Technological options for biological fuel ethanol

The current paradigm to produce biotechnological ethanol is to use the yeast Saccharomyces cerevisiae to ferment sugars derived from starch or sugar crops such as maize, sugar cane or sugar beet. Despite its current success, the global impact of this manufacturing model is restricted on the one hand by limits on the availability of these primary raw materials, and on the other hand by the maturity of baker's yeast fermentation technologies. Revisiting the technical, economic, and value chain aspects of the biotechnological ethanol industry points to the need for radical innovation to complement the current manufacturing model. Implementation of lignocellulosic materials is clearly a key enabler to the billion-ton biofuel vision. However, realization of the full market potential of biofuels will be facilitated by the availability of an array of innovative technological options, as the flexibility generated by these alternative processes will not only enable the exploitation of heretofore untapped local market opportunities, but also it will confer to large biorefinery structures numerous opportunities for increased process integration as well as optimum reactivity to logistic and manufacturing challenges. In turn, all these factors will interplay in synergy to contribute in shifting the economic balance in favor of the global implementation of biotechnological ethanol.     

Structural identifiability of a model for the acetic acid fermentation process

Modelling has proved an essential tool for addressing research into biotechnological processes, particularly with a view to their optimization and control. Parameter estimation via optimization approaches is among the major steps in the development of biotechnology models. In fact, one of the first tasks in the development process is to determine whether the parameters concerned can be unambiguously determined and provide meaningful physical conclusions as a result. The analysis process is known as 'identifiability' and presents two different aspects: structural or theoretical identifiability and practical identifiability. While structural identifiability is concerned with model structure alone, practical identifiability takes into account both the quantity and quality of experimental data. In this work, we discuss the theoretical identifiability of a new model for the acetic acid fermentation process and review existing methods for this purpose.     

Linking a farm model and a location optimization model for evaluating energetic and material straw valorization pathways—A case study in Baden‐Wuerttemberg

Diminishing fossil carbon resources, global warming, and increasing material and energy needs urge for the rapid development of a bioeconomy. Biomass feedstock from agro‐industrial value chains provides opportunities for energy and material production, potentially leading to competition with traditional food and feed production. Simulation and optimization models can support the evaluation of biomass value chains and identify bioeconomy development paths, potentials, opportunities, and risks. This study presents the linkage of a farm model (EFEM) and a techno‐economic location optimization model (BIOLOCATE) for evaluating the straw‐to‐energy and the innovative straw‐to‐chemical value chains in the German federal state of Baden‐Wuerttemberg taking into account the spatially distributed and price‐sensitive nature of straw supply. The general results reveal the basic trade‐off between economies of scale of the energy production plants and the biorefineries on the one hand and the feedstock supply costs on the other hand. The results of the farm model highlight the competition for land between traditional agricultural biomass utilization such as food and feed and innovative biomass‐to‐energy and biomass‐to‐chemical value chains. Additionally, farm‐modeling scenarios illustrate the effect of farm specialization and regional differences on straw supply for biomass value chains as well as the effect of high straw prices on crop choices. The technological modeling results show that straw combustion could cover approximately 2% of Baden‐Wuerttemberg's gross electricity consumption and approximately 35% of the district heating consumption. The lignocellulose biorefinery location and size are affected by the price sensitivity of the straw supply and are only profitable for high output prices of organosolv lignin. The location optimization results illustrate that economic and political framework conditions affect the regional distribution of biomass straw conversion plants, thus favoring decentralized value chain structures in contrast to technological economies of scale.     

