management (IAM) to become more agile and achieve their mission.

  • AWS Case Study: University of California Berkeley AMP Lab's Carat Project

    The Algorithms, Machine, and People (AMP) Lab at the University of California Berkeley is a multi-disciplinary research effort designed to build scalable machine learning and data analysis technology. With the help of AWS, the AMP Lab team is able to scale up experiments and try new software on realistic configurations across thousands of computers. The AWS Cloud provides the AMP Lab access to low-cost infrastructure and on-demand computing resources, which support big data projects that include Carat, an application created to help measure energy productivity and improve battery life on cell phones.

  • AWS Case Study: US Centers for Disease Control and Prevention (CDC)

    The US Centers for Disease Control and Prevention’s (CDC) BioSense program tracks public health problems to better prepare for and coordinate responses to safeguard the wellbeing of the American people. The CDC recently re-launched BioSense 2.0 on the AWS Cloud in AWS GovCloud (US) and other Regions. With AWS, the CDC can better share important health information among public health professionals and with partners in state and local governments while avoiding costly investments in hardware.

  • Baylor Case Study

    The Baylor College of Medicine is a leading contributor to the CHARGE Project, a group of more than 200 scientists who are working to identify genes that contribute to aging and heart disease. Baylor’s collaboration with the CHARGE researchers required a secure, scalable genomic analysis platform. By using AWS, CHARGE can analyze genome sequences 5 times faster than with traditional infrastructure and store 430 TB of data.

  • Benchling Case Study

    Benchling reduces its CRISPR search times from 30 seconds to under 3 seconds, scales to support CRISPR workflows for more than a hundred organisms, and saves thousands of dollars monthly using AWS. The company provides a complete R&D platform used by thousands of life science researchers across the globe. Benchling runs its genome search platform on AWS, taking advantage of AWS Lambda serverless architecture.  

  • Caltech Guttman Lab Case Study

    The Guttman Lab at the California Institute of Technology uses an AWS-based high-performance computing (HPC) cluster to quickly add new compute nodes, analyze genomic sequencing data in days instead of weeks, and easily manage cluster access credentials. Led by Dr. Mitch Guttman, the Guttman Lab is a Pasadena, California–based research laboratory specializing in the study of large noncoding RNA genes. The lab runs its growing HPC cluster on AWS, using Amazon Virtual Private Cloud to launch resources in a defined network and Amazon WorkSpaces and Simple AD to manage access.

  • Cambia Health Solutions Case Study

    Cambia Health Solutions uses AWS to enable startup healthcare companies to get to scale quickly while providing high levels of security for sensitive information and meeting compliance requirements. Cambia Health Solutions creates and invests in innovations designed to serve the changing needs of individuals and families, including a wide range of companies within its Direct Health Solutions Network. Within the portfolio of Direct Health Solutions companies, Wildflower uses AWS to deliver its pregnancy app to more than 50,000 women and HealthSparq delivers its healthcare price transparency app to more than 70 health plans covering 70 million members.

  • Celgene Case Study

    Celgene uses AWS to enable secure collaboration between internal and external researchers, allow individual scientists to launch hundreds of compute nodes, and reduce the time it takes to do computational jobs from weeks or months to less than a day. Celgene is a global biopharmaceutical company that creates drugs that fight cancer and other diseases and disorders. Celgene runs its high-performance-computing research clusters, as well as its research collaboration environment, on AWS.

  • Change Healthcare Case Study

    By using AWS, Change Healthcare can develop and test new services for its customers quickly, and it can scale to meet large demand while minimizing IT costs and complexity. Change Healthcare—previously known as Emdeon—is the largest health administrative network in the United States, processing claims, pharmacy requests, and performing other functions for more than 340,000 physicians and 60,000 pharmacies. Change Healthcare uses AWS services like Amazon EC2, Amazon S3, Amazon SQS, and Amazon SNS to handle millions of confidential transactions daily from its clients while staying in full compliance with healthcare industry regulations, including HIPAA.  

