AWS for Industries

Tag: life sciences

How natural language processing can uncover value from unreachable data in the modern medical ecosystem

The Dark Data Problem Up to 80% of your organization’s medical patient data is untapped, undervalued, or unused Imagine walking into a physician’s office for a checkup. As you describe some pain you’ve been having in your left knee, the doctor barely looks up from the screen as she clatters away on the keyboard, taking […]

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AWS re:Invent 2019 – Healthcare and life sciences industry recap

With over 75 launches and announcements of new services and major features during re:Invent, it can be hard for any technologist to keep track of the most relevant information for Healthcare and Life Science (HCLS) workloads. Explore the below recap of information important for HCLS customers and links to the top re:Invent breakout sessions. Top […]

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Building a scalable image processing pipeline for image-based transcriptomics

The below post was written by guest author Shannon Axelrod, Senior Software Engineer at the Chan Zuckerberg Initiative. At the Chan Zuckerberg Initiative (CZI), the science team’s goal is to support the science and technology that will make it possible to cure, prevent, or manage all diseases by the end of this century. In particular, the organization […]

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Enforcing immutability, traceability and transparency in clinical trials using Amazon Managed Blockchain

Amazon Managed Blockchain is a fully managed service that makes it easy to create and manage scalable blockchain networks using popular open source frameworks, such as Hyperledger Fabric and Ethereum. General availability of Hyperledger Fabric was announced in April 2019, with support for Ethereum coming soon. For additional details about Managed Blockchain, see What Is Amazon […]

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AWS and Novartis: Re-inventing pharma manufacturing

Today, AWS announced a new strategic collaboration with Novartis that will transform Novartis’ core supply chain, manufacturing, and delivery operations through the use of AWS services. For several years, many AWS partners and life science customers have been using AWS services to modernize various aspects of manufacturing and supply chain. This strategic collaboration with Novartis […]

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Webinar: Digital Medicine 101

Technology is changing how we practice medicine. Sensors and wearables are getting smaller and cheaper, and algorithms are becoming powerful enough to predict medical outcomes. Yet despite rapid advances, healthcare lags behind other industries in truly putting these technologies to use. A major barrier to entry is the cross-disciplinary approach required to create such tools, […]

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Automating GxP compliance in the cloud: Best practices and architecture guidelines

The Life Sciences industry (encompassing, but not exclusively bio-pharma, genomics, medical diagnostics, and medical devices) is governed by a set of regulatory guidelines called Good Laboratory Practice, Good Clinical Practice, and Good Manufacturing Practice (commonly referred to as “GxP”). GxP is intended to protect patient health by ensuring the safety, efficacy, and quality of medicinal […]

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Genomics Webinar: Improving the diagnosis of infectious diseases with microbial genomic analysis

The discovery of microbial cell-free DNA has propelled the introduction of new technologies that can be leveraged for next-generation diagnostic assays. Previously inaccessible genomic information can now be comprehensively surveyed for microorganisms, all from a single blood draw. This webinar will outline how infectious disease testing firm Karius analyzes microbial cell-free DNA data through novel […]

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Building a GPU-enabled CryoEM workflow on AWS

Cryo-electron microscopy (CryoEM) of non-crystalline single particles is a biophysical technique that can be used to determine the structure of biological macromolecules and assemblies. The technique is rapidly becoming the go-to technique in the life-sciences drug discovery process for understanding protein structure. Processing data/images coming from a CryoEM microscope demands a scalable storage for large datasets (median […]

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