Early Stages Of Development Process Research Articles

Using Green Chemistry and Engineering Principles To Design, Assess, and Retrofit Chemical Processes for Sustainability.

The concepts of green chemistry and engineering (GC&E) have been promoted as an effective qualitative framework for developing more sustainable chemical syntheses, processes, and material management techniques. This has been demonstrated by many theoretical and practical cases. In addition, there are several approaches and frameworks focused on demonstrating that improvements were achieved through GC&E technologies. However, the application of these principles is not always straightforward. We propose using systematic frameworks and tools that help practitioners when deciding which principles can be applied, the levels of implementation, prospective of obtaining simultaneous improvements in all sustainability aspects, and ways to deal with multiobjective problems. Therefore, this contribution aims to provide a systematic combination of three different and complementary design tools for assisting designers in evaluating, developing, and improving chemical manufacturing and materials management systems under GC&E perspectives. The WAR Algorithm, GREENSCOPE, and SustainPro were employed for this synergistic approach of incorporating sustainability at early stages of process development. In this demonstration, simulated ammonia production is used as a case study to illustrate this advancement. Results show how to identify process design areas for improvements, key factors, multicriteria decision-making solutions, and optimal trade-offs. Finally, conclusions were presented regarding the tools' use in more robust sustainable process and material management designs.

Progress and challenges in large-scale expansion of human pluripotent stem cells

The constant supply of high cell numbers generated by defined, robust, and economically viable culture processes is indispensable for the envisioned application of human pluripotent stem cells (hPSCs) and their progenies for drug discovery and regenerative medicine. To achieve required cell numbers and to reduce process-related risks such as cell transformation, relative short batch-like production processes at industry- and clinically-relevant scale(s) must be developed and optimized. Here, we will review recent progress in the large-scale expansion of hPSCs with particular focus on suspension culture, which represents a universal strategy for controlled mass cell production. Another focus of the paper relates to bioreactor-based approaches, including technical aspects of bioreactor technologies and operation modes. Lastly, we will discuss current challenges of hPSC process engineering for enabling the transition from early stage process development to fully optimized hPSC production scale operation, a mandatory step for hPSCs’ industrial and clinical translation.

Quantitative Sustainability Analysis: A Powerful Tool to Develop Resource-Efficient Catalytic Technologies

Demand for chemicals is growing. In fact, the chemical industry’s global output is expected to nearly double its 2010 volume by 2020. Lessening the collateral environmental burden of such growth requires sustainable alternative technologies. Fortunately, green chemistry and engineering research has made remarkable progress, laying the foundation for developing efficient processes that conserve feedstock and energy. Life cycle assessment (LCA) also plays a key role by identifying environmental hotspots along the supply chain, either within the manufacturing plant (catalysts, solvents, reactors, separators) or upstream during raw material extraction or during the generation of fossil-based energy at any stage. We present several examples that illustrate how important it is to incorporate LCA with techno-economic analysis—especially during the early stages of process development. This approach is not just useful, it is an essential tool for the rational development of sustainable chemical processes.

Transfer of Emulsion Polymerization of Styrene and n‐Butyl Acrylate from Semi‐Batch to a Continuous Tubular Reactor

The transfer of a semi‐batch emulsion copolymerization to a single feed continuous recipe is investigated herein. A single feed continuous tubular reactor is used in the presented study in accordance with the requirement of minimizing the number of dosing streams. The correlation between operating parameters and the product properties are experimentally presented for the semi‐batch as well as for the single feed continuous tubular reactor. It is shown that the transfer from semi‐batch to continuous smart‐scale tubular reactor needs to be direct as opposed to via a batch reactor. The particle sizes and molecular masses obtained in the tubular reactor are similar to those of the semi‐batch process. However, the adjustment of the polymer composition is challenging. Using monomer addition as a means to influence chemical composition is not applicable. Thus, in the tubular reactor the chemical composition of the resulting copolymer depends on the initial monomer composition and reaction temperature. Nevertheless, the mass transfer of the emulsion polymerization damps the copolymer composition distribution (CCD) drift for higher initial monomer contents compared to bulk polymerization. It is shown that transfer of a semi‐batch product to a continuous recipe is possible in early stages of process development. image

A machine learning based software process model recommendation method

Among many factors that influence the success of a software project, the software process model employed is an essential one. An improper process model will be time consuming, error-prone and cost expensive, and further lower the quality of software. Therefore, how to choose an appropriate software process model is a very important problem for software development. Current works focus on the selection criteria and often lead to subjective results. In this paper, we propose a software process model recommendation method, to help project managers choose the most appropriate software process model for a new project at an early stage of development process according to historical software engineering data. The proposed method casts the process model recommendation into a classification problem. It first evaluates the different combinations of the alternative classification and attribute selection algorithms, and the best one is used to build the recommendation model with historical software engineering data; then, the constructed recommendation model is used to predict process models for a new software project with only a few data. We also analyze the mutual impacts between process models and different types of project factors, to further help managers locate the most suitable process model. We found process models are also responsible for defect count, defect severity and software change. Experiments on the data sets from 37 different development teams of different countries show that the average recommendation accuracy of our method reaches up to 82.5%, which makes it potentially useful in practice.

