AWS for Industries

re:Invent 2020 – Life Sciences Industry Recap

AWS re:Invent 2020, the biggest cloud computing event of the year, kicked off its first wave of free virtual content and announcements from Nov 30 to Dec 18. The Life Sciences Industry Track brought industry leaders together to discuss how they leverage cloud technology to bring differentiated therapeutics to market faster. In this post, we’ll cover highlights of important announcements for Life Science and Genomics customers across the Pharma value chain:

Research & Development
Life Sciences Manufacturing & Supply Chain
Commercial
Core IT
On-demand Life Sciences Sessions

Research & Development:

  • Combine and share data assets more easily with Amazon HealthLake and AWS Glue Elastic Views. Amazon HealthLake is a new HIPAA-eligible service that uses machine learning (ML) models trained to automatically understand and extract meaningful medical data from raw, disparate data. Amazon HealthLake can foster collaboration with your provider and payer partners by enabling data sharing because it formats data using the Fast Healthcare Interoperable Resources (FHIR) standard. Webpage | Video

AWS Glue Elastic Views lets you use SQL-based queries to combine disparate data sources into a single table to support a research mission. AWS Glue Elastic Views lets analysts with SQL skills to combine and replicate data without having to engage a data engineer in the IT division. Webpage | Video

  • Foster researcher collaboration and manage researcher environments with Service Workbench on AWS and AWS CloudFormation Modules. Service Workbench on AWS is a solution that allows researchers to self-provision research environments that you can pre-configure to be compliant with HIPAA/HITRUST, GxP, and GDPR regulations. All analytic tools and data connections can be configured to accelerate research missions without the worry of navigating cloud infrastructure. Teams of collaborating researchers, even from different institutions, can access data assets within the cloud, avoiding the need to download and share data. Webpage | Blog | Video

AWS CloudFormation Modules are pre-configured and reusable building blocks that can be used to provision researcher environments and other R&D platform components that are consistently secure by default. Webpage | Blog | User Guide

  • Machine learning discovery and operations just got easier. Simplify and accelerate data profiling, preparation, and feature engineering for ML using Amazon SageMaker Data Wrangler. It offers over 300 built-in data transformations with no need to write code, making data preparation for ML easier for a wider range of analyst roles. Once features are defined, they can be stored for reuse within the Amazon SageMaker Feature Store, both for new model discovery and for inference. As the use of ML models grows, you can deploy, monitor, and modify ML models in production using Amazon SageMaker Pipelines. These new SageMaker capabilities lower the barriers to ML adoption for any R&D team. Webpage | Blog

Life Sciences Manufacturing & Supply Chain

  • Improve processes, identify bottle necks, and detect anomalies with computer vision. Pharmaceutical and medical device lead times and inventory turns are among the most challenging in any industry. Process deficiencies, bottlenecks, and manual processes are among the leading inhibitors to unlocking major improvements. New AWS services simplify the adoption of computer vision capabilities. Amazon Lookout for Vision enables Life Sciences customers to accurately find visual defects at scale. It uses computer vision to identify missing components, irregularities in production lines, and miniscule defects in physical products. You can automate real-time visual inspection for processes like quality control and defect assessment by providing as few as 30 images for the process you want to visually inspect. Webpage | AWS for Industrials

AWS Panorama is an ML appliance and SDK for building, deploying, and managing computer vision applications (Panorama applications) that can be deployed to edge devices (Panorama devices). With AWS Panorama, you can add computer vision to existing on-premises cameras or to new Panorama-enabled cameras. Live video feeds can also be used to automate monitoring or visual inspection tasks, like evaluating manufacturing quality, finding bottlenecks in industrial processes, and assessing worker safety within manufacturing, warehouse, and logistics facilities. Webpage | Blog

  • Simplify predictive maintenance and process analytics with machine data. One of the most common measures of productivity in manufacturing is overall equipment effectiveness (OEE). Best-in-class OEE ranges upwards of 95%, while Life Sciences OEE remains between 40-60%. Using machine data in new ways can improve unplanned downtime by 10-30%, which directly impacts OEE and operational effectiveness. Amazon Lookout for Equipment is an industrial equipment anomaly detection service that uses your machine data to detect abnormal equipment behavior automatically, so you can avoid unplanned downtime and optimize performance. Amazon Lookout for Equipment enables advanced ML analytics for operators and makes it easier to scale anomaly detection to hundreds or thousands of pieces of Life Sciences equipment. Webpage | Blog

