104 research outputs found

    Metabolomics And The Role Of Metabolism In Stem Cell Bioprocessing

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    Stem cell bioprocesses require reproducibility, robustness and quality control of both the process and the product for wide clinical use1. The role of metabolism is critical in stem cell bioprocesses as it controls cellular processes (proliferation, apoptosis, reprogramming) but also influences gene regulation and cellular physiology by directly affecting epigenomic changes2. Metabolomics analysis of both intracellular (finger-printing) and extracellular (foot-printing) metabolites a) enables evaluation of “cellular state”, b) captures a holistic view (snapshot) of the cell culture physiology, and c) provides dynamic information culture needs that can be used for bioprocess optimisation. Examples of research conducted in our group highlight 1) that metabolic profiling was able to identify differences in human pluripotent cell physiology (hESCs and hiPSCs) after treatment with ROCK inhibitor, which control gene expression and protein expression was not sensitive enough to detect; 2) time-series metabolomics analysis of the osteogenic differentiation process of umbilical cord blood mesenchymal stem cells identified differences in the efficiency of two major osteoinductive agents (dexamethasone and BMP-2) demonstrating that dexamethasone-treated MSCs were metabolically close to human primary osteoblasts; 3) the development of a novel perfusion bioreactor for the culture of pluripotent stem cells (ESCs) that facilitates environmental homeostasis by maintaining sufficient levels of nutrients while preventing the accumulation of metabolic by-products over toxic levels ensuring ESC pluripotency. The above examples emphasise the importance of metabolomics in all stages of stem cell bioprocess by sensitive and effective monitoring, which can be used for robust bioprocess optimisation as well as bioprocess and product quality control – critical aspects of biomanufacturing for clinical applications

    Towards model-based bioprocess characterization: A mathematical model of cell cycle, metabolism and apoptosis of mAb-producing mammalian cells

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    The biologics industry is changing and all players seek competitiveness through process optimization aiming at satisfying the market demand providing a compliant protein in as short time as possible. As blockbuster drugs experience patent expiry, several biosimilars are coming market and competition becomes fiercer. Unlike classical experiments-based optimization, bioprocess modeling is a rational, economically efficient and reliable alternative to deliver an optimized bioprocess. The biological aspects of a bioreactor are diverse and include cells growing and cycling, other cells dying, nutrients being consumed and by-products accumulating, energy production and usage and therapeutic proteins being produced. The understanding of the biology involved is crucial to ensure quality. Quality by Design (QbD) aspects that can be optimized from the design stages include clone selection, medium formulation, feeding strategies and culture conditions. In this work, a mathematical model of mammalian cell cultures has been developed. It includes a detailed description of the viable cell population by segregating it according to the stage of the cell cycle (G0/G1, S and G2/M), transition from viable to early and late apoptotic stages. Apoptosis is monitored through gene expression profiles (caspases 3 and 8, bax and bcl-2) linked to the presence or absence of key nutrients. Indeed, the profiles of glucose and 19 amino acids are also captured by the model which allow for detailed information on energy production (ATP) which is essential to ensure viability and hence the delivery of a high-quality product. Please click Additional Files below to see the full abstract

    The Use of Alginate Hydrogels for the Culture of Mesenchymal Stem Cells (MSCs): In Vitro and In Vivo Paradigms

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    Alginate hydrogels have been widely used in stem cell cultures due to their biocompatibility, malleable nature, high water content, enhanced mass transport properties, and their functionalization with bioactive molecules providing cues that modulate cell proliferation and differentiation. Mesenchymal stem cells (MSCs) are extensively utilized in clinical cellular therapies because of their differentiation efficiency, their immunosuppressive properties, and them not being tumorigenic when implanted in vivo. MSCs are isolated from numerous fetal and adult tissues, suitable for both autologous and allogeneic applications. Consequently, alginate hydrogels/MSCs have been applied in vivo for the treatment of a wide variety of musculoskeletal, cardiac, neural, and endocrine disorders. This chapter will review the use of alginate hydrogels (physical properties and functionalization) for MSC culture in vitro (various culture systems) and the application of alginate/MSC implants (animal models and human applications) for cellular therapy purposes in vivo

    An energy-based modelling tool for culture medium design and biomanufacturing optimization

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    Demand for high-value biologics, a rapidly growing pipeline, and pressure from competition, time-to-market and regulators, necessitate novel biomanufacturing approaches, including Quality by Design (QbD) principles and Process Analytical Technologies (PAT), to facilitate accelerated, efficient and effective process development platforms that ensure consistent product quality and reduced lot-to-lot variability. Herein, QbD and PAT principles were incorporated within an innovative in vitro-in silico integrated framework for upstream process development (UPD). The central component of the UPD framework is a mathematical model that predicts dynamic nutrient uptake and average intracellular ATP content, based on biochemical reaction networks, to quantify and characterize energy metabolism and its adaptive response, metabolic shifts, to maintain ATP homeostasis. The accuracy and flexibility of the model depends on critical cell type/product/clone-specific parameters, which are experimentally estimated. The integrated in vitro-in silico platform and the model’s predictive capacity reduced burden, time and expense of experimentation resulting in optimal medium design compared to commercially available culture media (80% amino acid reduction) and a fed-batch feeding strategy that increased productivity by 129%. The framework represents a flexible and efficient tool that transforms, improves and accelerates conventional process development in biomanufacturing with wide applications, including stem cell-based therapies

    Advanced computational tools to enhance continuous monoclonal antibody production

