On-line optimization of recombinant product in a fed-batch bioreactor

In this paper, an efficient scheme for on-line optimization of a recombinant product in a fed-batch bioreactor is presented. This scheme is based on the parametrization of the system states and the elimination of a subset of the dynamic equations in the mathematical model of the fed-batch bioreactor. The fed-batch bioreactor considered here involves the production of chloramphenicol acetyltransferase (CAT) in a genetically modified E. coli. The optimal inducer and the glucose feed rates are obtained using the proposed optimization approach. This approach is compared with the traditional optimization approach, where all the states and the manipulated variables are parametrized. The approach presented in this paper results in a 5-fold improvement in the computational time for the recombinant product optimization. The optimization technique is employed in an on-line optimization scheme, when parametric drift and a disturbance in the manipulated variable is present. Feedback from the process is introduced through resetting the initial conditions of the model and through an observer for estimating the time varying parameter. The simulation results indicated improvement in the amount of product formed, when the optimal profile is regenerated during the course of the batch.