A scale-down mimic for mapping the process performance of centrifugation, depth and sterile filtration.

ABSTRACTIn the production of biopharmaceuticals disk‐stack centrifugation is widely used as a harvest step for the removal of cells and cellular debris. Depth filters followed by sterile filters are often then employed to remove residual solids remaining in the centrate. Process development of centrifugation is usually conducted at pilot‐scale so as to mimic the commercial scale equipment but this method requires large quantities of cell culture and significant levels of effort for successful characterization. A scale‐down approach based upon the use of a shear device and a bench‐top centrifuge has been extended in this work towards a preparative methodology that successfully predicts the performance of the continuous centrifuge and polishing filters. The use of this methodology allows the effects of cell culture conditions and large‐scale centrifugal process parameters on subsequent filtration performance to be assessed at an early stage of process development where material availability is limited. Biotechnol. Bioeng. 2016;113: 1934–1941. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Q-SA√ESS: a methodology to help solvent selection for pharmaceutical manufacture at the early process development stage

A practicable, LCA based methodology has been developed to evaluate the sustainability implications of solvent selection during early process development for a batch manufacturing process for an API.

From Clone Selection to 80L Bioreactor Production: Better, Faster, Leaner

Materials and methods AmbrTM 48 and 80L stirred tank bioreactor were run for 14 days in a fed-batch mode in a chemically defined medium. A CHO cell line expressing a recombinant monoclonal antibody (MAb) was used. Feed was added daily from day 3 onwards. If required, antifoam C was added to the bioreactor. DO, pH, and temperature were controlled at setpoint. Viable cell concentration (VCC), cell viability, and average cell diameter were measured using a ViCell cell counter. Osmolality was obtained using an Osmometer (Advanced Instruments). On harvest day, MAb concentration of the supernatant samples was quantified using Protein A high performance liquid chromatography. For the minibioreactors run, triplicates were pooled on harvest day for product quality attributes analysis. For both scales cell culture fluid samples were centrifuged and filtered to remove cell debris. The monoclonal antibody was purified by AKTAXpress (GE Healthcare) Protein-A purification. The neutralized eluate was used for product quality analysis. Results High throughput technologies enable us to interconnect clone and process development thus reducing the risks associated with early-stage process development while reducing timelines and enabling us to achieve higher process robustness in a leaner manner. In one ambrTM48 run different feeding strategies were assessed on 4 preselected lead clones for selecting the final lead clone, the fed-batch feeding strategy and additional data with feed compositions all at once. The selected condition (clone, type of feed and feeding strategy) was based on the maximization of the MAb titer and target High Molecular Weight Species (HMWS) level and Acidic Peak Group (APG) level (data not shown). Scale up from ambrTM 48 to 80L stirred tank bioreactor was performed with the selected clone, feed and feeding strategy. Similar cell growth profiles were obtained at ambrTM scale and 80L scale for the selected condition (Figure 1). Monoclonal Antibody titers and percentages of Acidic Peak Group obtained at harvest day were comparable between scales (Table 1). Process robustness was shown by performing a number of 4 batches at 80L scale.

Interpreting process data of wet pressing process. Part 1: Theoretical approach

The wet pressing process represents a new production method for carbon fibre-reinforced plastics components. Due to the low cycle times, it is suitable for use in the automotive industry. Therefore, a sufficient degree of industrialisation needs to be achieved, which is characterised by a stable process. The knowledge about relevant process parameters, their interactions, and influence on the part quality builds the basis of an economic process. This is a major challenge, since in the early stage of process development the available amount of recorded process data is small and the data sets are not complete. As the implementation of time-, material-, and cost-intensive experiments represents no acceptable alternative, a theoretical approach is chosen. This article describes a theoretical procedure to define the critical factors of the wet pressing process with significantly less resource input.

