Improved production of industrially relevant recombinant proteins: application of multi-factorial design of experiments and scalable process modelling

The work described in this thesis focuses on the use of a design-of-experiments approach in a multi-well mini-bioreactor to enable the rapid establishments of high yielding production phase conditions in yeast, which is an increasingly popular host system in both academic and industrial laboratories. Using green fluorescent protein secreted from the yeast, Pichia pastoris, a scalable predictive model of protein yield per cell was derived from 13 sets of conditions each with three factors (temperature, pH and dissolved oxygen) at 3 levels and was directly transferable to a 7 L bioreactor. This was in clear contrast to the situation in shake flasks, where the process parameters cannot be tightly controlled. By further optimisating both the accumulation of cell density in batch and improving the fed-batch induction regime, additional yield improvement was found to be additive to the per cell yield of the model. A separate study also demonstrated that improving biomass improved product yield in a second yeast species, Saccharomyces cerevisiae. Investigations of cell wall hydrophobicity in high cell density P. pastoris cultures indicated that cell wall hydrophobin (protein) compositional changes with growth phase becoming more hydrophobic in log growth than in lag or stationary phases. This is possibly due to an increased occurrence of proteins associated with cell division. Finally, the modelling approach was validated in mammalian cells, showing its flexibility and robustness. In summary, the strategy presented in this thesis has the benefit of reducing process development time in recombinant protein production, directly from bench to bioreactor.

The implementation of a design of experiments strategy to increase recombinant protein yields in yeast (review)

Biological processes are subject to the influence of numerous factors and their interactions, which may be non-linear in nature. In a recombinant protein production experiment, understanding the relative importance of these factors, and their influence on the yield and quality of the recombinant protein being produced, is an essential part of its optimisation. In many cases, implementing a design of experiments (DoE) approach has delivered this understanding. This chapter aims to provide the reader with useful pointers in applying a DoE strategy to improve the yields of recombinant yeast cultures.

The implementation of a design of experiments strategy to increase recombinant protein yields in yeast (review)

Biological processes are subject to the influence of numerous factors and their interactions, which may be non-linear in nature. In a recombinant protein production experiment, understanding the relative importance of these factors, and their influence on the yield and quality of the recombinant protein being produced, is an essential part of its optimisation. In many cases, implementing a design of experiments (DoE) approach has delivered this understanding. This chapter aims to provide the reader with useful pointers in applying a DoE strategy to improve the yields of recombinant yeast cultures.

Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis

Renewable energy forms have been widely used in the past decades highlighting a "green" shift in energy production. An actual reason behind this turn to renewable energy production is EU directives which set the Union's targets for energy production from renewable sources, greenhouse gas emissions and increase in energy efficiency. All member countries are obligated to apply harmonized legislation and practices and restructure their energy production networks in order to meet EU targets. Towards the fulfillment of 20-20-20 EU targets, in Greece a specific strategy which promotes the construction of large scale Renewable Energy Source plants is promoted. In this paper, we present an optimal design of the Greek renewable energy production network applying a 0-1 Weighted Goal Programming model, considering social, environmental and economic criteria. In the absence of a panel of experts Data Envelopment Analysis (DEA) approach is used in order to filter the best out of the possible network structures, seeking for the maximum technical efficiency. Super-Efficiency DEA model is also used in order to reduce the solutions and find the best out of all the possible. The results showed that in order to achieve maximum efficiency, the social and environmental criteria must be weighted more than the economic ones.

A branch and efficiency algorithm for the optimal design of supply chain networks

Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.

