Category: Life Sciences

Celebrating its 10th year, AWS re:Invent 2021 is gearing up to deliver a week of inspiring content, educational workshops and bootcamps, and plenty of peer-to-peer networking opportunities. This year’s conference will take place in Las Vegas from November 29th through December 3rd, and will have an engaging virtual component for those who cannot join us […]

Guest blog authored by Jack Tabaska and Ian Davis from the Bayer Crop Sciences team. At Bayer Crop Science we are applying modern genomic and data science methods to the challenges of global food production. Our research routinely produces enormous volumes of raw data that must be processed quickly and cost-effectively. Automated analysis pipelines (also […]

The cloud has brought agility and cost savings compared to running workloads in a data center, forcing customers to consider how regulatory concerns are shared between themselves and the cloud provider. Customers with existing GxP (an abbreviation for “good practice” guidelines and regulations for various industries like pharmaceutical, agricultural, or manufacturing) solutions are challenged when […]

CliniOps offers a Data Science platform for the Life Science industry, to support digital Clinical trials, leveraging AI, mobile, analytics, cloud, sensors & connected devices. This novel Unified platform approach, with built-in Telemedicine, is custom designed for Patients, Sites and Sponsors, that ensures high data quality at less cost. The platform is also extremely flexible […]

To keep pace with the growing scale of genomics datasets, bioinformatics scientists rely on shared analysis workflows written with portable standards such as the Workflow Description Language (WDL). The race to track SARS-CoV-2 variants notably illustrates rapid deployment of such workflows at scale on many platforms, including AWS. This post presents a new solution for […]

Introduction This blog summarizes the use of image-based computing patterns in life sciences manufacturing to accelerate the cloud journey and realize predictive plant capabilities as foundational steps toward an “Industry 4.0” vision. AWS computer vision services automate discrete process steps using image analytics. We explore core business challenges and opportunities, target use-cases and AWS architecture […]

Today, we are excited to announce preview availability of Amazon Genomics CLI, a tool for genomics and life science customers to process genomics data at petabyte scale on AWS enabling population level genetic studies, faster drug discovery, and more. In this blog, we take a brief look at how to use Amazon Genomics CLI with […]

This blog was co-authored by Fabrice Schlegel, Senior Manager of Data Sciences at Amgen; Joao Alberto de Faria, Senior Associate Software Engineer at Amgen; Ammar Latif, Senior SA at AWS; and Pierre-Yves Aquilanti, Principal HPC Specialist SA at AWS. Amgen relies on computational modeling to gain insight into their biopharma processes. Modeling improves product designs through […]

Healthcare and life science organizations are moving towards digital transformation to decrease the cost of care, improve collaboration, make data-driven clinical and operational decisions, and enable faster development of new therapeutics and treatment paths. Identifying the right cloud technology to reach these goals can be challenging, and many organizations lack the internal resourcing and expertise […]

This post was co-authored by Michael DeRan, Scientific Consultant at Diamond Age Data Science; Chris Friedline, Scientific Consultant at Diamond Age Data Science; Netsanet Gebremedhin, Scientific Consultant at Diamond Age Data Science (Computational Biologist at Parexel at time of publication); Jenna Lang, Specialist Solutions Architect at AWS; and Lee Pang, Principal Bioinformatics Architect at AWS.  […]