Publications of Liesbet Geris
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See detailMulti-objective optimization of cost-efficient neotissue growth inside 3D scaffolds using evolutionary algorithms
Mehrian, Mohammad ULiege; olofsson, Simon; Misener, Ruth et al

Scientific conference (2018, March 26)

Tissue engineering is a fast progressing domain where solutions are provided for organ failure or tissue damage. Computer models can facilitate the design of optimal production process conditions leading ... [more ▼]

Tissue engineering is a fast progressing domain where solutions are provided for organ failure or tissue damage. Computer models can facilitate the design of optimal production process conditions leading to robust and economically viable products. We developed a computational model describing the neotissue growth (cells + their ECM) inside 3D scaffolds in a perfusion bioreactor. Here we apply multi-objective optimization (MOO) to maximize neotissue growth whilst minimizing the cost coming from medium refreshment and associated labor. [less ▲]

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See detailComputational modelling of human mesenchymal stem cell proliferation and extra cellular matrix production in 3D porous scaffolds in a perfusion bioreactor
Mehrian, Mohammad ULiege; Papantoniou, Ioannis; Lambrechts, Toon et al

Scientific conference (2018, March 26)

3D porous scaffolds are frequently used in tissue engineering (TE) applications in combination with bioreactor systems because of their ability to induce reproducible culture conditions that can control ... [more ▼]

3D porous scaffolds are frequently used in tissue engineering (TE) applications in combination with bioreactor systems because of their ability to induce reproducible culture conditions that can control specific cell behavior such as proliferation and extracellular matrix (ECM) production. A computational model describing neotissue growth inside 3D scaffolds in a perfusion bioreactor was developed, with neotissue being considered the combination of cells and their extra cellular matrix. In the model, the speed of neotissue growth depends on the flow-induced shear stress, curvature and the local concentrations of oxygen, glucose and lactate. The goal of this study is to make a distinction between the cell and the ECM fraction within the neotissue in the model to allow for a more detailed validation and optimization of the process. [less ▲]

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See detailMaximizing neotissue growth kinetics in a perfusion bioreactor: An in silico strategy using model reduction and Bayesian optimization
Mehrian, Mohammad ULiege; Guyot, Y.; Papantoniou, I. et al

in Biotechnology and Bioengineering (2017)

In regenerative medicine, computer models describing bioreactor processes can assist in designing optimal process conditions leading to robust and economically viable products. In this study, we started ... [more ▼]

In regenerative medicine, computer models describing bioreactor processes can assist in designing optimal process conditions leading to robust and economically viable products. In this study, we started from a (3D) mechanistic model describing the growth of neotissue, comprised of cells, and extracellular matrix, in a perfusion bioreactor set-up influenced by the scaffold geometry, flow-induced shear stress, and a number of metabolic factors. Subsequently, we applied model reduction by reformulating the problem from a set of partial differential equations into a set of ordinary differential equations. Comparing the reduced model results to the mechanistic model results and to dedicated experimental results assesses the reduction step quality. The obtained homogenized model is 105 fold faster than the 3D version, allowing the application of rigorous optimization techniques. Bayesian optimization was applied to find the medium refreshment regime in terms of frequency and percentage of medium replaced that would maximize neotissue growth kinetics during 21 days of culture. The simulation results indicated that maximum neotissue growth will occur for a high frequency and medium replacement percentage, a finding that is corroborated by reports in the literature. This study demonstrates an in silico strategy for bioprocess optimization paying particular attention to the reduction of the associated computational cost. © 2017 Wiley Periodicals, Inc. [less ▲]

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See detailBayesian Multi-Objective Optimisation of Neotissue Growth in a Perfusion Bioreactor Set-up
olofsson, Simon; Mehrian, Mohammad ULiege; Geris, Liesbet ULiege et al

Scientific conference (2017, October 01)

We consider optimising bone neotissue growth in a 3D scaffold during dynamic perfusion bioreactor culture. The goal is to choose design variables by optimising two conflicting objectives: (i) maximising ... [more ▼]