  • Cleveland Clinic Case Study

    The Cleveland Clinic runs its Healthy Brains Initiative on AWS, lowering operating costs so it can focus on bringing value to patients. The Cleveland Clinic is a multispecialty academic hospital based in Cleveland, Ohio. The clinic worked with AWS Certified Partner ClearDATA to ensure that the Healthy Brains Initiative, which gives patients and neurologists a way to enter and analyze information about conditions and activities that affect brain health, meets the clinic’s standards for protecting patient privacy.  

  • Cochlear Case Study

    Cochlear uses AWS for an automated solution that gets replacement parts for hearing devices delivered to customers in 24 hours or less. The Australian company is a leading provider of implantable medical devices used by people who are profoundly deaf. The application stack it built on AWS streamlines replacement parts ordering, minimizing the time that customers go without their sound processors and eliminating time-consuming parts processing tasks for clinicians.

  • Core Informatics Case Study

    By using AWS, Core Informatics quickly and securely deploys GxP-regulated applications, enabling life sciences customers to trace their products throughout the development cycle and save money. Core Informatics provides web-based laboratory management and informatics software to large life sciences and pharmaceutical companies, as well as midsize and startup organizations. The organization runs its lab informatics solutions—including Laboratory Information Management Systems (LIMS)—on the AWS Cloud. 

  • Dr. Lal Pathlabs Case Study

    Dr. Lal PathLabs eliminates downtime for applications to book medical tests and obtain test results online by migrating to AWS. Dr. Lal PathLabs is a leading diagnostic company offering healthcare-related diagnostic tests in India. The company uses Amazon EC2 instances for applications and databases that support test scheduling and results collection, as well as Amazon S3 to store all medical-test results.  

  • FIGmd/EHNAC Case Study

    FIGmd demonstrates compliance with healthcare industry regulations, gives healthcare organizations confidence their data is protected, and differentiates its business by using AWS and earning EHNAC cloud accreditation. The company offers clinical-data registries and other solutions to a range of healthcare organizations throughout the United States. FIGmd runs its clinical-data registries on the AWS Cloud.

  • Flatiron Health

    Flatiron Health delivers software faster, organizes and improves the quality of oncology data, and ensures regulatory compliance by running its applications on AWS. The company provides software to clinicians to manage their practice, workflow, and patient health information. Flatiron runs its critical data-management and research applications on AWS. 

  • GENALICE Case Study

    During a live webinar, biomedical startup GENALICE processed genomes from 800 Alzheimer’s disease patients in just 60 minutes, which would have taken its competitor more than two weeks to complete. GENALICE develops breakthrough software for analyzing big data relating to complex DNA diseases. It uses Amazon Web Services to run the Population Calling module of its GENALICE MAP Next-Generation Sequencing data analysis suite.  

  • Harvard Medical School Case Study

    The Laboratory for Personalized Medicine (LPM), of the Center for Biomedical Informatics at Harvard Medical School took the power of high throughput sequencing and biomedical data collection technologies and the flexibility of AWS to develop innovative whole genome analysis testing models in record time.

  • Health Guru Case Study

    Health Guru is one of the leading providers of online health information videos. Faced with scalability and performance challenges, the company switched to AWS, resulting in a 92.5% improvement in web service performance.

  • Healthcare.gov Case Study

    The Centers for Medicare and Medicaid Services (CMS) is part of the U.S. Department of Health and Human Services and is responsible for Healthcare.gov, the portal where consumers can find information and sign up for insurance plans under the Affordable Care Act. CMS turned to Amazon Web Services to launch three new features for the website, including an identity management system, a feature for comparing insurance plans, and a tool to determine eligibility for specific plans based on a consumer’s income and other variables. By using AWS, CMS has been able to deliver a stable and highly scalable set of features capable of handling hundreds of thousands of simultaneous users during peak insurance signup periods.

  • Icahn School of Medicine at Mount Sinai Case Study

    The Icahn School of Medicine at Mount Sinai is looking for clues to the genetic causes of breast and ovarian cancers. The team uses AWS to search and analyze more than 100 TB of genomics data to investigate the causes of those aggressive forms of cancer.

  • iFit Case Study

    Using AWS, iFit gains the flexibility to meet peaks in site visitors while reducing IT management costs by up to 80 percent. iFit—which promotes healthy lifestyles through its app and wearable devices—is an online community, an e-commerce platform, and a chain of main-street stores. The company runs its website on Amazon EC2 instances with Amazon S3 and Amazon CloudFront ensuring fast access to site content, and Amazon RDS supporting site transactions.

