AWS for Industries
Tag: life sciences
AWS Clean Rooms is now available for the Healthcare and Life Sciences industry
As healthcare and life sciences customers work to advance clinical research, and realize personalized healthcare and precision medicine for patients, they face varying compliance, regulatory, and security requirements as well as disparate data that is siloed across multiple applications and organizations. These customers increasingly need to unlock access to quality data and leverage privacy-enhanced multi-party […]
2023: a turning point for ML in life sciences
To our many customers and partners who work in Life Sciences, welcome to 2023, a year that I expect to be the turning point in how data science and machine learning (ML) accelerate development of new life-saving therapies. (I’ll share 2023 thoughts on Healthcare in an upcoming post.) The first reason I’m so optimistic is […]
Unlock Data for Clinical Trial Analytics with MuleSoft and AWS
Blog guest contributing authored by Ryan Stastny, Product Manager at MuleSoft Clinical trials are highly complex, lengthy, and expensive. They require effective collaboration among many key stakeholders including subjects, sites, sponsors, contract research organizations (CROs), and government agencies. However, the data needed to drive successful outcomes is often siloed and inaccessible where and when it […]
Executive Conversations: Catalyzing the next generation of cancer care with Prabhu Arumugam and Emma McCargow of Genomics England
What does the future of cancer treatment look like for patients, doctors, and researchers, and what is cloud computing’s role in its success? Rowland Illing, Director and CMO, Government Health at Amazon Web Services (AWS), sat down with Prabhu Arumugam, Genomics England’s Director of Clinical Data and Imaging, and Emma McCargow, Program Lead for Cancer […]
Get ready for re:MARS: The Healthcare and Life Sciences guide to re:MARS 2022
re:MARS is back! This year, re:MARS is happening in person from Las Vegas, NV from June 21-24, delivering cutting edge talks, demos, workshops, and networking opportunities, as well as a rich on-demand option for virtual attendees. The event is offering 100+ sessions spanning Machine Learning, Automation, Robotics, and Space tracks, with six of them focused […]
Reducing device downtime using actionable intelligence on AWS
Blog guest authored by Michael Petrillo of Becton, Dickinson, and Company (BD) Overview of Solution There’s never a good time to take an in-service device offline, especially when healthcare practitioners depend on the device to deliver care to patients. Yet, to keep customer devices operating at optimized throughput, performing maintenance is essential and often requires […]
Whitepaper: Navigating Regulatory and Compliance Requirements for HCLS on AWS
For customers, and partners, it can be a struggle to understand the complexities of regulatory and compliance requirements. To understand what Amazon Web Services (AWS) is doing to support these requirements in the cloud, there is a new whitepaper that can be a great starting point for your cloud compliance journey. Navigating Regulatory and Compliance […]
Improving Patient Engagement in clinical trials using voice and chat with AWS
Life sciences companies are rethinking patient engagement and legacy workflow processes in clinical trials due to low enrollment numbers and concerns around data quality. Voice and Chatbot solutions like Alexa and Amazon Lex, a fully managed conversational artificial intelligence (AI) service, can improve patient experience and increase patient engagement. An estimated 48% of clinical trials […]
Using Structural Variant Analysis on AWS with Amazon FSx for Lustre in Novel Therapeutic Discovery
This post is coauthored by Adam Tebbe (VP of Computational Data Science and Technology), Eva Fast (Senior Computational Biologist), Sarthak Vilas Patel (Senior Data Engineer) from Goldfinch Bio, Inc. and Henrique Silva (Machine Learning Lead) from AWS Advanced Consulting Partner Loka. Goldfinch Bio is an early-stage biotechnology company, who is working towards developing novel, genetically-validated […]
Hummingbird – a tool for effective prediction of performance and costs of genomics workloads on AWS
Blog guest authored by Utsab Ray, Amir Alavi, Amit Dixit, Vandhana Krishnan, and Amir Bahmani from Stanford University. Genomics researchers often face challenges in accurately estimating the compute and memory resources required for their workloads as they work to migrate their data processing to the cloud. AWS cloud computing infrastructure offers scalable and cost-effective solutions […]