Integrated process optimization: lessons from retrovirus and virus-like particle production

The optimization of production and purification processes is usually approached by engineers from a strictly biotechnological point of view. The present paper envisages the definition and application of an optimization model that takes into account the impact of both biological and technological issues upon the optimization protocols and strategies. For this purpose, the optimization of three analogous but different systems comprising animal cell growth and bioparticle production is presented. These systems were: human immunodeficiency 1 (HIV-1) and porcine parvovirus (PPV) virus-like particles (VLPs) produced in insect cells and retrovirus produced in mammalian cells. For the systematization of the optimization process four levels of optimization were defined-product, technology, design and integration. In this paper, the limits of each of the optimization levels defined are discussed by applying the concept to the systems described. This analysis leads to decisions regarding the production of VLPs and retrovirus as well as on the points relevant for further process development. Finally, the definition of the objective function or performance index, the possible strategies and tools for bioprocess optimization are described. Although developed from the three described processes, this approach can, based on the recent literature evidence reviewed here, be applied more universally for the process development of complex biopharmaceuticals.     

Modeling product formation in anaerobic mixed culture fermentations

The anaerobic conversion of organic matter to fermentation products is an important biotechnological process. The prediction of the fermentation products is until now a complicated issue for mixed cultures. A modeling approach is presented here as an effort to develop a methodology for modeling fermentative mixed culture systems. To illustrate this methodology, a steady-state metabolic model was developed for prediction of product formation in mixed culture fermentations as a function of the environmental conditions. The model predicts product formation from glucose as a function of the hydrogen partial pressure (P(H2)), reactor pH, and substrate concentration. The model treats the mixed culture as a single virtual microorganism catalyzing the most common fermentative pathways, producing ethanol, acetate, propionate, butyrate, lactate, hydrogen, carbon dioxide, and biomass. The product spectrum is obtained by maximizing the biomass growth yield which is limited by catabolic energy production. The optimization is constrained by mass balances and thermodynamics of the bioreactions involved. Energetic implications of concentration gradients across the cytoplasmic membrane are considered and transport processes are associated with metabolic energy exchange to model the pH effect. Preliminary results confirmed qualitatively the anticipated behavior of the system at variable pH and P(H2) values. A shift from acetate to butyrate as main product when either P(H2) increases and/or pH decreases is predicted as well as ethanol formation at lower pH values. Future work aims at extension of the model and structural validation with experimental data.     

Performance modeling and simulation of biochemical process sequences with interacting unit operations

Many biochemical processes consist of a sequence of operations for which optimal operating conditions (setpoints) have to be determined. If such optimization is performed for each operation separately with respect to objectives defined for each operation individually, overall process performance is likely to be suboptimal. Interactions between unit operations have to be considered, and a unique objective has to be defined for the whole process. This paper shows how a suitable optimization problem can be formulated and solved to obtain the best overall set of operating conditions for a process. A typical enzyme production process has been chosen as an example. In order to arrive at a demonstrative model for the entire sequence of unit operations, it is shown how interaction effects may be accommodated in the models. Optimal operating conditions are then determined subject to a global process objective and are shown to be different from those resulting from optimization of each separate operation. As this strategy may result in an economic benefit, it merits further research into interaction modeling and performance optimization.     

Integrating life cycle cost analysis and LCA

The private sector decision making situations which LCA addresses mustalso eventually take theeconomic consequences of alternative products or product designs into account. However, neither the internal nor external economic aspects of the decisions are within the scope of developed LCA methodology, nor are they properly addressed by existing LCA tools. This traditional separation of life cycle environmental assessment from economic analysis has limited the influence and relevance of LCA for decision-making, and left uncharacterized the important relationships and trade-offs between the economic and life cycle environmental performance of alternative product design decision scenarios. Still standard methods of LCA can and have been tightly, logically, and practically integrated with standard methods for cost accounting, life cycle cost analysis, and scenario-based economic risk modeling. The result is an ability to take both economic and environmental performance — and their tradeoff relationships — into account in product/process design decision making.     

