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ZS Helps Pharma Companies Navigate Change with Analytics on the AWS Cloud

2020

The Changing Healthcare Landscape

The healthcare industry is continually changing in response to need and demand. One example is the growth of telehealth, which is increasing patient access to diagnoses and treatments administered virtually. For pharmaceutical (pharma) companies, this means reimagining the patient experience and how it would impact the delivery and distribution of medicines. It also means modeling possible outcomes from a rapidly changing healthcare landscape and extracting meaningful data to make the right choices.

ZS Associates (ZS) provides comprehensive analytics expertise and services that help major pharma companies stay ahead of these changes. With its integrated analytics platform, REVO, customers are equipped with the necessary, relevant insights to develop more effective business strategies that are based on diverse, complex analytics and designed for multiple users and business scenarios.

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“REVO algorithm as a service, powered by AWS, introduces a shift in intelligent analytics delivery, fostering innovation, integration, and adoption in a rapidly changing healthcare space.”

Abhishek Trigunait
Chief Technology Officer, ZS Associates

Greater Analytical Power from the Cloud

When ZS launched in 1983, it ran its services from an on-premises data center. Over time, as the company grew amid the proliferation of cloud services, it sought the opportunity to improve the scalability and manageability of its services as well as reduce costs. Abhishek Trigunait, chief technology officer at ZS, says, “We saw the benefits of the cloud for our customers: from customized enterprise data lakes and analytically rich offerings to new services across REVO and our other platforms, Javelin and Verso.”

In 2015, ZS looked for a cloud provider to meet its goals. It chose Amazon Web Services (AWS), whose services were the most mature based on ZS’s analysis of the market. Dinesh Navsupe, senior director of architecture and technology at ZS, says, “We noticed that many of our customers were already looking to move to the AWS Cloud, which in turn gave us more confidence.”

Powering REVO with AWS

ZS decided to develop its REVO integrated analytics platform on the AWS Cloud. Along with customized big data, analytics, AI and machine learning (ML), and orchestration tools, it adopted core AWS services such as Amazon Elastic Compute Cloud (Amazon EC2) for launching applications and Amazon Relational Database Service (Amazon RDS) for scaling its database. ZS also used Amazon EMR for big data analytics and Amazon Simple Storage Service (Amazon S3) for data storage.

With AWS, REVO now delivers data management, dashboarding, and advanced analytics using accelerators and embedded packaged analytics. The REVO platform also supports all stages of drug development with powerful modules and applications. Each module is configurable to solve specific use cases by geography. Currently, more than 30 life sciences companies around the globe are benefiting from REVO products.

Crunching Data at up to 30% Lower Cost

As its offerings evolved, ZS added more AWS services to its core infrastructure. This included AWS Lambda, which allows customers to run code without the need to provision and manage servers. The business runs Lambda functions as a computation engine for crunching patients’ data to identify cohorts for therapeutic areas. Navsupe comments, “We avoid the cost of maintaining dedicated Amazon EC2 instances, giving us a cost reduction of up to 30 percent for delivering this service.”

Delivering On-Demand Machine Learning

ZS is also an early adopter of Amazon SageMaker, a fully managed service that provides ZS with access to a complete machine learning ecosystem to build, fine-tune, and deploy—and in turn offer customized ML algorithms to its customers. “The initial idea came out of the ZS Quest Innovation hackathon, where the concept of ‘algorithm as a service’ was introduced,” says Trigunait. “We wanted to preserve our ML expertise and protect our IP. Our aim was the industrialization of algorithms, so they were reusable for multiple clients and easily integrated with upstream-downstream systems.”

AWS provided ZS with access to Amazon SageMaker specialists, who discussed best practices, shared the experiences of other AWS customers, and proposed Python as the programming language. Navsupe says, “With guidance from AWS experts as well as various online resources, we accelerated our algorithm-as-a-service framework development. We’ve also reduced our time-to-market by 15–20 percent, enabling us to monetize the service faster.”

Trigunait adds, “REVO algorithm as a service, powered by AWS, introduces a shift in intelligent analytics delivery, fostering innovation, integration, and adoption in a rapidly changing healthcare space.”

Supporting New Healthcare Challenges

Today, ZS customers can identify trends and make predictions more accurately by taking advantage of the service created using Amazon SageMaker. The algorithms can handle multidimensional and multivariate data without the need for human intervention. Plus, its predictive capabilities are expected to improve over time. Dharmendra Sahay, managing principal at ZS, says, “Our algorithm-as-a-service offerings, powered by Amazon SageMaker, can help pharma companies respond to a rapidly changing business environment with sophisticated analytics.”


ZS Associates

ZS helps companies in multiple industries, including pharmaceuticals, develop and deliver products that drive customer value and company results through analytics, helping create more effective business strategies.


Benefits of AWS

  • Increases compute performance of existing analytics capabilities
  • Enables development of an algorithm-as-a-service offering
  • Provides a fully managed serverless ML ecosystem
  • Accelerates service development by up to 20%
  • Lowers data processing costs by up to 30%

AWS Services Used

Amazon SageMaker

Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models.

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AWS Lambda

AWS Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume.

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Amazon Elastic Compute Cloud

Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.

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Amazon Relational Database Service

Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups.

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