Stages Of Development Process Research Articles

Real-Time Adaptive Inline Acidification Enhances Continuous pH Control for Viral Inactivation.

Existing low pH viral inactivation methods for continuous downstream processing of biologics typically rely on predictive models to estimate the necessary pH adjustments. However, these methods are of limited use during the process development stage due to the dynamic nature of capture chromatography, where batch variations can alter the eluted protein titer. This study introduces an inline viral inactivation system (IVIS) that utilizes real-time adaptive control and inline sensor readings to precisely regulate the pH manipulation for inline acidification and continuous viral inactivation. The IVIS, which includes a coiled flow inversion reactor (CFIR), is integrated with a multicolumn capture chromatography system to demonstrate a fully continuous process from protein capture chromatography to inline pH manipulation. The system achieved precise inline pH manipulation within ±0.15 and a narrow residence time distribution of 13.5min with a relative width of 0.7. The introduction of real-time inline pH manipulation with the IVIS signifies a notable advancement in managing critical process parameters (CPPs) and ensuring consistent product quality across varied production environments for continuous downstream bioprocessing.

Synthetic Biology of Natural Products Engineering: Recent Advances Across the Discover-Design-Build-Test-Learn Cycle.

Advances in genome engineering and associated technologies have reinvigorated natural products research. Here we highlight the latest developments in the field across the discover-design-build-test-learn cycle of bioengineering, from recent progress in computational tools for AI-supported genome mining, enzyme and pathway engineering, and compound identification to novel host systems and new techniques for improving production levels, and place these trends in the context of responsible research and innovation, emphasizing the importance of anticipatory analysis at the early stages of process development.

A framework for early-stage sustainability assessment of innovation projects enabled by weighted sum multi-criteria decision analysis in the presence of uncertainty.

A two-level hierarchical framework for early-stage sustainability assessment (FESSA) amongst a set of alternatives applicable from the earliest stages of process or product development is introduced, and its use in combination with an improved method weighted-sum method multi-criteria decision analysis (WSM-MCDA) in the presence of uncertainty is presented through application to a case study based upon a real-world decision scenario from speciality polymer manufacture. The approach taken addresses the challenge faced by those responsible for innovation management in the manufacturing process industries to make simultaneously timely and rational decisions early in the innovation cycle when knowledge gaps and uncertainty about the options tend to be at their highest. The Computed Uncertainty Range Evaluations (CURE) WSM-MCDA method provides better discrimination than the existing Multiple Attribute Range Evaluations (MARE) method without the computational burden of generating heuristic outcome distributions via Monte-Carlo simulation.

Hybrid Modeling for On-Line Fermentation Optimization and Scale-Up: A Review

Modeling is a crucial tool in the biomanufacturing industry, namely in fermentation processes. This work discusses both mechanistic and data-driven models, each with unique benefits and application potential. It discusses semi-parametric hybrid modeling, a growing field that combines these two types of models for more accurate and easy result extrapolation. The characteristics and structure of such hybrid models will be examined. Moreover, its versatility will be highlighted, showing its usefulness in various stages of process development, including real-time monitoring and optimization. Scale-up remains one of the most relevant topics in fermentation processes, as it is important to have reproducible critical quality attributes, such as titer and yield, on larger scales. Furthermore, the process still relies on empirical correlations and iterative optimization. For these reasons, it is important to improve scale-up predictions, through e.g., the use of digital tools. Perspectives will be presented on the potential that hybrid modeling has by predicting performance across different process scales. This could provide more efficient and reliable biomanufacturing processes that require less resource consumption through experimentation.

A framework for the practical development of condition monitoring systems with application to the roller compactor

Implementing a condition-based maintenance strategy requires an effective condition monitoring (CM) system that can be complicated to develop and even harder to maintain. In this paper, we review the main complexities of developing condition monitoring systems and introduce a four-stage framework that can address some of these difficulties. The framework achieves this by first using process knowledge to create a representation of the process condition. This representation can be broken down into simpler modules, allowing existing monitoring systems to be mapped to their corresponding module. Data-driven models such as machine learning models could then be used to train the modules that do not have existing CM systems. Even though data-driven models tend to not perform well with limited data, which is commonly the case in the early stages of pharmaceutical process development, application of this framework to a pharmaceutical roller compaction unit shows that the machine learning models trained on the simpler modules can make accurate predictions with novel fault detection capabilities. This is attributed to the incorporation of process knowledge to distill the process signals to the most important ones vis-à-vis the faults under consideration. Furthermore, the framework allows the holistic integration of these modular CM systems, which further extend their individual capabilities by maintaining process visibility during sensor maintenance.

