Monitoring product and contaminants is critically important at all stages of bioprocess operation, development and control. The availability of rapid measurements on product and key contaminants will yield a higher resolution of data points and will allow for more intelligent operation of a process and thereby enhance the definition and characterisation of a bioprocess. The need to control a bioseparation process is due to the variable nature of upstream conditions, process additives and sub-optimal performance of processing equipment which may lead to different requirements for the operating conditions either within batches or on batch to batch basis. Potential operations for downstream processing of intracellular proteins are the selective flocculation, packed bed and expanded bed chromatographic operations. These processes involve the removal of a large number of contaminants in a single dynamic step and hence are difficult unit operations to characterise and operate in an efficient and reproducible manner. In order to achieve rapid charactensation and control of these processes some form of rapid monitoring was required. A sampling and monitoring system for analysis of an enzyme produced intracellularly in S.cerevisiae, alcohol dehydrogenase (ADH), cell debris, protein and RNA contaminants has been constructed, with a measurement cycle time of 135 s. Both an extended Kalman filter and the Levenberg-Marquardt nonlinear least squares model parameter identification technique have been implemented for rapid process characterisation. Estimation of model parameters from at-line data enabled process performance predictions to be represented in an optimum graphical manner and the subsequent determination of ideal operating conditions in a feedback model based control configuration. The application of such a control strategy for the batch flocculation process yielded on average 92% accuracy in achieving optimum operating conditions. A structured and intelligent use of the at-line data would improve process characterisation in terms of speed and stability. It was demonstrated that rapid monitoring of the packed and expanded bed chromatographic operations yielded improved characterisation in terms of higher resolution data points, enabled real time process analysis and control of the load cycle. For the control of the expanded bed operation a predictive technique was applied to compensate for the large dead volume associated with this unit operation. The feedback control resulted in approximately 80% accurate breakthrough setpoint regulation