Design of experiments to study the impact of process parameters on droplet size and development of non-invasive imaging techniques in tablet coating

Atomisation of an aqueous solution for tablet film coating is a complex process with multiple factors determining droplet formation and properties. The importance of droplet size for an efficient process and a high quality final product has been noted in the literature, with smaller droplets reported to produce smoother, more homogenous coatings whilst simultaneously avoiding the risk of damage through over-wetting of the tablet core. In this work the effect of droplet size on tablet film coat characteristics was investigated using X-ray microcomputed tomography (XμCT) and confocal laser scanning microscopy (CLSM). A quality by design approach utilising design of experiments (DOE) was used to optimise the conditions necessary for production of droplets at a small (20 μm) and large (70 μm) droplet size. Droplet size distribution was measured using real-time laser diffraction and the volume median diameter taken as a response. DOE yielded information on the relationship three critical process parameters: pump rate, atomisation pressure and coating-polymer concentration, had upon droplet size. The model generated was robust, scoring highly for model fit (R2 = 0.977), predictability (Q2 = 0.837), validity and reproducibility. Modelling confirmed that all parameters had either a linear or quadratic effect on droplet size and revealed an interaction between pump rate and atomisation pressure. Fluidised bed coating of tablet cores was performed with either small or large droplets followed by CLSM and XμCT imaging. Addition of commonly used contrast materials to the coating solution improved visualisation of the coating by XμCT, showing the coat as a discrete section of the overall tablet. Imaging provided qualitative and quantitative evidence revealing that smaller droplets formed thinner, more uniform and less porous film coats.

Design of improved membrane protein production experiments:quantitation of the host response

Eukaryotic membrane proteins cannot be produced in a reliable manner for structural analysis. Consequently, researchers still rely on trial-and-error approaches, which most often yield insufficient amounts. This means that membrane protein production is recognized by biologists as the primary bottleneck in contemporary structural genomics programs. Here, we describe a study to examine the reasons for successes and failures in recombinant membrane protein production in yeast, at the level of the host cell, by systematically quantifying cultures in high-performance bioreactors under tightlydefined growth regimes. Our data show that the most rapid growth conditions of those chosen are not the optimal production conditions. Furthermore, the growth phase at which the cells are harvested is critical: We show that it is crucial to grow cells under tightly-controlled conditions and to harvest them prior to glucose exhaustion, just before the diauxic shift. The differences in membrane protein yields that we observe under different culture conditions are not reflected in corresponding changes in mRNA levels of FPS1, but rather can be related to the differential expression of genes involved in membrane protein secretion and yeast cellular physiology. Copyright © 2005 The Protein Society.

Optimal design for correlated processes with input-dependent noise

Optimal design for parameter estimation in Gaussian process regression models with input-dependent noise is examined. The motivation stems from the area of computer experiments, where computationally demanding simulators are approximated using Gaussian process emulators to act as statistical surrogates. In the case of stochastic simulators, which produce a random output for a given set of model inputs, repeated evaluations are useful, supporting the use of replicate observations in the experimental design. The findings are also applicable to the wider context of experimental design for Gaussian process regression and kriging. Designs are proposed with the aim of minimising the variance of the Gaussian process parameter estimates. A heteroscedastic Gaussian process model is presented which allows for an experimental design technique based on an extension of Fisher information to heteroscedastic models. It is empirically shown that the error of the approximation of the parameter variance by the inverse of the Fisher information is reduced as the number of replicated points is increased. Through a series of simulation experiments on both synthetic data and a systems biology stochastic simulator, optimal designs with replicate observations are shown to outperform space-filling designs both with and without replicate observations. Guidance is provided on best practice for optimal experimental design for stochastic response models. © 2013 Elsevier Inc. All rights reserved.

