Karen A. McDonald

Nolinear model predictive control using Hammerstein models

Abstract Nonlinear models that are composed of a linear dynamic element in series with a nonlinear static element prove to be very attractive in describing the behaviour of many chemical processes. In this paper, a model predictive control scheme is proposed using the Hammerstein model structure. Two simulation examples, a pH neutralization process and a binary distillation column, are used to demonstrate the effectiveness of the method.

Bioreactor systems for in vitro production of foreign proteins using plant cell cultures.

Plant cells have been demonstrated to be an attractive heterologous expression host (using whole plants and in vitro plant cell cultures) for foreign protein production in the past 20years. In recent years in vitro liquid cultures of plant cells in a fully contained bioreactor have become promising alternatives to traditional microbial fermentation and mammalian cell cultures as a foreign protein expression platform, due to the unique features of plant cells as a production host including product safety, cost-effective biomanufacturing, and the capacity for complex protein post-translational modifications. Heterologous proteins such as therapeutics, antibodies, vaccines and enzymes for pharmaceutical and industrial applications have been successfully expressed in plant cell culture-based bioreactor systems including suspended dedifferentiated plant cells, moss, and hairy roots, etc. In this article, the current status and emerging trends of plant cell culture for in vitro production of foreign proteins will be discussed with emphasis on the technological progress that has been made in plant cell culture bioreactor systems.

Production of Human α-1-Antitrypsin from Transgenic Rice Cell Culture in a Membrane Bioreactor

Transgenic plant cell cultures offer a number of advantages over alternative host expression systems, but so far relatively low product concentrations have been achieved. In this study, transgenic rice cells are used in a two‐compartment membrane bioreactor (CELLine 350, Integra Biosciences) for the production of recombinant α‐1‐antitrypsin (rAAT). Expression of rAAT is controlled by the rice α‐amylase (RAmy3D) promoter, which is induced in the absence of sugar. The extracellular product is retained in the bioreactorapos;s relatively small cell compartment, thereby increasing product concentration. Due to the packed nature of the cell aggregates in the cell compartment, a clarified product solution can be withdrawn from the bioreactor. Active rAAT reached levels of 100–247 mg/L (4–10% of the total extracellular protein) in the cell compartment at 5–6 days postinduction, and multiple inductions of the RAmy3D promoter were demonstrated.

Manufacturing Economics of Plant-Made Biologics: Case Studies in Therapeutic and Industrial Enzymes

Production of recombinant biologics in plants has received considerable attention as an alternative platform to traditional microbial and animal cell culture. Industrially relevant features of plant systems include proper eukaryotic protein processing, inherent safety due to lack of adventitious agents, more facile scalability, faster production (transient systems), and potentially lower costs. Lower manufacturing cost has been widely claimed as an intuitive feature of the platform by the plant-made biologics community, even though cost information resides within a few private companies and studies accurately documenting such an advantage have been lacking. We present two technoeconomic case studies representing plant-made enzymes for diverse applications: human butyrylcholinesterase produced indoors for use as a medical countermeasure and cellulases produced in the field for the conversion of cellulosic biomass into ethanol as a fuel extender. Production economics were modeled based on results reported with the latest-generation expression technologies on Nicotiana host plants. We evaluated process unit operations and calculated bulk active and per-dose or per-unit costs using SuperPro Designer modeling software. Our analyses indicate that substantial cost advantages over alternative platforms can be achieved with plant systems, but these advantages are molecule/product-specific and depend on the relative cost-efficiencies of alternative sources of the same product.

Bioreactor strategies for improving production yield and functionality of a recombinant human protein in transgenic tobacco cell cultures.

Plant cell culture production of recombinant products offers a number of advantages over traditional eukaryotic expression systems, particularly if the product can be targeted to and purified from the cell culture broth. However, one of the main obstacles is product degradation by proteases that are produced during cell culture, and/or the loss of biological activity of secreted (extracellular) products as a result of alteration in the protein conformation. Because proteolysis activity and target protein stability can be significantly influenced by culture conditions, it is important to evaluate bioprocess conditions that minimize these effects. In this study, a bioreactor strategy using a protocol involving pH adjustment and medium exchange during plant cell culture is proposed for improving the production of functional recombinant α1‐antitrypsin (rAAT), a human blood protein, produced using several alternative expression systems, including a Cauliflower mosaic virus (CaMV) 35S constitutive promoter expression system, a chemically inducible, estrogen receptor‐based promoter (XVE) expression system, and a novel Cucumber mosaic virus (CMV) inducible viral amplicon (CMViva) expression system developed by our group. We have demonstrated that higher medium pH help reduce protease activity derived from cell cultures and improve the inherent stability of human AAT protein as well. This strategy resulted in a fourfold increase in the productivity of extracellular functional rAAT (100 µg/L) and a twofold increase in the ratio of functional rAAT to total rAAT (48%) in transgenic N. benthamiana cell cultures using a chemically inducible viral amplicon expression system. Biotechnol. Bioeng. 2009;102: 508–520.

