Capgemini helps Boehringer Ingelheim in a world of data

Ruth Lütticken, Director of Life Sciences, Data Science & AI, 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, Bruno Rizzuti. “It is a cloud-based ecosystem that we're building for our data needs not just for today but the years to come in the future. This project is designed 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 data and human pharma,” says Ruth Lütticken, Director of Life Sciences, Data Science & AI, Capgemini. “I think since Covid 19, everybody knows how important that step is in developing new tracks. Here the change was for the global feasibility managers at the country level to select a certain trial site for a certain trial phase. So many factors and data will have to be considered, and this gives them a predictive modelling solution which is using internal but also external data to allow them to have data-driven site identification, which means they can reduce the time for the trial.”

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

“Now they have a self-service analytics tool in place which helps them to identify at a very early stage, even any potential decrease in the performance,” says Lütticken. “This also helps them to fill any potential gaps in the regulatory documentation and find missing digital signatures, for example. And these are just two examples of how we can say discovery planning operations are supporting teams with data-driven evidence.”

Read the full Boehringer Ingelheim report HERE.


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