Bringing laboratories to the next digital level with modern data strategy

Life sciences organizations are looking for ways to increase the efficiency, right-first-time outcomes of quality control activities, and to accelerate the product release. Capgemini and Amazon Web Services (AWS) have collaborated for visioning a modern data strategy to make the laboratories future ready by leveraging the comprehensive suite of data, analytics, security, artificial intelligence (AI), machine learning (ML), and generative AI services from AWS.  The solution is powered by Capgemini’s Insights & Data tools and accelerators.

The solution focuses on bringing labs to the next level of digital transformation through Instrument connectivity, lab data cataloging, data harmonization and analytics, and custom connectors. This ensures seamless data transfer into any commercial off-the-shelf software applications using AWS microservices.

Key success factors identified across life sciences value chain are cost reduction, compliance, security, data integrity and process optimization. The solution has identified and addressed above elements with use cases such as:

  1. Move to cloud
  2. Digital transformation for process analytics
  3. Generative AI

Capgemini’s premium partnership with AWS is helping organizations to become data-powered enterprises and unlock tangible business value in a rapidly evolving landscape.

“Excited that the Capgemini life sciences team, in partnership with AWS, has developed a solution to enhance instrument and IoT connectivity in pharmaceutical labs. Our comprehensive solution includes key tenets such as instrument connectivity, lab data cataloging, data harmonization, analytics, and custom connectors. This addresses pharma lab challenges related to quality costs and lab productivity while building a modern data strategy.”

Raghunandan Hanumanthu, Vice President and India Industry Platform Leader for Life Sciences, Capgemini

Overview of the solution and challenges faced

The journey from molecule to medicine is pivotal to advancing human health, but it faces critical challenges, including rising costs, low approval rates, and long cycle times.  The current state of instrument connectivity within such laboratories is fragile and non-scalable, relying on point-to-point integration. Pharmaceutical/bio-pharmaceutical laboratories typically house a collection of various instruments.  Point-to-point connectivity is achieved using instrument-specific parsers and specific modules of laboratory information management systems (LIMS). Overall, the current state is suboptimal.

Future state: A modern data estate for the labs

Capgemini’s Data Estate Modernization methodology is designed to help customers across industry verticals by enabling them to “think big” and “scale fast.”

The solution eliminates the deficiencies of complex connectivity when they are multiple instruments and applications. The solution comprises of:

  • Instrument connectivity
  • Automate data conversion into Fast Healthcare Interoperability Resources (FHIR)
  • Lab data cataloging
  • Data harmonization and analytics
  • Custom connectors for data transfer into any commercial off-the-shelf application.

The implementation of the above functional elements is identified through the below use cases.

Traditional systems are typically siloed. Building an operating model that is data-driven is imperative to providing a comprehensive view of relevant data, and to make secure, modern pharmaceutical laboratories have systems that are integrated, democratized and interoperable. The move to cloud use case addresses the nuance of moving away from monolithic to modular. By leveraging AWS’s state-of-the-art cloud architecture that uses purpose-built services, and by scaling at large using Capgemini’s world-class consulting and advisory services in data and analytics, the solution aims at helping our joint pharmaceutical customers move to the AWS cloud seamlessly.

Digital transformation for process analytics by leveraging AWS Data Mesh framework is powered by Capgemini’s Collaborative Data Ecosystem methodology. Most organizations struggle to realize their vision of creating data as a product which enables the elements of governance, storage, and data science. The solution aims to consume AWS services like AWS data mesh and AWS data zone, to help build a data mesh environment for the labs for centralized data sharing and governance.

Capgemini has entered into a multi-year collaboration agreement with AWS to expedite the adoption of generative AI solutions in enterprises. The partnership aims to assist organizations in realizing the business benefits of generative AI, addressing challenges like cost, scale, and trust.
Capgemini’s generative AI Accelerator – Capgemini RAISE – is built on AWS, has multiple use case scenarios to speed up generative AI adoption for our healthcare, life sciences, and pharmaceutical customers. Paired with AWS generative AI components such as Amazon Bedrock, Amazon SageMaker, and Amazon Q, Capgemini RAISE unlocks AWS’s breadth of capabilities to simplify and supercharge generative AI solutions through:

  • Readiness at scale
  • Trusted AI
  • Cost efficiency

“The Laboratory Data Acquisition suite effectively turns the lab into a data-powered organization, providing IoT device connectivity, data cataloging, harmonization and analytics tools, and custom connectors to common lab applications. We and our strategic partner, AWS, are confident that this solution will enable life sciences organizations to bring products to market faster and more safely.”

Jeff Deyerle, Vice President, Insights & Data, Capgemini

“The journey from molecule to medicine is pivotal to advancing human health, but it faces critical challenges, including rising costs, low approval rates, and long cycle times. Laboratories play an integral role in this value chain and directly impact these outcomes, and Capgemini has partnered with Amazon Web Services to develop a laboratory data acquisition layer featuring the AWS Digital Transformational Hub to compliment the next-gen laboratories approach. This provides a unified approach to overcome heterogeneity and interoperability issues in instrument data and ELN/LIMS data sets that limit access to the full potential of laboratory data in driving efficiency, discovery lead time, and in realizing the full potential scientific insights.”

Brian Eden, Vice President, Global Life Sciences Technical Operations, Capgemini