A pneumonia caused by Pneumocystis jiroveci: highresolution computed tomography features at stages of process development

Pneumocystis jiroveci pneumonia is a common opportunistic infection affecting immunosuppressed patients. High-resolution CT may be indicated for evaluation of immunosuppressed patients with suspected pneumonia and normal chest radiographic findings. The most common highresolution CT finding of Pneumocystis jiroveci pneumonia is diffuse ground-glass opacity. Computed tomographic features of pneumonia caused by Pneumocystis jiroveci depend on the stage of the process. High-resolution computed tomography should be used

Prediction models for the flux decay profile and initial flux of microfiltration for therapeutic proteins.

Microfiltration (MF) is an essential step during biopharmaceutical manufacturing. However, unexpected flux decay can occur. Although the flux decay profile and initial flux are important factors determining MF filterability, predicting them accurately is challenging, as the root cause of unexpected flux decay remains elusive. In this study, the methodology for developing a prediction model of flux decay profiles was established. First, the filtration profiles of different monodisperse polystyrene latex and silica beads of various sizes were evaluated. These results revealed that the size and surface electrostatic properties of the beads affect the flux decay profile. Taking the size and surface electrostatic properties of protein aggregates into account, we constructed a predictive model using model bead filtration profiles. We showed that this methodology was applicable to two different MF filters to predict the flux decay profile of therapeutic proteins. Because our proposed prediction model is based on normalized flux, the initial flux is required to predict the overall filtration profile. Then, we applied the Hagen-Poiseuille equation using sample viscosity values to estimate the initial flux. The developed prediction models can be used for effective MF scale-up assessment during the early stages of process development.

Predicting protein retention in ion-exchange chromatography using an open source QSPR workflow.

Protein-based biopharmaceuticals require high purity before final formulation to ensure product safety, making process development time consuming. Implementation of computational approaches at the initial stages of process development offers a significant reduction in development efforts. By preselecting process conditions, experimental screening can be limited to only a subset. One such computational selection approach is the application of Quantitative Structure Property Relationship (QSPR) models that describe the properties exploited during purification. This work presents a novel open-source Python tool capable of extracting a range of features from protein 3D models on a local computer allowing total transparency of the calculations. As open-source tool, it also impacts initial investments in constructing a QSPR workflow for protein property prediction for third parties, making it widely applicable within the field of bioprocess development. The focus of current calculated molecular features is projection onto the protein surface by constructing surface grid representations. Linear regression models were trained with the calculated features to predict chromatographic retention times/volumes. Model validation shows a high accuracy for anion and cation exchange chromatography data (cross-validated R2 of 0.87 and 0.95). Hence, these models demonstrate the potential of the use of QSPR to accelerate process design.

Mimicking CHO large-scale effects in the single multicompartment bioreactor: A new approach to access scale-up behavior.

During the scale-up of biopharmaceutical production processes, insufficiently predictable performance losses may occur alongside gradients and heterogeneities. To overcome such performance losses, tools are required to explain, predict, and ultimately prohibit inconsistencies between laboratory and commercial scale. In this work, we performed CHO fed-batch cultivations in the single multicompartment bioreactor (SMCB), a new scale-down reactor system that offers new access to study large-scale heterogeneities in mammalian cell cultures. At volumetric power inputs of 20.4-1.5 W m-3, large-scale characteristics like long mixing times and dissolved oxygen (DO) heterogeneities were mimicked in the SMCB. Compared to a reference bioreactor (REFB) set-up, the conditions in the SMCB provoked an increase in lactate accumulation of up to 87%, an increased glucose uptake, and reduced viable cell concentrations in the stationary phase. All are characteristic for large-scale performance. The unique possibility to distinguish between the effects of changing power inputs and observed heterogeneities provided new insights into the potential reasons for altered product quality attributes. Apparently, the degree of galactosylation in the evaluated glycan patterns changed primarily due to the different power inputs rather than the provoked heterogeneities. The SMCB system could serve as a potent tool to provide new insights into scale-up behavior and to predict cell line-specific drawbacks at an early stage of process development.