Amazon Monitron is an end-to-end system that uses ML to detect abnormal behavior in industrial machinery, enabling you to implement predictive maintenance and reduce unplanned downtime. Amazon Monitron includes sensors to capture vibration and temperature data, gateways to automatically transfer data to the AWS Cloud, ML-based software that analyzes the data for abnormal machine patterns, and a companion mobile app for simple system setup and immediate notifications of abnormal machine behavior. Webpage | Blog

  • Enhance labs and factories with new edge computing and IoT services. AWS Outposts is a fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to virtually any datacenter, co-location space, or on-premises facility for a truly consistent hybrid experience. New AWS Outposts 1U and 2U form factors are rack-mountable servers that provide local compute and networking services to edge locations that have limited space or smaller capacity requirements. Outposts servers are ideal for customers with low-latency or local data processing needs for on-premises locations, like laboratories or factory floors. Webpage

AWS IoT SiteWise Edge is a new feature of AWS IoT SiteWise providing software that runs on-premises at industrial sites and makes it easy to collect, process, and monitor equipment data locally before sending the data to AWS Cloud destinations. SiteWise Edge is installed on local hardware such as third-party industrial gateways and computers, or on AWS Outposts and AWS Snow Family compute devices. Now, Life Sciences customers can perform local data collection and process for local monitoring and visualization of assets. Since AWS SiteWise Edge runs on premises, local applications that use data from AWS SiteWise Edge will continue to work even when cloud connectivity is disrupted or latency sensitivity is high. Webpage | Blog

Commercial

  • Gather business intelligence insights faster with Amazon Quicksight Q. Marketing and Sales organizations often struggle to gather insights from disparate data sources (e.g., internal sales data, 3rd party Rx data, market research data). Amazon QuickSight Q uses ML-powered, natural language query (NLQ) technology to let business users ask ad-hoc questions of their data in natural language and get answers in seconds. Amazon QuickSight Q is optimized to understand complex business language and data models from multiple domains, so users can simply type their question into the Amazon QuickSight Q search bar (e.g., “Show me the new prescriptions for product x over the last 3 months”). Instead of spending time searching through complex BI tools, business users can focus their time on taking the right actions to improve their business based on insights. Webpage | Blog
  • Build intelligent contact centers with new Amazon Connect services. The COVID-19 pandemic has drastically impacted every business, and call centers have become more important than ever before as consumers seek more help in these unfamiliar circumstances. With rising call volumes and employees transitioning to work from home, traditional call centers on aging legacy platforms can be updated with Amazon Connect, an easy-to-use omnichannel cloud contact center that helps you provide superior customer service at a lower cost. Webpage
    • Real-time contact center analytics with Contact Lens for Amazon Connect. Automatically identify issues during in‐progress calls based on sentiment or keywords, such as adverse events or side effect. When a call needs to be transferred, the call center agent can pass the real-time transcript along with conversation details to the medical subject matter expert, so customers don’t have to repeat themselves or wait on hold while the subject matter experts gets up to speed with the case. Contact Lens could be used to analyze post-call metrics, sentiment, and trends to understand customers better and provide superior, proactive service. Webpage | Blog
    • Enhance personalized service with Amazon Connect Customer Profiles. This feature equips agents with a more unified view of a customer’s profile for more personalized service during a call. It aggregates customer information like contact history, address, phone number, and recent engagements from multiple repositories, such as medical information requests or product sample orders. Webpage | Blog
    • Improve productivity with Amazon Connect Tasks. With traditional contact center solutions, agents track their tasks and customer follow-up items manually. This is time consuming and prone to errors, especially when tasks span multiple systems, as they often do in comprehensive patient support programs. Amazon Connect Tasks makes it easy to prioritize, assign, and track all contact center agent tasks to completion, improving agent productivity and ensuring customer issues are quickly resolved. Follow-ups can also be automated through connectors to external applications such as Salesforce, Amazon Lex chatbots, and Amazon Pinpoint. Webpage
    • Quickly authenticate callers with Amazon Connect Voice ID. This feature authenticates callers with real-time ML-powered voice analysis. When a customer opts-in to streamline their authentication, Connect Voice ID creates a digital voiceprint by analyzing the caller’s speech attributes like rhythm, pitch, and tone, as well as the device and network metadata. When the customer calls back, Connect Voice ID matches the caller voiceprint against the claimed identity and sends an ‘authentication’ or ‘not authenticated’ notification. Examples of interesting applications for this service in Life Sciences include authentication of clinical trial participants or patients participating in a patient support program. Webpage

