ABSTRACT
The preceding chapters of this book introduced the concept of hybrid modeling—combining model structures from a priori process knowledge with models whose structure is determined from data—and provided theoretical background and case-study examples of their applicability in a wide range of industries. This chapter provides an overview of the challenges within the (bio)pharma industrial sector resulting from the strict regulatory framework governing the industry and illustrates how hybrid modeling methodology may provide additional benefits in terms of deeper process understanding and greater model fidelity. A case study of monoclonal antibody production using a cell culture cultivation process is used to exemplify some of the challenges and benefits in this rapidly growing biopharma sector.