  • Igenomix Case Study

    Using AWS, Igenomix has the on-demand capacity to run highly data-intensive next-generation sequencing (NGS) workloads, so it can analyze 1,150 percent more samples and gain a competitive edge in genetics testing. The company provides services and solutions to address fertility issues, helping its patients to become pregnant and have healthy children. It uses Amazon EC2 and Amazon S3 to process and store tens of terabytes of data for its genetics testing.

  • Illumina Case Study

    Illumina uses AWS to globally scale its DNA sequencing technologies while driving down costs by 100X and meeting the security requirements of different countries and customers. The company is a leader in providing DNA sequencing and array-based technologies for customers in the research, clinical, and applied markets, with 90 percent of all DNA sequencing worldwide being performed on Illumina machines. Illumina uses products like Amazon Redshift to support its BaseSpace Sequence Hub that currently stores 10 petabytes of genomics data. 

  • InhibOx Case Study

    Pharmaceutical company, InhibOx, requires virtually unlimited compute capacity for drug discovery research. AWS provides the capacity that InhibOx needs while reducing computing costs by hundreds of thousands of dollars.

  • Intermountain Healthcare Case Study

    Intermountain Healthcare, using Amazon Web Services and working with APN partner Syapse, can provide fast, cloud-based services to oncologists across the United States so they can deliver precision medicine to cancer patients. Intermountain Healthcare, a large health system based in Utah, uses a cloud-based platform from Syapse that works on AWS, delivering a platform that combines genomic information, clinical data, and other information to deliver actionable information to clinicians.  

  • MiHIN Case Study

    The Michigan Health Information Network Shared Services (MiHIN) uses AWS to process more than 12 million patient health information messages weekly, keep pace with 20 percent growth in demand for new services, and build and test new features in days rather than months. MiHIN enables the exchange of health information throughout the state of Michigan. The company’s network is used by Michigan healthcare providers and payers to securely share patient information. MiHIN is all-in on AWS, running its health-information network in the AWS Cloud.

  • Murdoch University Case Study

    Australia’s Murdoch University Centre for Comparative Genomics (CCG) completes cattle-tick genomic analysis months faster, helps create new anti-tick vaccines, and has better control over its research processes using AWS. CCG undertakes bioinformatics and molecular therapy research and development, and provides research services. The Centre runs its genomic-analysis platform on the AWS Cloud.

  • New York University Langone Medical Center Case Study

    The High Performance Computing Facility of the New York University (NYU) Center for Health Informatics and Bioinformatics was established in 2009 to deliver forefront-computing capabilities to researchers at the NYU Langone Medical Center. The facility uses Globus Online, a free file transfer service hosted and powered by Amazon EC2, as well as Amazon S3 to allow medical informatics and bioinformatics researchers to share data and enable research computing needs that exceed local capacity limits.

  • Novartis Case Study

    Novartis Institutes for Biomedical Research’s (NIBR) purpose is to cure, care, and provide medicines that treat and prevent diseases, ease suffering and improve quality of life. NIBR maintains a global research network of 6,000 scientists that have 130 projects in development that combine clinical insights with mechanical understanding – focusing on the molecular pathways shared by various diseases. With an average time and cost to take a drug to market of 10 years and about $1 billion, NIBR wants to reduce these numbers using high performance computing.

  • Oscar Insurance Case Study

    Oscar Insurance built a technology and data-driven health insurance company from the ground up in just three months on AWS while meeting HIPAA compliance requirements. The company uses AWS to run its insurance platform, customer databases, and analytics solution. By using AWS, Oscar Insurance was able to process more than 25 million historical insurance claims in hours and launch its platform on time.

  • Philips Healthcare Case Study

    Philips’ Healthcare Informatics Solutions and Services division manages and analyzes data for health care providers around the world. The company hosts its digital healthcare platform, Philips HealthSuite, on AWS to manage and analyze 15 PB of patient data and scale as the platform grows at the rate of one petabyte per month. By using AWS, Philips can build secure and compliant environments to reinvent healthcare for billions of people around the globe.

