Capgemini helps Boehringer Ingelheim in a world of data

Ruth Lütticken, Director of Life Sciences, Data Science & AI at Capgemini, explains how data management is helping Boehringer Ingelheim to transform lives

Pioneering family-owned Boehringer Ingelheim is making use of cutting-edge data management services provided by Capgemini in its work on breakthrough therapies. 

Boehringer Ingelheim specialises in areas of unmet medical need in Human Pharma, Animal Health, and Biopharmaceutical Contract Manufacturing and has focused on advanced technologies to discover new ways of introducing technology to core business processes. 

As part of its Dataland program, Boehringer Ingelheim invests in data-related initiatives to strengthen its foothold in the digital world. Leveraging data has the potential to transform drug development and the patient experience. Several units within the organisation were already successfully working with data, but Boehringer Ingelheim wanted to scale its usage across the entire company. This ambition required a strong technology foundation and modern infrastructure, as well as clear processes and responsibilities in the area of data governance.

“This is a programme that we're running at Boehringer Ingelheim that has the goal of building an end-to-end ecosystem for data across all business units,” explains Boehringer Ingelheim’s Head of Data Management Services, Bruno Rizzuti. “Mainly, it is a cloud-based ecosystem that we're building for our data needs not just for today but the future in the years to come. The idea is to create a trusted environment not only for our regular use cases but also for those that require more, let's say, flexibility and the capabilities that the technology in the cloud can provide.”

“There are many exciting use cases for human pharma medicine and operations,” says Ruth Lütticken, Director of Life Sciences, Engineering R&D at Capgemini. “I think since Covid 19, everybody knows how important clinical studies are in developing new drugs. Here the challenge was for the Global Feasibility managers to select the country and for local investigators to select the site for a certain trial phase of a particular drug. A predictive modeling solution was developed using internal and external data to allow for a data-driven site identification and in this way reduce trial time via improved country and site identification.”

Ruth Lütticken offers another example of how data management can help human pharma teams working in quality control labs. “Lab personnel are confronted with lots of lab instruments and corresponding lab data, and they have to continuously monitor the behaviour of the analytical methods. This is, of course, to maintain patient safety but also for regulatory compliance.”

“The lab personnel now have a self-service analytic application in place which helps them to better identify any potential decrease in method performance but also to ensure regulatory compliance with all required documentation and digital signatures to be in place once a sample needs to be processed again. And these are just two examples of how we can say drug discovery pharma operations teams are supported by with data-driven evidence.”

Read the full Boehringer Ingelheim report HERE.

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