Beyond Proof of Concept: Making Model-Based Bioprocessing Stick

Julien De Crom 
UCB 

Abstract

Model-based bioprocessing has made significant technical progress, with predictive models and digital twins demonstrating value for process development. Yet, many initiatives fail to translate into routine use. Instead of guiding decisions, models are often run in parallel to established practices.  

This presentation argues that the main barrier to scaling digital bioprocessing is not model performance or technical readiness, but trust and adoption. When predictive approaches are perceived as opaque or fragile, they remain disconnected from existing workflows.  

Based on industrial experience, this talk presents a practical example of a structured approach to move model-based bioprocessing beyond proof of concept. By focusing on progressive confidence building, the approach enables adoption without disruptive change, allowing predictive models to become trusted partners in real bioprocess decisions.

Julien De Crom

Julien De Crom

Data and Predictive Sciences Lead 

Julien De Crom is a Data Science Associate Director at UCB with a strong background in biopharmaceutical analytics, predictive modeling, and digital transformation. He has led cross-functional teams, driven innovation in CMC development, and supported data science collaborations across the life sciences ecosystem.  

Before joining UCB, he held roles at Deloitte and Accenture, where he worked on planning and forecasting, automated reporting, machine learning initiatives, and technology projects. He holds a Master’s degree in Business Engineering from Louvain School of Management and a postgraduate degree in Big Data and Analytics in Business and Management from KU Leuven.

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