Optimal synthesis of protein purification processes

There has been an increasing interest in the development of systematic methods for the synthesis of purification steps for biotechnological products, which are often the most difficult and costly stages in a biochemical process. Chromatographic processes are extensively used in the purification of multicomponent biotechnological systems. One of the main challenges in the synthesis of purification processes is the appropriate selection and sequencing of chromatographic steps that are capable of producing the desired product at an acceptable cost and quality. This paper describes mathematical models and solution strategies based on mixed integer linear programming (MILP) for the synthesis of multistep purification processes. First, an optimization model is proposed that uses physicochemical data on a protein mixture, which contains the desired product, to select a sequence of operations with the minimum number of steps from a set of candidate chromatographic techniques that must achieve a specified purity level. Since several sequences that have the minimum number of steps may satisfy the purity level, it is possible to obtain the one that maximizes final purity. Then, a second model that may use the total number of steps obtained in the first model generates a solution with the maximum purity of the product. Whenever the sequence does not affect the final purity or more generally does not impact the objective function, alternative models that are of smaller size are developed for the optimal selection of steps. The models are tested in several examples, containing up to 13 contaminants and a set of 22 candidate high-resolution steps, generating sequences of six operations, and are compared to the current synthesis approaches.     

Assessment of lignocellulosic biorefineries in Germany using a hybrid LCA multi‐objective optimization model

In this study a tiered hybrid life cycle assessment (LCA) multi‐objective optimization model is developed and applied to determine the optimal choice of new biorefinery technologies in Germany. Thereby, several aspects can be explicitly addressed, including a regionally differentiated accountability of sustainable feedstock availability, identification of environmental impacts along global value chains, and identification of trade‐offs between different sustainability goals. The model is applied to assess the optimal choice between two lignocellulosic biorefinery concepts. Two optimization objectives are taken into account: maximizing the investor's profit and minimizing global impacts on climate change related to a specified demand for products. In terms of environmental impacts, the model also takes into account the comparison of new biorefineries with current available technologies producing the specified final demand. The results of the case study show that the biorefinery concept including the ethylene production is more beneficial in terms of reducing climate impacts, while on the other hand the biorefinery including the ethanol production is more cost‐effective. Depending on the decision‐maker's preference on weighting the two objectives, different capacities of biorefineries and optimal locations in Germany are identified. Furthermore, regions in Germany providing the necessary biomass feedstock can be identified on a county level. Finally, we argue that the extension of LCA by multi‐objective optimization is well suited guiding the way toward well‐informed decision‐making in the field of technological choices.     

Metabolic engineering of Cyanobacteria and microalgae for enhanced production of biofuels and high‐value products

A lot of research has been performed on Cyanobacteria and microalgae with the aim to produce numerous biotechnological products. However, native strains have a few shortcomings, like limitations in cultivation, harvesting and product extraction, which prevents reaching optimal production value at lowest costs. Such limitations require the intervention of genetic engineering to produce strains with superior properties. Promising advancements in the cultivation of Cyanobacteria and microalgae have been achieved by improving photosynthetic efficiency through increasing RuBisCO activity and truncation of light‐harvesting antennae. Genetic engineering has also contributed to final product extraction by inducing autolysis and product secretory systems, to enable direct product recovery without going through costly extraction steps. In this review, we summarize the different enzymes and pathways that have been targeted thus far for improving cultivation aspects, harvesting and product extraction in Cyanobacteria and microalgae. With synthetic biology advancements, genetically engineered strains can be generated to resolve demanding process issues and achieve economic practicality. This comprehensive overview of gene modifications will be useful to researchers in the field to employ on their strains to increase their yields and improve the economic feasibility of the production process.     

A fuzzy multi-objective optimization model for sustainable reverse logistics network design

Decreasing the environmental impact, increasing the degree of social responsibility, and considering the economic motivations of organizations are three significant features in designing a reverse logistics network under sustainability respects. Developing a model, which can simultaneously consider these environmental, social, and economic aspects and their indicators, is an important problem for both researchers and practitioners. In this paper, we try to address this comprehensive approach by using indicators for measurement of aforementioned aspects and by applying fuzzy mathematical programming to design a multi-echelon multi-period multi-objective model for a sustainable reverse logistics network. To reflect all aspects of sustainability, we try to minimize the present value of costs, as well as environmental impacts, and optimize the social responsibility as objective functions of the model. In order to deal with uncertain parameters, fuzzy mathematical programming is used, and to obtain solutions on Pareto front, a customized multi-objective particle swarm optimization (MOPSO) algorithm is applied. The validity of the proposed solution procedure has been analyzed in small and large size test problems based on four comparison metrics and computational time using analysis of variance. Finally, in order to indicate the applicability of the suggested model and the practicality of the proposed solution procedure, the model has been implemented in a medical syringe recycling system. The results reveal that the suggested MOPSO algorithm overtakes epsilon-constraint method from the aspects of quality of the solutions as well as computational time. Proper use of the proposed process could help managers efficiently manage the flow of recycled products with regard to environmental and social considerations, and the process offers a sustainable competitive advantage to corporations.     

