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.