Software Performance Evaluation Utilizing UML Specification and SRN Model and Their Formal Representation

A distributed system is a complex system. Developing complex systems is a demanding task when attempting to achieve functional and non-functional properties such as synchronization, communication, fault tolerance. These properties impose immense complexities on the design, development, and implementation of a distributed system that incur massive effort and cost a large amount of money. Therefore, it is vital to ensure that the system must satisfy the functional and non-functional properties once the system development process is finished. Once a distributed system is developed, it is very difficult, time consuming, and expensive to conduct any modification in its architecture. As a result, the quantitative analysis of a complex distributed system at the early stage of the development process is always an essential and intricate endeavor. To meet the challenge of conducting quantitative analysis at the early stage of the system development process, this thesis introduces an extensive framework for performance and performability evaluation of a distributed system. The goal of the performance modeling framework is the assessment of the non-functional properties of the distributed system at an early stage based on the system’s functional description and deployment mapping of service components over an execution environment. The performability framework is the extension of the performance modeling framework. The extended part of the performability modeling framework considers the behavioral change of the system components due to failures. This later reveals how such behavioral changes affect the system performance. The reusable specification of service components is the main specification unit of our framework. The specification of the reusable service component is realized through UML collaboration and activity. Activity diagrams are used to aid the illustration of the complete behavior of a system, which includes both local behavior of the service components and the necessary interactions among them. Reusable building blocks are collaborative in nature, which allows them to span across several participating components. The local behavior and interaction among the participating components are realized in an encapsulated way, which can be further reused to develop new applications. The assignment of service components that capture the system functional behavior of the physical components is recognized as deployment mapping. Deployment mapping has a significant impact on ensuring the non-functional properties provided by the system in a resource limited environment. This thesis also specifies the deployment mapping of service components using UML deployment diagrams. The focus of the deployment mapping is on considering the non-functional requirements such that the performance of a service or a system on a particular physical infrastructure can be assessed in a fully distributed manner and for large scale. In addition, a UML state machine diagram is utilized in our performability modeling framework to capture the dependability behavior of the system components. To conduct the performance and performability evaluation of a distributed system, the UML model is transformed into analytic models that provide performance and performability evaluation results. The significance of using an analytical model is because of its well-established mathematical formula and the availability of model evaluation tools. We have specified an automated transformation process that is performed in an efficient and scalable way through the use of model transformation rules to achieve model transformation. To analyze the correctness of the model transformation process, we have used temporal logic, specifically cTLA, to formalize the UML specification style. This, in turn, provides the opportunity for model validation. The motivation of applying cTLA is to take advantage of its well-established method to illustrate various forms of structures and actions by exploiting a variety of operators and techniques, which is wonderfully compatible with UML collaborations, activities, deployment, and state machine diagram. The framework is applied to artificial and real case studies to generate performance and performability results at the early stage of the system development process. The modeling process is supported by a set of tools, including Arctis and SHARPE with the incremental model checking facility. Arctis is used for specifying the system functional behavior. The evaluation of the performance and performability models generated by the framework is achieved using SHARPE.

Flow front advancement during composite processing: predictions from numerical filling simulation tools in comparison with real-world experiments

Liquid composite molding (LCM) techniques are innovative manufacturing processes for processing fiber reinforced polymer parts used e.g. for aerospace structures. Thereby the reinforcing material is placed in a mold and infiltrated with a low viscosity polymer matrix. Increasing production rates as well as part complexity lead to high production risks such as air inclusions or incomplete mold filling. Numerical mold filling simulations are promising tools enabling the composite manufacturing engineer to detect dry spots in the mold and find the optimal positions of the resin entry and ventilation system at an early process development stage. Today, different numerical models and software packages are available for modeling the flow through the reinforcing structure for visualization of the flow behavior. The goal of this study is the systematic comparison of two different software packages, namely PAM-RTM® and OpenFOAM. Both software tools are operated as they are commonly foreseen. Real world experiments under real process conditions are the basis for the assessment of the numerical predictions. The resin transfer molding (RTM) experiments are executed in a tool with a transparent upper mold half in order to see the flow front advancement. POLYM. COMPOS., 37:2782–2793, 2016. © 2015 Society of Plastics Engineers

Strategies for assessing and reducing inherent occupational health hazard and risk based on process information

Over the last few decades, the concept of inherent occupational health has gained increasing attention to reduce occupational hazards that may adversely impact workers’ health. In order to assess occupational hazards in the chemical process, different inherent occupational health assessment methods have been developed at the early stages of process development and design. The methods in the order of process information availability – ranging from the detailed piping and instrumentation diagrams to a simple sketch of process concepts are the: occupational health index (OHI), health quotient index (HQI) and inherent occupational health index (IOHI). This paper proposes systematic heuristic frameworks to assist process designers and engineers in assessing and reducing inherent occupational health hazards or risks based on process information availability. Strategies for reducing health hazards or risks in the OHI, HQI and IOHI methods based on inherently safer design (ISD) keywords of minimization, substitution, moderation and simplification are included in this study. It is worth mentioning that the proposed frameworks act as guidelines for design engineers in systematically selecting the appropriate index and methodology to assess and reduce health hazards/risks based on the availability of the process information. A case study is solved to illustrate the proposed framework.