Biosurfactant production: emerging trends and promising strategies

Biosurfactants are economically most sought after biotechnological compounds of the 21st century. However, inefficient bioprocessing has mitigated the economical commercial production of these compounds. Although much work is being done on the use of low-cost substrates for their production, a paucity of literature exists on the upcoming bioprocess optimization strategies and their successes and potential for economical biosurfactant production. This review discusses some of the latest developments and most promising strategies to enhance and economize the biosurfactant production process. Recent market analysis, developments in the field of optimally formulated cost credit substrates for enhanced product formation and subsequent process economization are few of the critical aspects highlighted here. Use of nanoparticles and coproduction of biosurfactant along with other commercially important compounds like enzymes, are other upcoming bioprocess intensification strategies. The recent developments discussed here would not only give an overview of pertinent parameters for economic biosurfactant production but would also bring to fore multiple strategies that would open up new avenues of research on biosurfactant production. This would go a long way in making biosurfactants a commercially successful compound of the current century.     

An overview of mechanistic modeling of liquid chromatography

Abstract

Liquid chromatography is considered to be the bottleneck for purification of therapeutic proteins. Development and optimization of chromatography process is a cumbersome activity due to the increasing complexities in the types and content of impurities present in the high product titer cell culture harvest obtained from the upstream processing. Further, regulatory expectations are continuously rising with the recent initiatives of quality by design and process analytical technology expecting the manufacturer to have a deeper understanding of the process and the product. Mechanistic modeling is one approach to gain this deeper understanding of a process step. It involves modeling of the underlying physicochemical processes. A well calibrated model with acceptable predictability can be very effective in both process optimization and process characterization activities. In this paper we provide an overview of mechanistic modeling of liquid chromatography. We discuss the various components that such a model entails and also presents the status quo of this area.     

The behavior of adaptive bone-remodeling simulation models

The process of adaptive bone remodeling can be described mathematically and simulated in a computer model, integrated with the finite element method. In the model discussed here, cortical and trabecular bone are described as continuous materials with variable density. The remodeling rule applied to simulate the remodeling process in each element individually is, in fact, an objective function for an optimization process, relative to the external load. Its purpose is to obtain a constant, preset value for the strain energy per unit bone mass, by adapting the density. If an element in the structure cannot achieve that, it either turns to its maximal density (cortical bone) or resorbs completely.

It is found that the solution obtained in generally a discontinuous patchwork. For a two-dimensional proximal femur model this patchwork shows a good resemblance with the density distribution of a real proximal femur.

It is shown that the discontinuous end configuration is dictated by the nature of the differential equations describing the remodeling process. This process can be considered as a nonlinear dynamical system with many degrees of freedom, which behaves divergent relative to the objective, leading to many possible solutions. The precise solution is dependent on the parameters in the remodeling rule, the load and the initial conditions. The feedback mechanism in the process is self-enhancing; denser bone attracts more strain energy, whereby the bone becomes even more dense. It is suggested that this positive feedback of the attractor state (the strain energy field) creates order in the end configuration. In addition, the process ensures that the discontinuous end configuration is a structure with a relatively low mass, perhaps a minimal-mass structure, although this is no explicit objective in the optimization process.

It is hypothesized that trabecular bone is a chaotically ordered structure which can be considered as a fractal with characteristics of optimal mechanical resistance and minimal mass, of which the actual morphology depends on the local (internal) loading characteristics, the sensor-cell density and the degree of mineralization.     