We consider optimising bone neotissue growth in a 3D scaffold during dynamic perfusion bioreactor culture. The goal is to choose design variables by optimising two conflicting objectives: (i) maximising neotissue growth and (ii) minimising operating cost. Our contribution is a novel extension of Bayesian multi-objective optimisation to the case of one black-box (neotissue growth) and one analytical (operating cost) objective function, that helps determine, within a reasonable amount of time, what design variables best manage the trade-off between neotissue growth and operating cost. Our method is tested against and outperforms the most common approach in literature, genetic algorithms, and shows its important real-world applicability to problems that combine black-box models with easy-to-quantify objectives like cost. [less ▲]

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See detailModelling BMP-2 carrier device for bone tissue engineering application
Manhas, Varun ULiege; Carlier, Aurelie; Geris, Liesbet ULiege

Poster (2017, February 01)

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See detailMAXIMIZING NEOTISSUE GROWTH IN A PERFUSION BIOREACTOR USING BAYESIAN OPTIMIZATION
Mehrian, Mohammad ULiege; guyot, Yann; Papantoniou, Ioannis et al

Scientific conference (2017, February 01)

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See detailModel-Based Optimization of the Medium Refreshment Regime During Neotissue Growth in a Perfusion Bioreactor
Mehrian, Mohammad ULiege; guyot, Yann; Papantoniou, Ioannis et al

Scientific conference (2017, January 08)

Computational models are interesting tools to facilitate the translation from the laboratory to the patient. In regenerative medicine, computer models describing bioprocesses taking place in bioreactor ... [more ▼]

Computational models are interesting tools to facilitate the translation from the laboratory to the patient. In regenerative medicine, computer models describing bioprocesses taking place in bioreactor environment can assist in designing process conditions leading to robust and economically viable products. In this study we present a low-cost computational model describing the neotissue (cells + extracellular matrix) growth in a perfusion bioreactor set-up. The neotissue growth is influenced by the geometry of the scaffold, the flow-induced shear stress and a number of metabolic factors. After initial model validation, a Genetic Algorithm optimization technique is used to find the best medium refreshment regime (frequency and percentage of medium replaced) resulting in a maximal amount of neotissue being produced in the scaffold in a 28 days of culture period. [less ▲]

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See detailAN IN-SILICO MODEL OF BMP-2 CARRIER DEVICE FOR BONE TISSUE ENGINEERING APPLICATION
Manhas, Varun ULiege; Carlier, Aurelie; Geris, Liesbet ULiege

Poster (2016, November 25)

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See detailImproving Perfusion Bioreactor Yields by Using Particle Swarm Optimization
Mehrian, Mohammad ULiege; guyot, Yann; Papantoniou, Ioannis et al

Scientific conference (2016, November 25)

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See detailMathematical modelling of ectopic bone formation in bone morphogenetic (BMP) carrier device
Manhas, Varun ULiege; Carlier, Aurelie; Geris, Liesbet ULiege

Conference (2016, September 28)

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See detailSIMULATION AND ANALYSIS OF RECEPTOR DYNAMICS IN A BMP REGULATORY NETWORK
Germain, Morgan ULiege; Bolander, Johanna; Ji, Wei et al

Poster (2016, September)

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See detailComputational modelling of local calcium ions release from calcium phosphate-based scaffolds
Manhas, Varun ULiege; Guyot, Yann; Kerckhofs, Greet et al

in Biomechanics & Modeling in Mechanobiology (2016)

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See detailMathematical modelling of the degradation behaviour of biodegradable metals
Bajger, P; Ashbourn, JMA; Manhas, Varun ULiege et al

in Biomechanics & Modeling in Mechanobiology (2016)

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See detailInvestigating in vitro calcium dissolution using a mathematical model
Manhas, Varun ULiege; Guyot, Yann; Kerckhofs, Greet et al

Scientific conference (2016, March)

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See detailIn silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market.
Geris, Liesbet ULiege; Guyot, Y.; Schrooten, J. et al

in Interface focus (2016), 6(2), 20150105

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as ... [more ▼]

