The application of modeling tools to better understand and control bioprocess development and manufacturing has become a hot topic within the last few years. However, what do we actually need to create digital bioprocess twins? Is it just about data and powerful modeling algorithms, or is there more to consider to accurately describe a process, transfer the knowledge and model structure from early-stage development until manufacturing?
Discussion points and provided solutions:
• The overall goal of process modeling
• Experimental design concepts
• Different modeling approaches for different requirements
• Solutions to speed up both up- and downstream development
• Model transfer along with scales
• Model usage for real-time monitoring and control
Learning Objectives:
1. Describe what a digital bioprocess twin is and what can it serve for.
2. Discuss how to setup a digital twin and what are important things to consider.
3. Explain why the model structure is of importance to achieve both fast learning and process control goals.