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    Leading pharmaceutical companies invest high percentage of their revenue in the improvement of existing technologies used for the production of monoclonal antibodies (mAbs). Recently, there has been a paradigm shift towards the development of continuous/quasi-continuous purification operations, aiming to reduce capital and operational costs [1]. At the moment, however, there are no standardized methods and/or tools that can be used for global control and monitoring of integrated processes. Mathematical models and advanced computational tools can be the key for the development of robust, integrated processes, as they can provide valuable insight in the process dynamics and ensure optimal operation [2]. However, such processes are usually characterized by complex mathematical models and periodic operation profiles that result into computationally expensive solutions and challenge the development of global control methods and tools. In this work, we are presenting a novel approach for the development of advanced controllers towards the intensification of mAb production, considering the fed-batch culturing of GS-NS0 cells and the semi-continuous Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) process [3]. The controller development is realized via the application of a generic framework for the development of advanced control strategies (PAROC) [4] that involves: (i) development of a high-fidelity process model, (ii) approximation of the complex, process model, (iii) design of the multi-parametric controller, (iv) ‘closed-loop’, in-silico validation of the controller against the process model. The development of the control policies is based on multi-parametric Model Predictive Control (mp-MPC) policies that reduce the online, computational force of the controller by deriving the control inputs as a set of explicit functions of the system states and can be implemented on embedded devices [5]. One of the main advantages of the proposed framework is the ability to test the controllers ‘in-silico’, against the high-fidelity process model and evaluate their performance before operating them online. The results from this study indicate that optimal operation, under maximum purity and productivity yield can be ensured with the development of advanced computational tools. The control policies are applied both in the upstream and the downstream processing; yielding therefore a fertile ground towards the development of a global control strategy that can ensure continuous operation

    Key environmental stress biomarker candidates for the optimisation of chemotherapy treatment of leukaemia

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    The impact of fluctuations of environmental parameters such as oxygen and starvation on the evolution of leukaemia is analysed in the current review. These fluctuations may occur within a specific patient (in different organs) or across patients (individual cases of hypoglycaemia and hyperglycaemia). They can be experienced as stress stimuli by the cancerous population, leading to an alteration of cellular growth kinetics, metabolism and further resistance to chemotherapy. Therefore, it is of high importance to elucidate key mechanisms that affect the evolution of leukaemia under stress. Potential stress response mechanisms are discussed in this review. Moreover, appropriate cell biomarker candidates related to the environmental stress response and/or further resistance to chemotherapy are proposed. Quantification of these biomarkers can enable the combination of macroscopic kinetics with microscopic information, which is specific to individual patients and leads to the construction of detailed mathematical models for the optimisation of chemotherapy. Due to their nature, these models will be more accurate and precise (in comparison to available macroscopic/black box models) in the prediction of responses of individual patients to treatment, as they will incorporate microscopic genetic and/or metabolic information which is patient-specific.peer-reviewe

    Polyurethane scaffolds seeded with CD34<sup>+</sup> cells maintain early stem cells whilst also facilitating prolonged egress of haematopoietic progenitors

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    We describe a 3D erythroid culture system that utilises a porous polyurethane (PU) scaffold to mimic the compartmentalisation found in the bone marrow. PU scaffolds seeded with peripheral blood CD34+ cells exhibit a remarkable reproducibility of egress, with an increased output when directly compared to human bone scaffolds over 28 days. Immunofluorescence demonstrated the persistence of CD34+ cells within the scaffolds for the entirety of the culture. To characterise scaffold outputs, we designed a flow cytometry panel that utilises surface marker expression observed in standard 2D erythroid and megakaryocyte cultures. This showed that the egress population is comprised of haematopoietic progenitor cells (CD36+GPA−/low). Control cultures conducted in parallel but in the absence of a scaffold were also generally maintained for the longevity of the culture albeit with a higher level of cell death. The harvested scaffold egress can also be expanded and differentiated to the reticulocyte stage. In summary, PU scaffolds can behave as a subtractive compartmentalised culture system retaining and allowing maintenance of the seeded “CD34+ cell” population despite this population decreasing in amount as the culture progresses, whilst also facilitating egress of increasingly differentiated cells

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Pore Interconnectivity Analysis of Porous Three Dimensional Scaffolds of Poly (3-Hydroxybutyric Acid) (PHB) and Poly(3-Hydroxybutyric-co-3-Hydroxyvaleric Acid) (PHBV) Through Non-Invasive Color Staining Method

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    Polyhydroxyalkanoates (PHAs) has been investigated for more than eighty years. Ever since then, the scientists are kept on synthesizing and developing new polymers and application to suit human interests nowadays. The resourcefulness of PHAs has made them a good candidates for the study of their potential in a variety of areas from biomedical/medical fields to food, packaging, textile and household material. In medical field (specifically in tissue engineering application), producing a biocompatible 3-D scaffold with adaptable physical properties are essential. However, to the best of our knowledge, scaffolds from PHB and PHBV with thickness greater than 1 mm have not been produced yet. In this work, PHB and PHBV porous 3-D scaffolds with an improved thickness greater than 4 mm was fabricated using conventional method of solvent-casting particulate-leaching (SCPL). A preliminary assessment on the improved thickness 3-D scaffolds was carried out to examine its pore interconnectivity by using non-invasive color staining method. The vertical cross sections image of the stained scaffolds was analyzed by image analyzer software. This technique was considered simple, fast and cost effective method prior to the usage of super accurate analytical instruments (micro-computed tomography). The results showed that over 80% of the pores have been interconnected with the adjacent pores. Moreover, there was a good correlation between the predicted pore interconnectivity and porosity. These results indicated how well a simple technique can do by giving an overview of the internal morphology of a porous 3-D structure material
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