Continuous Nanofiltration and Recycle of an Asymmetric Ketone Hydrogenation Catalyst

The continuous nanofiltration and recycle of a ruthenium diphosphine/diamine catalyst for the asymmetric hydrogenation of α-tetralone is demonstrated in a small scale flow system. Batch experiments show that the catalyst can be recycled under hydrogen pressure. Subsequent transient packed bed experiments serve to characterize the reaction and inform the design of the recycle experiments. The total internal volume of the resulting system is ∼50 mL, making this pilot useful for testing catalyst recyclability via nanofiltration during the early stages of process development. The high-pressure catalyst recycle system is run with an automatic control system to respond to membrane flux decline during the course of operation and enable long duration runs. In 24 h, we achieved a turnover number approaching 5000 for ruthenium diphosphine/diamine catalyst used in the asymmetric hydrogenation of α-tetralone, demonstrating significant reuse of the catalyst since the substrate-to-catalyst ratio in the reactor approach...

IJARCCE - Computer and Communication Engineering

The quality of any object oriented design is critical because it has a great influence on overall quality of finally delivered software product. Testability quantification early in the software development process is a criterion of crucial important to software development team. Testability has always been an indefinable concept its correct measurement, quantification or evaluation is a difficult task because of its potential factors. Testability analysis of object oriented software at an initial stage of software development process has been identified as a key factor for high quality product. A best suited object oriented design (OOD) properties and its associated metrics are helpful if applied in the early stage of development process .This paper describes an improved testability quantification framework using the identified set of potential factors, OOD properties and OOD metrics for software products at early phase, exclusively at design time. The proposed framework relates OOD properties to high level quality attributes/constructs using appropriate information to develop quality product and it may used to benchmark software products according to their key attribute. The objective of this research work to encourage researchers and developers to provide a framework to access and quantify software testability at early stage of development life cycle.

Novel shortcut estimation method for regeneration energy of amine solvents in an absorption-based carbon capture process.

Among various CO2 capture processes, the aqueous amine-based absorption process is considered the most promising for near-term deployment. However, the performance evaluation of newly developed solvents still requires complex and time-consuming procedures, such as pilot plant tests or the development of a rigorous simulator. Absence of accurate and simple calculation methods for the energy performance at an early stage of process development has lengthened and increased expense of the development of economically feasible CO2 capture processes. In this paper, a novel but simple method to reliably calculate the regeneration energy in a standard amine-based carbon capture process is proposed. Careful examination of stripper behaviors and exploitation of energy balance equations around the stripper allowed for calculation of the regeneration energy using only vapor-liquid equilibrium and caloric data. Reliability of the proposed method was confirmed by comparing to rigorous simulations for two well-known solvents, monoethanolamine (MEA) and piperazine (PZ). The proposed method can predict the regeneration energy at various operating conditions with greater simplicity, greater speed, and higher accuracy than those proposed in previous studies. This enables faster and more precise screening of various solvents and faster optimization of process variables and can eventually accelerate the development of economically deployable CO2 capture processes.

Tools for an enhanced solvent properties screening in the early stages of pharmaceutical process development

The objective of this research was the implementation of tools for the evaluation of solvents trough property screening in the early stages of process development. An important feature of the tools is that the implementation of indexes, scores, or weights is avoided. Information already available from the literature was stored in a database in order to turn raw data into decision making information. As a result, a solvent radar chart, a solvent representation table, and a solvent telescopying tool were developed in an ASP.NET application. The synthesis of Propranolol was used as study case in order to explore the selection of solvents in the early stages of process development. The replacement of diethyl ether was possible in the extraction step, while solvent choices were detected for potential telescoping for extraction and crystallisation steps. Solubility was found as a critical parameter in telescoping analysis. The methodology proposed enhanced the view towards a more holistic perspective and a more robust solvent screening process. As a consequence, the next steps into solvent evaluation and process development can be reduced.

