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AWS offers Competency programs for customers to find AWS partners who have demonstrated technical proficiency and proven customer success in specialized solution areas.

Healthcare Competency Partners
Consulting and technology partners that have demonstrated success in building solutions to help healthcare providers and payers securely store, process, transmit, and analyze clinical information.

Life Sciences Competency Partners
Consulting and technology partners that help customers conduct drug discovery, research and develop novel genetic-based treatments, manage clinical trials, and engage in biopharma manufacturing and distribution activities. 

This paper briefly outlines how companies can use Amazon Web Services to power HIPAA-compliant information processing systems.

This whitepaper focuses on common issues raised by Amazon Web Services (AWS) customers about security best practices for human genomic data and controlled access datasets, such as those from National Institutes of Health (NIH) repositories like Database of Genotypes and Phenotypes (dbGaP) and genome-wide association studies (GWAS). Our intention is to provide you with helpful guidance that you can use to address common privacy and security requirements. However, we caution you not to rely on this whitepaper as legal advice for your specific use of AWS. We strongly encourage you to obtain appropriate compliance advice about your specific data privacy and security requirements, as well as applicable laws relevant to your human research projects and datasets.

This whitepaper provides a high-level overview of recent trends in healthcare analytics, including current adoption of cloud-based solutions among healthcare providers and an outlook on the future.

This whitepaper outlines the considerations organizations with GxP requirements should take when deploying systems in the AWS Cloud. Topics covered include suggestions for updating your quality system, how to incorporate the cloud into your system development life cycle, and how your regulatory affairs department should treat cloud-based applications.

This whitepaper outlines considerations for the use of cloud-based high performance computing when conducting pre-clinical biotechnology and pharmaceutical research.

This whitepaper outlines considerations for the use of the cloud to improve manufacturing and supplier management. Topics include how life sciences companies can bring more consistency, control and compliance when collaborating with their contract manufacturers and suppliers.

This whitepaper outlines several industry thought leaders' views on how cloud technology will be applied in healthcare.

Dale C. Wiggins, GM of Philips' HealthSuite Digital Platform, discusses how the cloud helps in healthcare data management.

An interview with Matt Ferrari, CTO of APN Partner ClearDATA, on improving your healthcare security posture via deployment in the AWS Cloud.

Laurent Rotival from Cambia discussions how the AWS Cloud plays a role in Cambia's innovation strategy.

This whitepaper outlines how properly managed, existing data from R&D, manufacturizing or commercialization in combination with new data sources can yield new insights through the creation of data lates. 

The use of the cloud for regulated workloads can transform how companies think about their compliance practices. Cloud-based regulated workloads can improve auditability, transparency, and consistency, as well as offer scalability, transparent costs, and a reduced need for on-premises hardware systems. In this whitepaper, you will learn about GxP in the AWS cloud and the compliance and efficiency benefits of rethinking regulated workloads.

Life science companies are responding with Real World Evidence (RWE) to capture data from clinical through postmarket activities to prove drug products are efficacious, to maintain formulary preference, and to maximize reimbursement. In order to help customers build their own RWE platforms, this document contains reference architectures for data acquisition, data processing and data consumption using AWS Services.

This whitepaper focuses on common strategies and best practices used successfully by AWS customers for analyzing genomics sequencing data and associated medical datasets.

Healthcare reform, increasing patient expectations, exponential data growth, and the threat of cyberattacks are forcing healthcare providers to re-evaluate their data management strategies. Healthcare providers are responding to these demands by leveraging AWS to enforce lifecycle management, employ cost effective, scalable storage and un-trap data for operational and quality insights. In order to help customers, the attached diagrams are reference architectures for managing healthcare data on AWS, including data ingestion and storage management using AWS services.

Change is the only constant in today’s biopharma industry. To succeed, companies must collaborate and outmaneuver the competition against a backdrop of fast-evolving regulations and technologies. Being nimble is essential. To help companies achieve this state, AWS has partnered with SAP. Multi-year upgrade projects are out. Rapid iteration is in. In this whitepaper, learn how life sciences companies are finding faster and simpler ways to move from on-premise hardware and get started with SAP HANA in the AWS cloud.

Healthcare organizations are facing a fast growing data management challenge, with some estimates showing the amount of digital healthcare data growing at close to 50% of year and hitting 2.3 Exabytes by 2020. The Amazon Web Services (AWS) Cloud is at the core of Philips HealthSuite, which currently manages more than 23 petabytes of imaging study data for healthcare providers. In this webinar, you’ll learn about some of Philips’ decisions, considerations and lessons learned when they were building a cloud-based ecosystem that offers solutions and services to manage the growing amount of data.

(This is only a sample of public data sets on AWS. For a complete list of healthcare and life sciences data sets, see AWS Public Data Sets)

The Cancer Genome Atlas (TCGA) is a joint effort of the National Cancer Institute and the National Human Genome Research Institute to accelerate our understanding of the molecular basis of cancer, and consists of raw and processed genomic, transcriptomic, and epigenomic data from thousands of cancer patients.



The International Cancer Genome Consortium (ICGC) coordinates projects with the common aim of accelerating research into the causes and control of cancer. More than 2,400 consistently analyzed genomes, providing one of the world’s largest collections of curated cancer genome data in the cloud.



3000 Rice Genome Project
The 3000 Rice Genome Project is an international effort to sequence the genomes of 3,024 rice varieties from 89 countries. Through analysis of these genomes, researchers can potentially identify genes for important agronomic traits such as better nutrition, climate change tolerance, and disease resistance.

Genome in a Bottle
The Genome in a Bottle Consortium is a public-private-academic consortium hosted by the National Institute of Standards and Technology to develop the technical infrastructure to enable translation of whole human genome sequencing to clinical practice. The Consortium has selected several genomes to produce and characterize as reference materials; the complete data set from the project is freely available on Amazon S3.

1000 Genomes Project
The 1000 Genomes Project, initiated in 2008, is an international public-private consortium that aims to build the most detailed map of human genetic variation available.

We can help you get started with a consultation from our sales and architecture organization, or you can begin your own pilot today.

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