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Solution

Transforming life sciences laboratories with a modern integrated data strategy

Leverage the power of seamless data and instrument connectivity

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

Next-gen laboratories solutions

To accelerate drug discovery, increase approval rates and reduce cycle times

Read more

Research and insights

Capgemini Research Institute

Lab of the future

capgemini-research-institute

Meet our experts

Amit Kakatkar

Director | SME & Lead – Lab of the Future, Life Sciences Industry Platform
Amit has been part of the Life Sciences industry for over 22 years. Amit completed a BSc, MSc, DIRI from the University Department of Chemical Technologies (UDCT), and an MBA from Newcastle University. Amit began their career as a Junior Scientific Officer at IRMRA, a joint affiliation between the Ministry of Defense and the Ministry of Commerce. Amit conducted extensive research on reverse engineering aspects of polymer compounding, involving separation techniques like HPLC and FTIR. In June 2007, Amit published their first paper in Rubber India on FTIR and its implications.

Debjani Chatterjee

Partner Development and Acceleration Leader
Debjani has over 17 years of cross-functional experience across a wide spectrum of management consulting domains that includes innovation management, partner and alliance management, business, technology (data, AI, and generative AI), program management, and business enablement areas that requires extensive global outreach. Developing new business models, crafting innovative offerings, and working in close collaboration with technology ecosystem partners are some of her areas of interest. At Capgemini she is currently managing the global data, AI, and generative AI partnership with AWS and Informatica, and has been a part of Capgemini’s global insights and data business line for over four years.

Matthew Thompson

Managing Consultant
Matthew Thompson has been working in various roles and industries in the life science sector for the past 20 years.  His consistent focus has always been on the laboratory, whether as a technician, research scientist or now as strategist focusing on transforming the laboratory for next generation of discoveries.  Matthew received a Ph.D in biochemistry and continued his work in the field of immune-oncology and worked as an analytical R&D scientist.  Since joining the consulting industry 7 years ago Matthew has focused on digital lab transformation efforts such as LIMS/ELN implementations, ERP integrations, global process harmonization, and digital strategy development.  Outside of the lab Matthew spends his time with his wife and 2 children outside of Chicago, Illinois.

Suraj Badrayan

Lead, Partnerships and Alliances, Life Sciences Industry Platform
Suraj has over six years of experience in program management, operations, client delivery, compliances, contract management, and intellectual property. Previously, he was also an intellectual property and contracts specialist at TVS Motors R&D Centre, and has driven technology ideation strategies across the R&D value chain. An innovation and technology enthusiast, Suraj brings technological skills blended with legal and intellectual property expertise in life sciences. He is currently Lead, Partnerships and Alliances within the Life Sciences industry platform.

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