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design. [less ▲]

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See detailCoupling curvature-dependent and shear stress-stimulated neotissue growth in dynamic bioreactor cultures: a 3D computational model of a complete scaffold.
Guyot, Y.; Papantoniou, I.; Luyten, F. P. et al

in Biomechanics & Modeling in Mechanobiology (2016), 15(1), 169-80

The main challenge in tissue engineering consists in understanding and controlling the growth process of in vitro cultured neotissues toward obtaining functional tissues. Computational models can provide ... [more ▼]

The main challenge in tissue engineering consists in understanding and controlling the growth process of in vitro cultured neotissues toward obtaining functional tissues. Computational models can provide crucial information on appropriate bioreactor and scaffold design but also on the bioprocess environment and culture conditions. In this study, the development of a 3D model using the level set method to capture the growth of a microporous neotissue domain in a dynamic culture environment (perfusion bioreactor) was pursued. In our model, neotissue growth velocity was influenced by scaffold geometry as well as by flow- induced shear stresses. The neotissue was modeled as a homogenous porous medium with a given permeability, and the Brinkman equation was used to calculate the flow profile in both neotissue and void space. Neotissue growth was modeled until the scaffold void volume was filled, thus capturing already established experimental observations, in particular the differences between scaffold filling under different flow regimes. This tool is envisaged as a scaffold shape and bioprocess optimization tool with predictive capacities. It will allow controlling fluid flow during long-term culture, whereby neotissue growth alters flow patterns, in order to provide shear stress profiles and magnitudes across the whole scaffold volume influencing, in turn, the neotissue growth. [less ▲]

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See detailCombining microCT-based characterization with empirical modelling as a robust screening approach for the design of optimized CaP-containing scaffolds for progenitor cell-mediated bone formation.
Kerckhofs, G.; Chai, Y. C.; Luyten, F. P. et al

in Acta Biomaterialia (2016), 35

Biomaterials are a key ingredient to the success of bone tissue engineering (TE), which focuses on the healing of bone defects by combining scaffolds with cells and/or growth factors. Due to the widely ... [more ▼]

Biomaterials are a key ingredient to the success of bone tissue engineering (TE), which focuses on the healing of bone defects by combining scaffolds with cells and/or growth factors. Due to the widely variable material characteristics and patient-specificities, however, current bone TE strategies still suffer from low repeatability and lack of robustness, which hamper clinical translation. Hence, optimal TE construct (i.e. cells and scaffold) characteristics are still under debate. This study aimed to reduce the material-specific variability for cell-based construct design, avoiding trial-and-error, by combining microCT characterization and empirical modelling as an innovative and robust screening approach. Via microCT characterization we have built a quantitative construct library of morphological and compositional properties of six CE approved CaP-based scaffolds (CopiOs(R), BioOss, Integra Mozaik, chronOS Vivify, MBCP and ReproBone), and of their bone forming capacity and in vivo scaffold degradation when combined with human periosteal derived cells (hPDCs). The empirical model, based on the construct library, allowed identification of the construct characteristics driving optimized bone formation, i.e. (a) the percentage of beta-TCP and dibasic calcium phosphate, (b) the concavity of the CaP structure, (c) the average CaP structure thickness and (d) the seeded cell amount (taking into account the seeding efficiency). Additionally, the model allowed to quantitatively predict the bone forming response of different hPDC-CaP scaffold combinations, thus providing input for a more robust design of optimized constructs and avoiding trial-and error. This could improve and facilitate clinical translation. STATEMENT OF SIGNIFICANCE: Biomaterials that support regenerative processes are a key ingredient for successful bone tissue engineering (TE). However, the optimal scaffold structure is still under debate. In this study, we have provided a useful innovative approach for robust screening of potential biomaterials or constructs (i.e. scaffolds seeded with cells and/or growth factors) by combining microCT characterization with empirical modelling. This novel approach leads to a better insight in the scaffold parameters influencing progenitor cell-mediated bone formation. Additionally, it serves as input for more controlled and robust design of optimized CaP-containing bone TE scaffolds. Hence, this novel approach could improve and facilitate clinical translation. [less ▲]

