Reliable control of the specific growth rate (μ) in fed-batch fermentations depends on the availability of accurate online estimations of the controlled variable. Due to difficulties in measuring biomass, μ is typically estimated using reference models relating measurements of substrate consumption or oxygen uptake rate to biomass growth. However, as culture conditions vary, these models are adapted dynamically, resulting in complex algorithms that lack the necessary robustness for industrial applicability. A simpler approach is presented where biomass is monitored using dielectric spectroscopy. The measurements are subjected to online balances and reconciled in real time against metabolite concentrations and off-gas composition. The reconciled biomass values serve to estimate the growth rate and a simple control scheme is implemented to maintain the desired value of μ. The methodology is developed with the yeast Kluyveromyces marxianus, tested for disturbance rejection and validated with two other strains. It is applicable to other cellular systems with minor modifications.

Understanding the growth characteristics of microorganisms is an essential step in bioprocessing, not only because product formation may be growth-associated but also because they might influence cell physiology and thereby product quality. The specific growth rate, a key variable of many bioprocesses, cannot be measured directly and relies on the estimation through other measurable variables such as biomass, substrate, or product concentrations. Techniques for real-time estimation of the specific growth rate in microbial fed-batch cultures are discussed in the present paper. The advantages and limitations of different models and various monitoring techniques are discussed, highlighting the importance of the specific growth rate in the development of fast, reliable, and robust processes for the production of high-value products such as recombinant proteins.

Biological reaction calorimetry, also known as biocalorimetry, has led to extensive applications in monitoring and control of different bioprocesses. A simple real-time estimator for biomass and growth rate was formulated, based on in-line measured metabolic heat flow values. The performance of the estimator was tested in a unique bench-scale calorimeter (BioRC1), improved to a sensitivity range of 8 mW l(-1) in order to facilitate the monitoring of even weakly exothermic biochemical reactions. A proportional-integral feedback control strategy based on these estimators was designed and implemented to control the growth rate of Candida utilis, Kluyveromyces marxianus and Pichia pastoris by regulating an exponential substrate feed. Maintaining a particular specific growth rate throughout a culture is essential for reproducible product quality in industrial bioprocesses and therefore a key sequence for the step from quality by analysis to quality by design. The potential of biocalorimetry as a reliable biomass monitoring tool and as a key part of a robust control strategy for aerobic fed-batch cultures of Crabtree-negative yeast cells in defined growth medium was investigated. Presenting controller errors of less than 4% in the best cases, the approach paves the way for the development of a generally applicable process analytical technology platform for monitoring and control of microbial fed-batch cultures.

With increasing pressure from regulatory authorities on industry to develop processes embracing process analytical technology (PAT) initiatives, there is a growing demand to establish reliable tools and systems capable of meeting this need. With regard to monitoring and control of bioprocesses, this need translates to a search for robust instrumentation capable of monitoring the critical process parameters in real time. The application of such technologies at all stages of the process, from the initial R&D phase to process optimisation and production, enhances process understanding and paves the way for the development of control platforms. An examination of the PAT concept and selected tools (NIR, MIR, Raman, dielectric spectroscopy and calorimetry) are presented here. A description of each tool is given, with particular emphasis on the nature of the signal produced and how these relate to measurements of biomass, metabolites and product. A description of the signal processing that is necessary to gain meaningful results from the different tools is also given, together with online data reconciliation techniques based on mass and energy balances. Many techniques such as those based on vibrational spectroscopy are of particular interest, since they are capable of monitoring several critical process parameters which are typically controlled in a bioprocess. A window of application for each of the techniques, when used in the area of bioprocessing, is suggested based on their uses and inherent limitations.

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