The bioprocess industry is starting to face new commercial pressures leading to a greater emphasis on improving manufacturing, and delivering relatively low-volume; high value-added products at costs acceptable to health-care providers. A major challenge in this industry is the rapid development of new integrated processes for optimal large scale production. Accurate predictive models of biochemical unit and process operations are required if optimal design is to be achieved without extensive pilot plant trials (Richardson and Peacock, 1994).In the literature 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 associated with each model presents a,number of problems. The main obstacle is that using an operating policy which has been optimised for the nominal model parameter values in an uncertain system can lead to dramatic changes in the performance of the process. It is preferable to use a policy in which these changes are kept to a minimum, while maintaining a good performance in the nominal ease. Therefore a comprehensive design of the process must account explicitly for these uncertainties. 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 ensuring such robustness during the optimisation of the dynamic operation of a fermenter. We use an illustrative example to contrast, using stochastic simulation, the proposed robust approach with a deterministic design based on nominal parameter values.