ROBUST OPTIMAL FERMENTATION OPERATING POLICIES

The bioprocess industry is starting to face new commercial pressures l eading to a greater emphasis on improving manufacturing, and deliverin g relatively low-volume; high value-added products at costs acceptable to health-care providers. A major challenge in this industry is the r apid development of new integrated processes for optimal large scale p roduction. Accurate predictive models of biochemical unit and process operations are required if optimal design is to be achieved without ex tensive pilot plant trials (Richardson and Peacock, 1994). In the lite rature there exist many models of unit operations used in bioprocesses . In principle, these should be particularly useful in determining the optimal operation of the process, but a wide range of; uncertainty as sociated with each model presents a,number of problems. The main obsta cle is that using an operating policy which has been optimised for the nominal model parameter values in an uncertain system can lead to dra matic changes in the performance of the process. It is preferable to u se a policy in which these changes are kept to a minimum, while mainta ining a good performance in the nominal ease. Therefore a comprehensiv e design of the process must account explicitly for these uncertaintie s. This paper concentrates on the optimisation of fermenter operating policies. Here, we consider an appropriate definition of ''robustness' ' for biochemical processes, and go on to describe one means of ensuri ng such robustness during the optimisation of the dynamic operation of a fermenter. We use an illustrative example to contrast, using stocha stic simulation, the proposed robust approach with a deterministic des ign based on nominal parameter values. (C) 1998 Elsevier Science Ltd. All rights reserved.