Bioreactor studies of growth and nutrient utilization in alfalfa suspension cultures.

Alfalfa (Medicago sativa L.) cells were grown in 500 ml, aerated and stirred batch bioreactors using Schenk and Hildebrant medium. For cultures in which the pH was allowed to vary, we observed two fairly distinct growth phases. Evidence is presented which indicates that the two-phase growth is most likely a result of the two nitrogen sources in the medium. The ammonium present in the medium is directly utilized during the first growth phase and ammonium resulting from intracellular nitrate reduction is utilized during the second phase. During the first growth phase, sucrose is completely hydrolyzed to glucose and fructose with some glucose and fructose consumption. In the second growth phase glucose is consumed preferentially over fructose. Attempts at maintaining the pH at 5.5 using 1N NaOH as the base titrant resulted in very little cell growth compared with cultures for which the pH was allowed to vary.

Bioreactor Production of Human α1‐Antitrypsin Using Metabolically Regulated Plant Cell Cultures

Transgenic rice cell cultures, capable of producing recombinant human α1‐antitrypsin (rAAT), were scaled up from shake flasks to a 5‐L bioreactor. The maximum specific growth rates (μmax) observed from two bioreactor runs were 0.40 day−1 (doubling time of 1.7 days) and 0.47 day−1 (doubling time of 1.5 days), and the maximum specific oxygen uptake rates were 0.78 and 0.84 mmol O2/(g dw h). Using a metabolically regulated rice α‐amylase (RAmy3D) promoter, signal peptide, and terminator, sugar deprivation turned on rAAT expression, and rAAT was secreted into the culture medium. After 1 day of culture in sugar‐free medium, there was still continued biomass growth, oxygen consumption, and viability. Extracellular concentrations of 51 and 40 mg active rAAT/L were reached 1.7 and 2.5 days, respectively, after induction in a sugar‐free medium. Volumetric productivities for two batch cultures were 7.3 and 4.6 mg rAAT/(L day), and specific productivities were 3.2 and 1.6 mg rAAT/(g dw day). Several different molecular weight bands of immunoreactive rAAT were observed on immunoblots.

Classification of abnormal plant operation using multiple process variable trends

Abstract This paper illustrates two strategies for the detection and classification of abnormal process operating conditions in which multiple process variable trends are available. The first strategy uses a hidden Markov model (HMM) for overall process classification while the second method uses a back-propagation neural network (BPNN) to determine the overall process classification. The methods are compared in terms of their ability to detect and correctly diagnose a variety of abnormal operating conditions for a non-isothermal CSTR simulation. For the case study problem, the BPNN method resulted in better classification accuracy with a moderate increase in training time compared with the HMM approach.

Classification of process trends based on fuzzified symbolic representation and hidden Markov models

Abstract This paper presents a strategy to represent and classify process data for detection of abnormal operating conditions. In representing the data, a wavelet-based smoothing algorithm is used to filter the high frequency noise. A shape analysis technique called triangular episodes then converts the smoothed data into a semi-qualitative form. Two membership functions are implemented to transform the quantitative information in the triangular episodes to a purely symbolic representation. The symbolic data is classified with a set of sequence matching hidden Markov models (HMMs), and the classification is improved by utilizing a time correlated HMM after the sequence matching HMM. The method is tested on simulations with a non-isothermal CSTR and compared with methods that use a back-propagation neural network with and without an ARX model.

Optimal dynamic experiments for bioreactor model discrimination

This paper describes a general approach for dynamic model discrimination for continuous cultures and presents dynamic models for pure cultures ofE. coli andC. utilis obtained using the method. For each pure culture system, four candidate models representing various levels of structure were considered. All models reduce to Monod growth kinetics at steady state. An optimized set of multivariable step inputs in selected manipulative variables was used to discriminate between candidate models. The models that best predicted the dynamic behavior were selected by comparison of model predictions with experimental data. Two discrimination functions were compared in terms of their ability to determine the optimal set of multivariable step inputs to discriminate between candidate models. Results indicate that model discrimination based on maximizing the minimum absolute difference between any two models for a given set of inputs possessed good potential for discrimination between candidate models. Models selected forE. coli andC. utilis from the model discrimination work are presented and compared with experimental data.