Table Discussions – Your time, your topic!


Friday, June 18, 2021


2:00 pm


Choose the topic that is relevant to you. In this session we offer focused topics to dig in deeper into specific content segments. So this is the perfect opportunity to share your story, your specific question and get first hand advice from your peers and experts.  All attendees can participate in the roundtable of their choice and it’s a camera on event.

Digital and Date Literacy in Pharma. Nice-to-have or Must-have? (Boris Adryan)

Digital and data skills are in demand across all industries. Likewise, there’s a growing gap between those “who know” and those “who don’t”. How much data literacy is needed in the workforce along the pharma value chain? For example, how much conceptual knowledge does a bench scientist need to fully understand and adhere to the FAIR principles? In pharma production, are traditional Six Sigma tools enough, or should practitioners have a notion of machine learning? Does everyone need upskilling?

What can Healthcare learn from the Financial Sector? (Dennis Diederix)

Data science brings enormous potential for our society. As the techniques are fit to solve a multitude of problems, we see the use in different sectors. So how far is each sector with data science an AI? And what can healthcare learn from other sectors, such as the financial sector? What makes the healthcare sector different in use of data science? And which problems are common? As a consulting firm working in both the healthcare, financial and public sector, we understand the differences.

Challenges & Trends in the Health Sector During and After Corona (Martin Szugat)

Corona changed everything, especially the health sector. It has put a lot of pressure on the system, but also fostered new innovations. The pharmaceutical companies and hospitals have shown that they could react quickly and work effectively. But many weaknesses have also been revealed. In this round we discuss what has changed with Corona and especially what a post-Corona world might and should look like.

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