СТРАТЕГІЧНЕ УПРАВЛІННЯ ІННОВАЦІЙНІСТЮ БІЗНЕС-ПРОЦЕСІВ ПІДПРИЄМСТВА

The article examines and summarizes the concepts and basics of enterprise business process management. The effective functioning of the enterprise depends on the implementation of a complex of business processes, their integrity and consistency in business processes. The details of their strategic management are taken into account. The purpose of the article is to research and establish the peculiarities of the formation and implementation of strategic management of business processes in the conditions of the development of the innovative orientation of enterprises. The stages of business process development are considered in detail. Enterprise strategy depends on strategic innovation management, which is the key to achieving competitive advantage in a complex and competitive market. There are questions about the need to develop a strategic model for managing innovative development, which will contribute to stimulating economic activity, increasing competitiveness, and motivating the introduction of innovations into business processes. In the modern business environment, the technology of production activities determines the business processes that make up an innovative enterprise, which is the result of the combination and optimization of various business processes. Innovative elements are crucial to creating and maintaining a financially stable business policy. For the effective management of business processes in the organization, it is extremely important to create a management system that allows evaluating strategic goals and determining the effectiveness of all business processes in achieving these goals. A management tool is to create and use metrics that measure how well business processes are performing, covering all aspects of operations. Innovation is related to the concept of sustainable development, and it is appropriate for companies to constantly monitor and respond to changes and ensure an acceptable level of risk, so that companies can combine their existing resources and capabilities to use them as efficiently as possible. By improving business processes, companies can gain a competitive advantage and fully utilize their resources. Therefore, the issue of its strategic management is gaining more and more importance.

Application of PAT Probes in Aluminum Phosphate Adjuvant Manufacturing.

This study is focused on monitoring process parameters and quality attributes of aluminum phosphate (AlPO4) using multiple in-line probes incorporated into an industrial-scale adjuvant suspension manufacturing unit. The manufacturing of aluminum adjuvant suspension was monitored at manufacturing scale using conductivity, turbidity, infrared, and particle sizing and count probes to follow the continuous evolution of particle formation and size distribution, and the reaction kinetics during the synthesis of AlPO4. The data showed that AlPO4 forms large particles at the early stages of mixing, followed by a decrease in size and then stabilization towards the later stages of mixing and pH adjustment. The results provided a complementary view of process events and assisted in optimizing several parameters, e.g., flow rate of reactants AlCl3 and Na3PO4 solutions, mixing rate, pH, and conductivity of AlPO4, as well as adjuvant quality attribute such as particle size, thus streamlining and shortening the process development stage. The results of this study showed the usefulness of the in-line probes to automate continuous assessment of AlPO4 batch-to-batch consistency during in-house adjuvant production at the industrial scale.

Possibility Assessment of Automatic Formation of Technological Processes in Small Batch Production

The work is devoted to urgent problem solution of lack of convenient tools with functional capabilities of the system of route technological process automated design, adapted to small-scale production. The estimation of potential possibility of automatic small-scale production formation by means of estimation of efficiency and expediency technological processes of automation of key stages of design of production technological preparation, such as equipment selection, selection of cutting modes, workpiece, cutting and measuring tools and tooling selection is given. The key stages of technological process development are considered and characterized, such as selection of technological bases, type of workpiece and equipment, formation of route technological process, calculation of cutting modes, selection of allowances and so on. The paper shows both the relevance and necessity of analyzing approaches to automation and their correct adaptation to production needs to achieve maximum efficiency and resource savings for small batch production, and the high relevance for small-batch production of the automatic formation of route technological processes. At the same time, the paper shows the lack of automated systems adapted to the specifics of small-batch production. The existing approaches to the formation of stages are analyzed, as well as the possible methods of automation of stages and the existing limitations of these methods are considered, the efficiency of the considered approaches is evaluated. The methods of automation of separate stages of technological preparation of production are analyzed and the efficiency of the considered approaches is evaluated. The original concept of solving the problem of automation for small-scale production by using a combination of a limited number of standard solutions, represented as a set of technological parameters or knowledge base, with individual solutions, adapted to the specifics of enterprises and industry, is proposed and the potential effectiveness of this approach is shown.

A comprehensive assessment of the applicability of RoboColumn as a chromatography scale-down model for use in biopharmaceutical process validation

High-throughput process development has become a standard practice in the biopharmaceutical industry to enable time, cost, and material savings. In downstream biopharmaceutical process development, miniaturized, parallelized chromatography columns, known as RoboColumn, have become the standard for process development, as RoboColumn have shown generally comparable performance to bench and manufacturing scale columns. However, RoboColumn have yet to be widely implemented in process validation and characterization, where many multifactor experiments are typically executed, and there is a strong value proposition for performing high-throughput experiments. The hesitancy to utilize RoboColumn in process validation arises from scale differences that result in exacerbated peak broadening at RoboColumn scale relative to traditional bench or manufacturing scales. Thus, to support reliable application of RoboColumn in process validation, the present study provides a comprehensive investigation to understand how scale differences affect chromatographic performance by comparing RoboColumn, bench, and manufacturing scales using seven different production processes covering three different antibody formats, five different resin types, and three chromatographic modes of operation. RoboColumn chromatographic performance was compared at target and off-target conditions to emulate scale-down model qualification and multifactor studies, respectively. RoboColumn demonstrated good comparability at both target and off-target process conditions. To further demonstrate an understanding of comparability, a study was performed to show a rare case in which product quality offsets may occur as a result RoboColumn scale differences. By showing scale comparability and an understanding of potential offsets, this work demonstrates that RoboColumn can be used in any stage of process development, including process validation and characterization.

Development of a chemically defined medium for Paenibacillus polymyxa by parallel online monitoring of the respiration activity in microtiter plates

BackgroundOne critical parameter in microbial cultivations is the composition of the cultivation medium. Nowadays, the application of chemically defined media increases, due to a more defined and reproducible fermentation performance than in complex media. In order, to improve cost-effectiveness of fermentation processes using chemically defined media, the media should not contain nutrients in large excess. Additionally, to obtain high product yields, the nutrient concentrations should not be limiting. Therefore, efficient medium optimization techniques are required which adapt medium compositions to the specific nutrient requirements of microorganisms.ResultsSince most Paenibacillus cultivation protocols so far described in literature are based on complex ingredients, in this study, a chemically defined medium for an industrially relevant Paenibacillus polymyxa strain was developed. A recently reported method, which combines a systematic experimental procedure in combination with online monitoring of the respiration activity, was applied and extended to identify growth limitations for Paenibacillus polymyxa. All cultivations were performed in microtiter plates. By systematically increasing the concentrations of different nutrient groups, nicotinic acid was identified as a growth-limiting component. Additionally, an insufficient buffer capacity was observed. After optimizing the growth in the chemically defined medium, the medium components were systematically reduced to contain only nutrients relevant for growth. Vitamins were reduced to nicotinic acid and biotin, and amino acids to methionine, histidine, proline, arginine, and glutamate. Nucleobases/-sides could be completely left out of the medium. Finally, the cultivation in the reduced medium was reproduced in a laboratory fermenter.ConclusionIn this study, a reliable and time-efficient high-throughput methodology was extended to investigate limitations in chemically defined media. The interpretation of online measured respiration activities agreed well with the growth performance of samples measured in parallel via offline analyses. Furthermore, the cultivation in microtiter plates was validated in a laboratory fermenter. The results underline the benefits of online monitoring of the respiration activity already in the early stages of process development, to avoid limitations of medium components, oxygen limitation and pH inhibition during the scale-up.

Моделирование напряженного состояния концевой радиусной фрезы при формообразовании сложной поверхности

The paper presents results of simulating stress state in the cutting edge zone of the radial end milling cutter with the given tool orientation along the transverse angle. Simulation involved calculating the cutting forces in the ABAQUS program, converting them into loads acting on the tool surface, determining the contact zone of the tool front surface with chips based on the cutting theory and calculating stresses with the uniform load distribution in the considered tool section. Results of the preliminary calculations are provided. Distribution curves of the equivalent, normal and shear stresses in the cutting edge zone of the radial end milling cutter obtained using hardware of the ANSYS finite element analysis system were constructed. Simulation results allow further research to study the tool orientation and the cutting conditions influence on the tool stress state in shaping the complex surfaces. Determination of the machined surface zones, where the calculated stress values exceed the critical values, using the model makes it possible already at the initial stage of the technological process development to exclude destruction of the tool cutting edges and to achieve maximum productivity in shaping the complex surfaces.

PreHAZOP: Graph‐Based Safety Analysis for Early Integration into Automated Engineering Workflows

AbstractThe increasing digitalization and standardization within the process industry lead to a high availability of digital, machine‐readable processes and plant descriptions. In particular, the publication of the DEXPI standard provides a digital representation of plant topologies including a complete description of all specifications. In early planning phases, this can be used as the basis for an automated safety assessment since digital availability significantly simplifies accessibility for smart search algorithms. This paper presents the preHAZOP search algorithm, which was developed to analyze P&IDs in DEXPI format and to detect safety‐critical deviations regarding their risk according to a classical HAZOP analysis. The preHAZOP is of particular interest in early process development stages and can be easily integrated into modern, digital engineering workflows.

Development of the Extremely Poor Students Selection Process for Receiving the Teacher Production Project Scholarship for Protected Schools in Thailand

This study aimed to develop a systematic process for selecting scholarship recipients to participate in the Krurakthin project at Kalasin University. To gather insights into the selection process, stakeholders from five distinct groups, including the director of the educational service area, the director of the destination school, community leaders, lecturers, and scholarship recipients, were interviewed. This study represents the preliminary stage of analysis and process development. The research instruments consisted of (1) an opinion interview form on the scholarship recipient selection process and (2) a form for evaluating the appropriateness of the selection procedure for scholarship recipients. The data were analyzed statistically by comparing the means and standard deviations. The research findings prompted the development of a procedure for selecting scholarship recipients. Regarding the appropriateness of the scholarship recipient selection process, it was found that the appropriateness of the advertisement process was scored at 4.55 ± 0.50 points, which was at the highest level. The appropriateness of the finding process was scored at 4.73 ± 0.45 points, which was at the highest level. The appropriateness of the screening process was scored at 4.58 ± 0.50 points, which was at the highest level. Additionally, the appropriateness of the selection process was 4.54 ± 0.64 points, which was at the highest level. Each process had a total appropriateness score of 4.61 + 0.32 points, which is considered to be at the highest level. These results led to the production of a manual for choosing scholarship candidates to enroll in the Krurakthin project at Kalasin University and to prepare for the field test of the selection process of 4th-year Krurakthin students.

Efficient and metal Free synthesis of 2,3-disubstituted pyridopyrimidinones via ketenimine intermediates

A highly efficient synthesis has been developed for the direct access of 2,3-disubstitued 4H-pyrido[1,2-a]pyrimidin-4-ones from N-pyridoketenimine precursors. The ketenimine intermediates are demonstrated to react efficiently with N-, S-, O- and C-nucleophiles, and provide the corresponding disubstituted pyridopyrimidinone products in good yields. This one-pot method is operationally simple and avoids the use of transition metals, enabling rapid assembly of this type of structural motif for SAR studies as well as late stage process development.

An inherently safer design approach based on process safety time for batch chemical reaction processes

The economic attractiveness of an industrial process depends a large extent on its safe and reliable operation. The inherently safer design can help reduce the potential hazard on a fundamental level and eliminate escalation at the early stage of process development. In this work, an inherently safer design method for batch chemical reactors is proposed, which maximizes the yield of target product while minimizes Dow’s fire and explosion index. Process safety time is introduced as criterion to respond to the thermal runaway risk risen by unexpected failures. Finally, two examples for specific reaction systems with given kinetics are performed to demonstrate the feasibility and validity of the proposed method. The results indicate that the product yield optimized with the proposed method is significantly higher than that obtained from literature approach involving temperature limit or divergence criterion under the same PST. With the same yield, the PST optimized with the proposed method is longer.

Is There a Difference in Innovation Performance Depending on the Investment in Each Stage of Development Process? Evidence From Medical Device Industry

Is There a Difference in Innovation Performance Depending on the Investment in Each Stage of Development Process? Evidence From Medical Device Industry