The synthesis of fundamental process models is many times imprac-
ticable due to the high development time and cost, the lack of mea-
surement techniques of key properties, and, more importantly, the
lack of fundamental knowledge about key aspects of the process.
Hybrid modeling has been pointed out as a cost-eﬀective method-
ology for modeling such inherently complex processes. The under-
lying design principle is that all sources of knowledge, be them
mechanistic, heuristic, or statistic, are considered valuable comple-
mentary — not mutually excluding — resources for model develop-
ment. Most of the hybrid modeling studies reported in the literature
showbiological applications involving the cultivation ofmicroorgan-
isms or cells characterized by intricate metabolic phenomena. Mem-
brane processes are also many times characterized by complexity
that can be hardly modeled at a fundamental level. The main goal in
this chapter is to illustrate how the hybrid modeling technique can
be applied with advantage to such complex membrane processes.