Modelling of transient heat transfer in annealing furnaces

This is a study of heat transfer in a lift-off furnace which is employed in the batch annealing of a stack of coils of steel strip. The objective of the project is to investigate the various factors which govern the furnace design and the heat transfer resistances, so as to reduce the time of the annealing cycle, and hence minimize the operating costs. The work involved mathematical modelling of patterns of gas flow and modes of heat transfer. These models are: Heat conduction and its conjectures in the steel coils;Convective heat transfer in the plates separating the coils in the stack and in other parts of the furnace; and Radiative and convective heat transfer in the furnace by using the long furnace model. An important part of the project is the development of numerical methods and computations to solve the transient models. A limited number of temperature measurements was available from experiments on a test coil in an industrial furnace. The mathematical model agreed well with these data. The model has been used to show the following characteristics of annealing furnaces, and to suggest further developments which would lead to significant savings: - The location of the limiting temperature in a coil is nearer to the hollow core than to the outer periphery. - Thermal expansion of the steel tends to open the coils, reduces their thermal conductivity in the radial direction, and hence prolongs the annealing cycle. Increasing the tension in the coils and/or heating from the core would overcome this heat transfer resistance. - The shape and dimensions of the convective channels in the plates have significant effect on heat convection in the stack. An optimal design of a channel is shown to be of a width-to-height ratio equal to 9. - Increasing the cooling rate, by using a fluidized bed instead of the normal shell and tube exchanger, would shorten the cooling time by about 15%, but increase the temperature differential in the stack. - For a specific charge weight, a stack of different-sized coils will have a shorter annealing cycle than one of equally-sized coils, provided that production constraints allow the stacking order to be optimal. - Recycle of hot flue gases to the firing zone of the furnace would produce a. decrease in the thermal efficiency up to 30% but decreases the heating time by about 26%.

Some studies relating to the design of shallow, fluidized bed boilers

The concept of shallow fluidized bed boilers is defined and a preliminary working design for a gas-fired package boiler has been produced. Those areas of the design requiring further study have been specified. Experimental investigations concerning these areas have been carried out. A two-dimensional, conducting paper analog has been developed for the specific purpose of evaluating sheet fins. The analog has been generalised and is presented as a simple means of simulating the general, two-dimensional Helmholtz equation. By recording the transient response of spherical, calorimetric probes when plunged into heated air-fluidized beds, heat transfer coefficients have been measured at bed temperatures up to 1 100°C. A correlation fitting all the data to within ±10% has been obtained. A model of heat transfer to surfaces immersed in high temperature beds has been proposed. The model solutions are, however, only in qualitative agreement with the experimental data. A simple experimental investigation has revealed that the effective, radial, thermal conductivities of shallow fluidized beds are an order of magnitude lower than the axial conductivities. These must, consequently, be taken into account when considering heat transfer to surfaces immersed within fluidized beds. Preliminary work on pre-mixed gas combustion and some further qualitative experiments have been used as the basis for discussing the feasibility of combusting heavy fuel oils within shallow beds. The use of binary beds, within which the fuel could be both gasified and subsequently burnt, is proposed. Finally, the consequences of the experimental studies on the initial design are considered, and suggestions for further work are made.

The design of environmental test rigs

Product reliability and its environmental performance have become critical elements within a product's specification and design. To obtain a high level of confidence in the reliability of the design it is customary to test the design under realistic conditions in a laboratory. The objective of the work is to examine the feasibility of designing mechanical test rigs which exhibit prescribed dynamical characteristics. The design is then attached to the rig and excitation is applied to the rig, which then transmits representative vibration levels into the product. The philosophical considerations made at the outset of the project are discussed as they form the basis for the resulting design methodologies. It is attempted to directly identify the parameters of a test rig from the spatial model derived during the system identification process. It is shown to be impossible to identify a feasible test rig design using this technique. A finite dimensional optimal design methodology is developed which identifies the parameters of a discrete spring/mass system which is dynamically similar to a point coordinate on a continuous structure. This design methodology is incorporated within another procedure which derives a structure comprising a continuous element and a discrete system. This methodology is used to obtain point coordinate similarity for two planes of motion, which is validated by experimental tests. A limitation of this approach is that it is impossible to achieve multi-coordinate similarity due to an interaction of the discrete system and the continuous element at points away from the coordinate of interest. During the work the importance of the continuous element is highlighted and a design methodology is developed for continuous structures. The design methodology is based upon distributed parameter optimal design techniques and allows an initial poor design estimate to be moved in a feasible direction towards an acceptable design solution. Cumulative damage theory is used to provide a quantitative method of assessing the quality of dynamic similarity. It is shown that the combination of modal analysis techniques and cumulative damage theory provides a feasible design synthesis methodology for representative test rigs.

