Process performance models in the optimization of multiproduct protein production plants

In this work we propose a model that simultaneously optimizes the process v ariables and the structure of a multiproduct batch plant for the production of recombinant proteins. The complete model includes process performance m odels for the unit stages and a posynomial representation for the multiprod uct batch plant. Although the constant time and size factor models are the most commonly used to model multiproduct batch processes, process performan ce models describe these time and size factors as functions of the process variables selected for optimization. These process performance models are e xpressed as algebraic equations obtained from the analytical integration of simplified mass balances and kinetic expressions that describe each unit o peration. They are kept as simple as possible while retaining the influence of the process variables selected to optimize the plant. The resulting mix ed-integer nonlinear program simultaneously calculates the plant structure (parallel units in or out of phase, and allocation of intermediate storage tanks), the batch plant decision variables (equipment sizes, batch sizes, a nd operating times of semicontinuous items), and the process decision varia bles (e.g., final concentration at selected stages, volumetric ratio of pha ses in the liquid-liquid extraction). A noteworthy feature of the proposed approach is that the mathematical model for the plant is the same as that u sed in the constant factor model. The process performance models are handle d as extra constraints. A plant consisting of eight stages operating in the single product campaign mode (one fermentation, two micro-filtrations, two ultrafiltrations, one homogenization, one liquid-liquid extraction, and on e chromatography) for producing four different recombinant proteins by the genetically engineered yeast Saccharomyces cerevisiae was modeled and optim ized. Using this example, it is shown that the presence of additional degre es of freedom introduced by the process performance models, with respect to a fixed size and time factor model, represents an important development in improving plant design. (C) 2001 John Wiley & Sons, Inc. Biotechnol Bioeng 74: 451-465, 2001.