Core IT

  • Reduce friction when integrating with a hybrid cloud environment with Amazon EKS, ECS Anywhere, and AWS Lambda container image support. Amazon EKS and Amazon ECS Anywhere brings a consistent AWS management experience to customers’ data centers. Amazon EKS and Amazon ECS Anywhere saves you the complexity of buying or building your own management tooling to create clusters, configure the operating environment, update software, and handle backup and recovery. Amazon EKS and Amazon ECS Anywhere enables automated cluster management and reduced support costs, and eliminates the redundant effort of using multiple open source or 3rd party tools for operating Kubernetes clusters. Additionally, AWS Lambda now supports packaging and deploying functions as container images, so you can easily build Lambda-based applications by using familiar container image tooling, workflows, and dependencies. Webpage | Blog
  • Optimize cost by upgrading to the latest instance and storage types. The new general purpose (M6g), general purpose burstable (T4g), compute optimized (C6g), and memory optimized (R6g) Amazon EC2 instances deliver up to 40% improved price performance over comparable x86-based instances for a broad spectrum of workloads. The new storage-focused D3 and D3en instances offer 100% higher disk throughput, 7x more storage capacity (up to 336 TB), and 80% lower cost per-TB of storage compared to D2 instances. Lastly, gp3, the next-generation general purpose SSD volumes for Amazon Elastic Block Store (Amazon EBS) lets you provision performance independent of storage capacity, and offers up to 20% lower price-point per GB than existing gp2 volumes. With gp3 volumes, you can scale IOPS (input/output operations per second) and throughput without needing to provision additional block storage capacity, and pay only for the resources needed. Webpage

On-demand Life Sciences Sessions:

Life Sciences Industry Executive Outlook – Learn how AWS technology is helping organizations improve their data liquidity, achieve operational excellence, and enhance customer engagement. Speaker: Shez Partovi, Director Healthcare & Life Sciences, AWS

Improving data liquidity in Roche’s personalized healthcare platform – Learn how Roche’s personalized healthcare platform is accelerating drug discovery and transforming the patient journey with digital technology. Speaker: Mustaqhusain Kazi, Head of Personalized Healthcare – Pharma Informatics, Roche

AstraZeneca genomics on AWS: from petabytes to new medicines – Learn how AstraZeneca built an industry-leading genomics pipeline on AWS to analyze 2 million genomes in support of precision medicine. Speaker: Slave Petrovski, VP and Head of Genome Analytics, AstraZeneca

Building patient-centric virtualized trials – Learn how Evidation Health architects on AWS to create patient-centric experiences in decentralized and virtual clinical trials. Speaker: Alessio Signorini, Chief Technology Officer, Evidation Health

Streamlining manufacturing and supply chain at Novartis – Learn how Novartis is creating real-time analytics and transparency in the pharma manufacturing process and supply chain to bring innovative medicines to market. Speaker: Amit Nastik, VP Strategy & Operations and Local Markets Manufacturing, Novartis

Accelerating regulatory assessments in life sciences manufacturing – Learn how Merck leveraged Amazon Machine Learning to build an evaluation and recommendation engine for streamlining pharma manufacturing change requests. Speakers: John Baker, Executive Director – ML & Analytics, Merck; Kyle Hayes, Director Regulatory Affairs – CMC, Merck

Kelli Jonakin, Ph.D.

Kelli Jonakin, Ph.D.

Kelli Jonakin is the Principal Marketing Manager for the Life Sciences and Genomics Industry verticals at AWS. She comes with a background in pharmaceutical research, with a special focus on development and commercialization of biologics. Kelli received her Ph.D. in Pharmacology and Systems Biology from the University of Colorado, and received an NIH post-doctoral fellowship grant to study Biochemistry at the University of Wisconsin-Madison.