In the slowly evolving landscape of bioprocess development and manufacturing, digital bioprocess-twins have emerged as potential accelerators. While advanced algorithms are at the heart of this endeavor, they are just one piece of the puzzle. The lecture delves into key discussion points that are integral to this paradigm shift. The foundation of accelerated process development and automated process control starts with a clever experimental design, in-time data accessibility combined with powerful modeling algorithms. The lecture will highlight the advantages of using AI and hybrid modeling, while emphasizing the other critical aspects on his journey. Several industrial relevant upstream showcases for microbial and mammalian celllines will be highlighted. Thereby, concepts to save experimental effort by up to 70% will be elaborated, and the modeling structure created in the late-stage development will be reused for real-time monitoring and control in the later stages. Also, one downstream optimization showcase for UF/DF/SPTFF will be highlighted. The talk will wrap up by presenting a future vision and emphasizing the necessity for these modeling approaches to become an integral component of student curricula.

Learning Objectives

1. Explain the pitfalls and solution paths for implementation of AI and digital twins.

2. Describe how to apply the circle of process modeling.

3. Define examples of Upstream and Downstream Optimization possibilities.