Dynamic process conditions in bioprocess development

Abstract

In this review, we summarise recent studies that purposefully employed dynamic conditions, such as shifts, pulses, ramps and oscillations, for fast physiological strain characterisation and bioprocess development. We show the broad applicability of dynamic conditions and the various objectives that can thereby be investigated in a short time. Dynamic processes reveal information about the analysed system faster than traditional strategies, like continuous cultivations, as process parameters can directly be linked to platform and product parameters. Furthermore, we demonstrate that dynamic operations can result in increased productivity and high product quality, making this strategy a valuable tool for bioprocess development. With this review, we would like to encourage bioprocess engineers to an increased use of dynamic conditions in bioprocess development.

Cultivation strategies to enhance productivity of Pichia pastoris: A review

“…The use of dynamic process conditions for fast physiological strain characterisation are summarised by reviews of Spadiut and Herwig, (2014) and Spadiut et al (2013). Various dynamic fedbatch approaches currently under development would allow the entire production range of µ to be covered in a single experiment (Lüthy et al, 2011, Spadiut et al, 2014b, Zalai et al, 2012.…”

A Critical Assessment of Microbiological Biogas to Biomethane Upgrading Systems

“…By using dynamic process conditions (pulse, shift, ramps or oscillations), knowledge of maximum biological capacity [21] or yields can be investigated in a short time. Also the examination of limitations, changing productivities, yields, and metabolic states can be achieved through dynamic experiments [34]. Furthermore by precisely altering process conditions through application of dynamic experiments putative liquid and gaseous limitations can be rapidly detected and physiological parameters, which are important for scale-up and bioprocess development, may be rapidly determined.…”

“…dynamic process conditions or by using Design of Experiments (DoE) examination strategies for rapid screening of relevant process parameters. The implementation and the use of DoE for bioprocess development and the utilisation of dynamic process conditions is advantageous, because it accelerates research, if data exploitation can be properly performed [34]. By using dynamic process conditions (pulse, shift, ramps or oscillations), knowledge of maximum biological capacity [21] or yields can be investigated in a short time.…”

Optimization of Bioethanol In Silico Production Process in a Fed-Batch Bioreactor Using Non-Linear Model Predictive Control and Evolutionary Computation Techniques

“…The in silico optimization experiments represent an important alternative, as multiple operational scenarios can be studied in the pursue for desired product yield maximization and/or the minimization of by-products obtention [39,40]. Several studies emphasize the importance of the dynamic conditions of the operational variables for bioprocess, as its transient characteristics may impact profoundly the desired product yield or its purity [21,22,33,41]. In this sense, the dynamical optimization of bioprocess is cardinal for ensuring its economic competitiveness, encouraging the utilization of advanced control techniques such as the dynamic real-time optimization (DRTO), which is briefly described below.…”

“…The dynamic optimization will employ two evolutionary computation techniques, the genetic algorithm (GA) and the differential evolution (DE), and compare their performances on the manipulation of the feed rate profile in terms of the obtained bioprocess productivity trough the utilization of the DRTO approach, using a free terminal time concept. As the dynamic profile of operational parameters exhibits direct correlation with the bioprocess yield, different feeding profiles are evaluated in terms of ethanol productivity [21,22].…”