Structural behaviour and design of load-bearing falsework

Tne object of this research was to investigate the behaviour of birdcage scaffolding as used in falsework structures, assess the suitability of existing design methods and make recommendations for a set of design rules. Since excessive deflection is as undesirable in a structure as total collapse, the project was divided into two sections. These were to determine the ultimate vertical and horizontal load-carrying capacity and also the deflection characteristics of any falsework. So theoretical analyses were developed to ascertain the ability of both the individual standards to resist vertical load, and of the bracing to resist horizontal load.Furthermore a model was evolved which would predict the horizontal deflection of a scaffold under load using strain energy methods. These models were checked by three series of experiments. The first was on individual standards under vertical load only. The second series was carried out on full scale falsework structures loading vertically and horizontally to failure. Finally experiments were conducted on scaffold couplers to provide additional verification of the method of predicting deflections. This thesis gives the history of the project and an introduction into the field of scaffolding. It details both the experiments conducted and the theories developed and the correlation between theory and experiment. Finally it makes recommendations for a design method to be employed by scaffolding designers.

Agent-orientated auction mechanism and strategy design

Agent-based technology is playing an increasingly important role in today’s economy. Usually a multi-agent system is needed to model an economic system such as a market system, in which heterogeneous trading agents interact with each other autonomously. Two questions often need to be answered regarding such systems: 1) How to design an interacting mechanism that facilitates efficient resource allocation among usually self-interested trading agents? 2) How to design an effective strategy in some specific market mechanisms for an agent to maximise its economic returns? For automated market systems, auction is the most popular mechanism to solve resource allocation problems among their participants. However, auction comes in hundreds of different formats, in which some are better than others in terms of not only the allocative efficiency but also other properties e.g., whether it generates high revenue for the auctioneer, whether it induces stable behaviour of the bidders. In addition, different strategies result in very different performance under the same auction rules. With this background, we are inevitably intrigued to investigate auction mechanism and strategy designs for agent-based economics. The international Trading Agent Competition (TAC) Ad Auction (AA) competition provides a very useful platform to develop and test agent strategies in Generalised Second Price auction (GSP). AstonTAC, the runner-up of TAC AA 2009, is a successful advertiser agent designed for GSP-based keyword auction. In particular, AstonTAC generates adaptive bid prices according to the Market-based Value Per Click and selects a set of keyword queries with highest expected profit to bid on to maximise its expected profit under the limit of conversion capacity. Through evaluation experiments, we show that AstonTAC performs well and stably not only in the competition but also across a broad range of environments. The TAC CAT tournament provides an environment for investigating the optimal design of mechanisms for double auction markets. AstonCAT-Plus is the post-tournament version of the specialist developed for CAT 2010. In our experiments, AstonCAT-Plus not only outperforms most specialist agents designed by other institutions but also achieves high allocative efficiencies, transaction success rates and average trader profits. Moreover, we reveal some insights of the CAT: 1) successful markets should maintain a stable and high market share of intra-marginal traders; 2) a specialist’s performance is dependent on the distribution of trading strategies. However, typical double auction models assume trading agents have a fixed trading direction of either buy or sell. With this limitation they cannot directly reflect the fact that traders in financial markets (the most popular application of double auction) decide their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders. Experiments are conducted under both dynamic and static settings of the continuous BDA market. We find that the allocative efficiency of a continuous BDA market mainly comes from rational selection of trading directions. Furthermore, we introduce a high-performance Kernel trading strategy in the BDA market which uses kernel probability density estimator built on historical transaction data to decide optimal order prices. Kernel trading strategy outperforms some popular intelligent double auction trading strategies including ZIP, GD and RE in the continuous BDA market by making the highest profit in static games and obtaining the best wealth in dynamic games.

Design of a genetic algorithm for bi-objective flow shop scheduling problems with re-entrant jobs

This paper presents a simulated genetic algorithm (GA) model of scheduling the flow shop problem with re-entrant jobs. The objective of this research is to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines in the same order. Furthermore, the re-entrant jobs are stochastic as only some jobs are required to reenter to the flow shop. The tardiness weight is adjusted once the jobs reenter to the shop. The performance of the proposed GA model is verified by a number of numerical experiments where the data come from the case company. The results show the proposed method has a higher order satisfaction rate than the current industrial practices.