Prediction of the pilot-scale recovery of a recombinant yeast enzyme using integrated models

This article describes the rapid prediction of recovery process performance for a new recombinant enzyme product on the basis of a broad portfolio of computer models and highly targeted experimentation. A process model for the recombinant system was generated by linking unit operation models in an integrated fashion, with required parameter estimation and physical property determination accomplished using data from scale-down studies. This enabled the generic modeling framework established for processing of a natural enzyme from bakers' yeast to be applied. An experimental study of the same operations at the pilot scale showed that the process model gave a conservative prediction of recombinant enzyme recovery. The model successfully captured interactions leading to a low overall product yield and indicated the need for further study of precipitate breakage in the feed zone of a disc stack centrifuge in order to improve performance. The utility of scale-down units as an aid to fast model generation and the advantage of integrating computer modeling and scale-down studies to accelerate bioprocess development are highlighted.     

Neuromusculoskeletal computer modeling and simulation of upright, straight-legged, bipedal locomotion of Australopithecus afarensis (A.L. 288-1)

The skeleton of Australopithecus afarensis (A.L. 288-1, better known as "Lucy") is by far the most complete record of locomotor morphology of early hominids currently available. Even though researchers agree that the postcranial skeleton of Lucy shows morphological features indicative of bipedality, only a few studies have investigated Lucy's bipedal locomotion itself. Lucy's energy expenditure during locomotion has been the topic of much speculation, but has not been investigated, except for several estimates derived from experimental data collected on other animals. To gain further insights into how Lucy may have walked, we generated a full three-dimensional (3D) reconstruction and forward-dynamic simulation of upright bipedal locomotion of this ancient human ancestor. Laser-scanned 3D bone geometries were combined with state-of-the-art neuromusculoskeletal modeling and simulation techniques from computational biomechanics. A detailed full 3D neuromusculoskeletal model was developed that encompassed all major bones, joints (10), and muscles (52) of the lower extremity. A model of muscle force and heat production was used to actuate the musculoskeletal system, and to estimate total energy expenditure during locomotion. Neural activation profiles for each of the 52 muscles that produced a single step of locomotion, while at the same time minimizing the energy consumed per meter traveled, were searched through numerical optimization. The numerical optimization resulted in smooth locomotor kinematics, and the predicted energy expenditure was appropriate for upright bipedal walking in an individual of Lucy's body size.     

Regulatory perspectives from Japan - comparability of biopharmaceuticals.

In Japan there is no official guideline about comparability assessment of biotechnological products at present. However, there is some notifications which should be referred to, when the manufacturer changes the manufacturing process. Here, regulatory perspectives from Japan on the comparability assessment are presented. When establishing the comparability of biotechnological products derived from different manufacturing processes and the validity of modified manufacturing process, rational step-by-step approaches based on both product and process aspects would be useful. At first, relevant physicochemical and biological properties of products including purity, impurity profiles and stability should be compared before and after the manufacturing change, depending on the type and nature of the desired products. It is also necessary to examine the capacities of the new manufacturing process for ensuring the consistent production of the active protein product as well as the anticipated elimination of potential impurities and contaminants. Further relevant assessment of preclinical and clinical comparability of product may be necessary in some cases.     

Proteomic characterization of a wild-type wine strain of Saccharomyces cerevisiae

Saccharomyces cerevisiae is the optimal eukaryotic model system to study mammalian biological responses. At the same time Saccharomyces cerevisiae is also widely utilized as a biotechnological tool in the food industry. Enological Saccharomyces cerevisiae strains have been so far routinely analyzed for their microbiological aspects. Nevertheless, wine yeasts are gaining an increasing interest in the last years since they strongly affect both the vinification process and the organoleptic properties of the final product wine. The protein repertoire is responsible of such features and, consequently, 2D-PAGE can be an useful tool to evaluate and select optimal wine yeast strains. We present here the first proteomic map of a wild-type wine Saccharomyces cerevisiae strain selected for the guided fermentation of very high quality wines.     

Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction

One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer’s utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider.