The design basis for the integrated and continuous biomanufacturing framework.
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ABSTRACT:
SUBMITTER: Coffman J
PROVIDER: S-EPMC8453788 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cell line development is a critical step in the establishment of a biopharmaceutical manufacturing process. Current protocols rely on random transgene integration and amplification. Due to considerable variability in transgene integration profiles, this workflow results in laborious screening campaigns before stable producers can be identified. Alternative approaches for transgene dosage increase and integration are therefore highly desirable. In this study, we present a novel strategy for the rapid design, construction, and genomic integration of engineered multiple-copy gene constructs consisting of up to 10 gene expression cassettes. Key to this strategy is the diversification, at the sequence level, of the individual gene cassettes without altering their protein products. We show a computational workflow for coding and regulatory sequence diversification and optimization followed by experimental assembly of up to nine gene copies and a sentinel reporter on a contiguous scaffold. Transient transfections in CHO cells indicates that protein expression increases with the gene copy number on the scaffold. Further, we stably integrate these cassettes into a pre-validated genomic locus. Altogether, our findings point to the feasibility of engineering a fully mapped multi-copy recombinant protein 'production island' in a mammalian cell line with greatly reduced screening effort, improved stability, and predictable product titers.
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Project description:Tuberculosis (TB) is a highly contagious disease that mostly affects the lungs and is caused by a bacterial pathogen, Mycobacterium tuberculosis. The associated mortality rate of TB is much higher compared to any other disease and the situation is more worrisome by the rapid emergence of drug resistant strains. Bacillus Calmette-Guerin (BCG) is the only licensed attenuated vaccine available for use in humans however, many countries have stopped its use as it fails to confer protective immunity. Therefore, urgent efforts are required to identify new and safe vaccine candidates that are not only provide high immune protection but also have broad spectrum applicability. Considering this, herein, I performed an extensive computational vaccine analysis to investigate 200 complete sequenced genomes of M. tuberculosis to identify core vaccine candidates that harbor safe, antigenic, non-toxic, and non-allergic epitopes. To overcome literature reported limitations of epitope-based vaccines, I carried out additional analysis by designing a multi-epitopes vaccine to achieve maximum protective immunity as well as to make experimental follow up studies easy by selecting a vaccine that can be easily analyzed because of its favorable physiochemical profile. Based on these analyses, I identified two potential vaccine proteins that fulfill all required vaccine properties. These two vaccine proteins are diacylglycerol acyltransferase and ESAT-6-like protein. Epitopes: DSGGYNANS from diacylglycerol acyltransferase and AGVQYSRAD, ADEEQQQAL, and VSRADEEQQ from ESAT-6-like protein were found to cover all necessary parameters and thus used in a multi-epitope vaccine construct. The designed vaccine is depicting a high binding affinity for different immune receptors and shows stable dynamics and rigorous van der Waals and electrostatic binding energies. The vaccine also simulates profound primary, secondary, tertiary immunoglobulin production as well as high interleukins and interferons count. In summary, the designed vaccine is ideal to be evaluated experimentally to decipher its real biological efficacy in controlling drug resistant infections of M. tuberculosis.
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Project description:Ensuring consistent high yields and product quality are key challenges in biomanufacturing. Even minor deviations in critical process parameters (CPPs) such as media and feed compositions can significantly affect product critical quality attributes (CQAs). To identify CPPs and their interdependencies with product yield and CQAs, design of experiments, and multivariate statistical approaches are typically used in industry. Although these models can predict the effect of CPPs on product yield, there is room to improve CQA prediction performance by capturing the complex relationships in high-dimensional data. In this regard, machine learning (ML) approaches offer immense potential in handling non-linear datasets and thus are able to identify new CPPs that could effectively predict the CQAs. ML techniques can also be synergized with mechanistic models as a 'hybrid ML' or 'white box ML' to identify how CPPs affect the product yield and quality mechanistically, thus enabling rational design and control of the bioprocess. In this review, we describe the role of statistical modeling in Quality by Design (QbD) for biomanufacturing, and provide a generic outline on how relevant ML can be used to meaningfully analyze bioprocessing datasets. We then offer our perspectives on how relevant use of ML can accelerate the implementation of systematic QbD within the biopharma 4.0 paradigm.
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Project description:The development of a commercial fusion power plant presents a unique set of challenges associated with the complexity of the systems, the integration of novel technologies, the likely diversity and distribution of the organizations involved, and the scale of resources required. These challenges are reviewed and compared to those for other complex engineering systems. A framework for creating a digital environment that integrates research, test, design and operational data is discussed and is based on combining the integrated nuclear digital environment (INDE), proposed recently for nuclear fission power plants, with the hierarchical pyramid of test and simulation used in the aerospace industry. The framework offers the opportunity to plan modelling strategies that allow large design domains to be explored prior to optimizing a detailed design for construction; and in this context, the relationship between measurements and predictions are explored. The use of the framework to guide the socio-technical activity associated with a distributed and collaborative design process is discussed together with its potential benefits and the technology gaps that need to be addressed in order to realize them. These benefits include shorter development times, reduced costs and improvements in credibility, operability, reliability and safety.
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Project description:BackgroundeHealth and telehealth play a crucial role in assisting older adults who visit hospitals frequently or who live in nursing homes and can benefit from staying at home while being cared for. Adapting to new technologies can be difficult for older people. Thus, to better apply these technologies to older adults' lives, many studies have analyzed the acceptance factors for this particular population. However, there is not yet a consensual framework that can be used in further development and to search for solutions.ObjectiveThis paper aims to present an integrated acceptance framework (IAF) for older users' acceptance of eHealth based on 43 studies selected through a systematic review.MethodsWe conducted a 4-step study. First, through a systematic review in the field of eHealth from 2010 to 2020, the acceptance factors and basic data for analysis were extracted. Second, we conducted a thematic analysis to group the factors into themes to propose an integrated framework for acceptance. Third, we defined a metric to evaluate the impact of the factors addressed in the studies. Finally, the differences among the important IAF factors were analyzed according to the participants' health conditions, verification time, and year.ResultsThrough a systematic review, 731 studies were found in 5 major databases, resulting in 43 (5.9%) selected studies using the PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) methodology. First, the research methods and acceptance factors for eHealth were compared and analyzed, extracting a total of 105 acceptance factors, which were grouped later, resulting in an IAF. A total of 5 dimensions (ie, personal, user-technology relational, technological, service-related, and environmental) emerged, with a total of 23 factors. In addition, we assessed the quality of evidence and then conducted a stratification analysis to reveal the more appropriate factors depending on the health condition and assessment time. Finally, we assessed the factors and dimensions that have recently become more important.ConclusionsThe result of this investigation is a framework for conducting research on eHealth acceptance. To elaborately analyze the impact of the factors of the proposed framework, the criteria for evaluating the evidence from the studies that have the extracted factors are presented. Through this process, the impact of each factor in the IAF has been presented, in addition to the framework proposal. Moreover, a meta-analysis of the current status of research is presented, highlighting the areas where specific measures are needed to facilitate eHealth acceptance.
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Project description:Continuous cultivation with Escherichia coli has several benefits compared to classical fed-batch cultivation. The economic benefits would be a stable process, which leads to time independent quality of the product, and hence ease the downstream process. However, continuous biomanufacturing with E. coli is known to exhibit a drop of productivity after about 4-5 days of cultivation depending on dilution rate. These cultivations are generally performed on glucose, being the favorite carbon source for E. coli and used in combination with isopropyl β-D-1 thiogalactopyranoside (IPTG) for induction. In recent works, harsh induction with IPTG was changed to softer induction using lactose for T7-based plasmids, with the result of reducing the metabolic stress and tunability of productivity. These mixed feed systems based on glucose and lactose result in high amounts of correctly folded protein. In this study we used different mixed feed systems with glucose/lactose and glycerol/lactose to investigate productivity of E. coli based chemostats. We tested different strains producing three model proteins, with the final aim of a stable long-time protein expression. While glucose fed chemostats showed the well-known drop in productivity after a certain process time, glycerol fed cultivations recovered productivity after about 150 h of induction, which corresponds to around 30 generation times. We want to further highlight that the cellular response upon galactose utilization in E. coli BL21(DE3), might be causing fluctuating productivity, as galactose is referred to be a weak inducer. This "Lazarus" phenomenon has not been described in literature before and may enable a stabilization of continuous cultivation with E. coli using different carbon sources.
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