GenAI in life science

Explore the realistic applications of AI, significant reduced manual workload and lead times while minimizing errors.

Delaware engineered an automated content‑labelling solution for a global pharmaceutical company facing high costs and long lead times in tagging brand‑specific marketing content. The solution architecture combined Azure Databricks, MLflow, Azure OpenAI, and other Azure AI services to process and interpret diverse document types and generate accurate labels.

Date: 17 June 2026
Time: 12h30-13h30 CET
Format: Keynote speaker + interactive Q&A & discussion

A Microsoft Teams invite will be send about 1 day before the event to all registered persons.

The Knowledge Café will include a Q&A session, please enter your question(s) during the registration or via MS Teams Chat during the call.

Event Properties

Event Date	17-Jun-2026 12:30 - 13:30
Capacity	80
Registered	79
Individual Price	Free
Location	Online - Teams

Agendas

12:30	GenAI in life science Delaware engineered an automated content‑labelling solution for a global pharmaceutical company facing high costs and long lead times in tagging brand‑specific marketing content. The solution architecture combined Azure Databricks, MLflow, Azure OpenAI, and other Azure AI services to process and interpret diverse document types and generate accurate labels.

Speakers

Wouter Labeeuw

Data & AI Sr Manager

Wouter Labeeuw is a Senior Manager in Data & AI at delaware, holding a PhD in Engineering Science from KU Leuven, with a strong background in data engineering, machine learning, deep learning, and GenAI and Agentic AI. He focuses on delivering practical, scalable AI solutions in complex environments, including the pharmaceutical sector, with particular attention to reliability, traceability and the industrialisation of AI.

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