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See detailThe combined mechanism of bone morphogenetic protein- and calcium phosphate-induced skeletal tissue formation by human periosteum derived cells.
Bolander, J.; Ji, W.; Geris, Liesbet ULiege et al

in European Cells and Materials (2016), 31

When combining osteogenic progenitor cells such as human periosteum derived cells (hPDCs) with osteoconductive biomaterials like calcium phosphate (CaP)-scaffolds, in vivo bone formation can be achieved ... [more ▼]

When combining osteogenic progenitor cells such as human periosteum derived cells (hPDCs) with osteoconductive biomaterials like calcium phosphate (CaP)-scaffolds, in vivo bone formation can be achieved. This process is dependent on the early activation of Bone morphogenetic protein (BMP)-signalling. However, the bone forming process is slow and routinely only a limited amount of bone and bone marrow is formed. Therefore, we hypothesised that a robust clinically relevant outcome could be achieved by adding more physiological levels of potent BMP-ligands to these cell- and CaP-based constructs. For this, hPDCs were characterised for their responsiveness to BMP-ligands upon in vitro 2D stimulation. BMP-2, -4, -6 and -9 robustly induced osteochondrogenic differentiation. Subsequently, these ligands were coated onto clinically approved CaP-scaffolds, BioOss(R) and CopiOs(R), followed by hPDC-seeding. Protein lysates and conditioned media were investigated for activation of BMP signalling pathways. Upon in vivo implantation, the most abundant bone formation was found in BMP-2 and BMP-6-coated scaffolds. Implanted cells actively contributed to the newly formed bone. Remnants of cartilage could be observed in BMP-coated CopiOs(R)-constructs. Computational analysis displayed that the type of BMP-ligand as well as the CaP-scaffold affects skeletal tissue formation, observed in a qualitative as well as quantitative manner. Furthermore, the in vitro mechanism appears to predict the in vivo outcome. This study presents further evidence for the potential of BMP-technology in the development of clinically relevant cell-based constructs for bone regenerative strategies. [less ▲]

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See detailEarly BMP, Wnt and Ca(2+)/PKC pathway activation predicts the bone forming capacity of periosteal cells in combination with calcium phosphates.
Bolander, Johanna; Chai, Yoke Chin; Geris, Liesbet ULiege et al

in Biomaterials (2016), 86

The development of osteoinductive calcium phosphate- (CaP) based biomaterials has, and continues to be, a major focus in the field of bone tissue engineering. However, limited insight into the ... [more ▼]

The development of osteoinductive calcium phosphate- (CaP) based biomaterials has, and continues to be, a major focus in the field of bone tissue engineering. However, limited insight into the spatiotemporal activation of signalling pathways has hampered the optimisation of in vivo bone formation and subsequent clinical translation. To gain further knowledge regarding the early molecular events governing bone tissue formation, we combined human periosteum derived progenitor cells with three types of clinically used CaP-scaffolds, to obtain constructs with a distinct range of bone forming capacity in vivo. Protein phosphorylation together with gene expression for key ligands and target genes were investigated 24 hours after cell seeding in vitro, and 3 and 12 days post ectopic implantation in nude mice. A computational modelling approach was used to deduce critical factors for bone formation 8 weeks post implantation. The combined Ca(2+)-mediated activation of BMP-, Wnt- and PKC signalling pathways 3 days post implantation were able to discriminate the bone forming from the non-bone forming constructs. Subsequently, a mathematical model able to predict in vivo bone formation with 96% accuracy was developed. This study illustrates the importance of defining and understanding CaP-activated signalling pathways that are required and sufficient for in vivo bone formation. Furthermore, we demonstrate the reliability of mathematical modelling as a tool to analyse and deduce key factors within an empirical data set and highlight its relevance to the translation of regenerative medicine strategies. [less ▲]

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