  • San Francisco State University Case Study

    San Francisco State University, in collaboration with the Stanford Helix Group, needed to accelerate computations for their research project, FEATURE. Using machine learning techniques and Amazon EC2, the teams were able to complete research that previously would have taken them weeks in just hours while reducing computing costs.

  • Seven Bridges Genomics Case Study

    Seven Bridges Genomics uses AWS to provide researchers with IGOR, a cloud platform that helps them analyze DNA sequencing data. Using AWS has helped enable Seven Bridges to provide their customers with complex genetics analysis at a large scale and at low cost—typically saving researchers 40% compared to in-house solutions.

  • Sparta Systems Case Study

    Sparta Systems uses the AWS Cloud to host quality-management systems for the life sciences industry that maintain data integrity, foster collaboration across a company’s quality ecosystem, and enable customers to deliver safer products to consumers. Sparta Systems hosts a solution on which pharmaceutical and medical-device companies can operate validated workloads that can be secured, analyzed, and verified by regulatory agencies. Using a variety of AWS services, it helps these customers minimize the costs and work interruptions that come with regulatory investigations and manage quality for processes across their entire production life cycle.

  • Thermo Fisher Case Study

    Thermo Fisher is one of the world’s leaders in serving scientists with tools and technologies that enable better research globally. To help accelerate science, the company built its new Thermo Fisher Cloud on AWS where it helps scientists and researchers store, analyze, and share medical data. By using AWS, the company was able to build this new solution in less time and at lower costs than what would have been required by an on-premises solution.

  • TraceLink Case Study

    Using AWS, TraceLink helps life sciences companies achieve compliance with global track-and-trace regulations in GxP-compliant environments, scales its data-exchange network to support hundreds of thousands of supply chain partners, and helps companies save millions of dollars. The organization provides a track-and-trace network that connects life sciences companies and stops counterfeit drugs from entering the marketplace. TraceLink runs its cloud-based track-and-trace solution and data exchange on the AWS Cloud. 

  • UCarer Case Study

    Using AWS, Ucarer has reduced IT costs by about 30 percent and eliminated 97 percent of the workloads associated with one routine management task. The company developed an app-based service for the elderly to book appointments with registered caregivers in the local community. Ucarer runs the platform behind its service on AWS using Amazon EC2 instances for platform code and Amazon RDS for storing data relating to caregivers and platform users. 

  • uMotif Case Study

    Using AWS, uMotif facilitates medical research by improving the quality of data captured during clinical studies. The company’s software makes it easy for patients to record their experiences during a study, using mobile devices like tablets and smartphones. The data is then regularly synced to a cloud-based, backend infrastructure running on the AWS Cloud.

  • University of California Berkeley AMP Lab's Genomics Research Project Case Study

    The Algorithms, Machine, and People (AMP) Lab at the University of California Berkeley is a multi-disciplinary research effort designed to build scalable machine learning and data analysis technology. With the help of AWS, the AMP Lab team is able to scale up experiments and try new software on realistic configurations across thousands of computers. The AWS Cloud provides the AMP Lab access to low-cost infrastructure and on-demand computing resources, which support projects that include analyzing genome sequencing data to help advance cancer research.

  • University of Chicago Case Study

    The University of Chicago’s Computation Institute builds solutions to provide “science as a service” to researchers. The Institute uses AWS to host its Globus Transfer and Globus Genomics services and offer more than 99% availability to its customers.

  • Verge Health Case Study

    By using AWS, Verge Health shortened the time to deploy HIPAA-compliant development environments from three weeks to just a few minutes. Founded in 2001, Verge Health provides the governance, risk, and compliance platform of choice for more than 900 health systems and hospitals nationwide. The company uses AWS Service Catalog to self-provision the resources it needs to create comprehensive health care risk management solutions that meet industry-specific compliance and security requirements.

     

  • We Feel Case Study

    The Black Dog Institute (BDI) is a nonprofit Australian research body dedicated to improving the diagnosis, treatment, and prevention of various mood disorders. The institute partnered with CSIRO, Australia’s national science agency, to conduct the We Feel study, which uses AWS to analyze tweets from around the world and measure how emotions are impacted by environmental factors. By using AWS, BDI can analyze more than 27 million tweets per day in real time and scale its resources to handle up to 28,000 website visitors per day.

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