Life Sciences Resources
Life Science Competency Partner Program
AWS offers Competency programs for customers to find AWS partners who have demonstrated technical proficiency and proven customer success in Life Sciences & Genomics. Consulting and technology partners can help customers conduct drug discovery, research and develop novel genetic-based treatments, manage clinical trials, and engage in biopharma manufacturing and distribution activities.
New! Life Sciences Resource Center
Explore the resource center to access the newest content, customer stories, and events in Life Sciences.
Life Science Whitepapers
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 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.
In this whitepaper, learn how life science manufacturing companies have built modern GxP compliant data platforms in the cloud, which allow them to achieve better trackability and traceability as well as glean insights from enhanced data analytics.
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 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 lakes.
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.
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.
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.
This whitepaper focuses on common strategies and best practices used successfully by AWS customers for analyzing genomics sequencing data and associated medical datasets.
In this eBook, learn the advantages of AWS for next-gen business intelligence in healthcare and life sciences. This includes services that allow customers to build solutions that align with all major global compliance frameworks.
An interview with Matt Ferrari, CTO of APN Partner ClearDATA, on improving your healthcare security posture via deployment in the AWS Cloud.
This paper briefly outlines how companies can use Amazon Web Services to power HIPAA-compliant information processing systems.
Select Life Science Videos & Webinars
Select Public Data Sets
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