Supercritical fluids and gas-expanded liquids as tunable media for multiphase catalytic reactions

Solvents play a vital role in multiphase catalysis. They are selected to perform several functions during liquid phase catalytic transformations such as solubilizing reactants, facilitating product/catalyst separation, increasing reaction rates, enhancing solubilities of gaseous reactants (such as O2, CO, H2) in the liquid phase, and providing heat capacity to effectively manage the heat of reaction. This review discusses such roles of conventional solvents in multiphase catalytic processes such as hydroformylation, carbonylation, hydrogenation and oxidation. For each of these chemistries, industrially relevant examples are presented, highlighting the advantages and limitations of the conventional solvents used therein. Further, it is shown how the pressure-tunable properties of supercritical fluids (SCFs) and gas-expanded liquids (GXLs) have been exploited in such systems to develop novel multiphase catalytic technology concepts. GXLs in particular provide advantages such as rate intensification, efficient feedstock utilization, enhanced process safety, waste minimization and reduced use of volatile organic solvents, all at relatively mild pressures and temperatures. Conventional reactors and reaction engineering tools that integrate phase behavior (for reactions and separations), catalytic kinetics and multiphase reactor modeling may be applied for the rational development of multiphase reactors using GXLs. Quantitative economic and environmental impact analyses during early stages of process development provide valuable research and process engineering guidance for developing practically viable GXL processes. The Rh catalyzed hydroformylation in CO2-expanded liquids and methyltrioxorhenium-based ethylene epoxidation are highlighted as exemplars of GXL-based technology concepts. Emerging feedstocks, such as plant-based biomass, shale gas and sequestered CO2, that require new catalytic conversion technologies to produce chemical intermediates, offer excellent opportunities for using tunable solvents.

Selection of Technical Reactor Equipment for Modular, Continuous Small-Scale Plants

Fast process development, flexible production and the utilization of advanced process conditions are the main goals of modular and continuous small-scale plants (MCSPs). A configurable layout of the modules and the use of predefined equipment enable a quick and reliable conceptual process development and scale-up of continuous processes. Therefore, a computer-assisted selection methodology was developed and is presented, which allows the quick selection of plug flow reactor equipment for homogeneous liquid phase reactions. It identifies a favorable technical apparatus and the configuration in the early stages of process development. This can lead to the effective planning and guiding of scale-up experiments and closes the gap between lab and process development.

Profiling and Characterization of Sialylated N-glycans by 2D-HPLC (HIAX/PGC) with Online Orbitrap MS/MS and Offline MSn

Glycosylation is a critical parameter used to evaluate protein quality and consistency. N-linked glycan profiling is fundamental to the support of biotherapeutic protein manufacturing from early stage process development through drug product commercialization. Sialylated glycans impact the serum half-life of receptor-Fc fusion proteins (RFPs), making their quality and consistency a concern during the production of fusion proteins. Here, we describe an analytical approach providing both quantitative profiling and in-depth mass spectrometry (MS)-based structural characterization of sialylated RFP N-glycans. Aiming to efficiently link routine comparability studies with detailed structural characterization, an integrated workflow was implemented employing fluorescence detection, online positive and negative ion tandem mass spectrometry (MS/MS), and offline static nanospray ionization-sequential mass spectrometry (NSI-MS(n)). For routine use, high-performance liquid chromatography profiling employs established fluorescence detection of 2-aminobenzoic acid derivatives (2AA) and hydrophilic interaction anion-exchange chromatography (HIAX) charge class separation. Further characterization of HIAX peak fractions is achieved by online (-) ion orbitrap MS/MS, offering the advantages of high mass accuracy and data-dependent MS/MS. As required, additional characterization uses porous graphitized carbon in the second chromatographic dimension to provide orthogonal (+) ion MS/MS spectra and buffer-free liquid chromatography peak eluants that are optimum for offline (+)/(-) NSI-MS(n) investigations to characterize low-abundance species and specific moieties including O-acetylation and sulfation.

Process development and optimization of fed-batch production processes for therapeutic proteins by CHO cells

Background In the biopharmaceutical industry, process development and optimization is key to produce high quality recombinant proteins at high yields. As technologies mature, pressure on cost and timelines becomes greater for delivering scalable and robust processes. Overall, process development should be viewed as a continuum from the early stages up to process validation. Here we outline a lean approach on upstream development during the initial phases to optimize yields while maintaining the desired product quality profiles. Early-stage process development was designed to lead to the establishment of a baseline process and to systematically include experiments with input parameters that have a high impact on performance and quality. At this stage, potential for pre-harvest titer and yield increases as well as product quality challenges were identified. Feed adjustments and systematic experiments with top, high, and medium impact parameters have then been performed to develop a robust and scalable process. This approach was applied to two early stage upstream processes.