Yann Guyot

Coupling curvature-dependent and shear stress-stimulated neotissue growth in dynamic bioreactor cultures: a 3D computational model of a complete scaffold

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.

Spatial optimization in perfusion bioreactors improves bone tissue-engineered construct quality attributes

Perfusion bioreactors have shown great promise for tissue engineering applications providing a homogeneous and consistent distribution of nutrients and flow‐induced shear stresses throughout tissue‐engineered constructs. However, non‐uniform fluid‐flow profiles found in the perfusion chamber entrance region have been shown to affect tissue‐engineered construct quality characteristics during culture. In this study a whole perfusion and construct, three dimensional (3D) computational fluid dynamics approach was used in order to optimize a critical design parameter such as the location of the regular pore scaffolds within the perfusion bioreactor chamber. Computational studies were coupled to bioreactor experiments for a case‐study flow rate. Two cases were compared in the first instance seeded scaffolds were positioned immediately after the perfusion chamber inlet while a second group was positioned at the computationally determined optimum distance were a steady state flow profile had been reached. Experimental data showed that scaffold location affected significantly cell content and neo‐tissue distribution, as determined and quantified by contrast enhanced nanoCT, within the constructs both at 14 and 21 days of culture. However, gene expression level of osteopontin and osteocalcin was not affected by the scaffold location. This study demonstrates that the bioreactor chamber environment, incorporating a scaffold and its location within it, affects the flow patterns within the pores throughout the scaffold requiring therefore dedicated optimization that can lead to bone tissue engineered constructs with improved quality attributes. Biotechnol. Bioeng. 2014;111: 2560–2570.

In silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market.

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.

Immersed Boundary Models for Quantifying Flow-Induced Mechanical Stimuli on Stem Cells Seeded on 3D Scaffolds in Perfusion Bioreactors.

Perfusion bioreactors regulate flow conditions in order to provide cells with oxygen, nutrients and flow-associated mechanical stimuli. Locally, these flow conditions can vary depending on the scaffold geometry, cellular confluency and amount of extra cellular matrix deposition. In this study, a novel application of the immersed boundary method was introduced in order to represent a detailed deformable cell attached to a 3D scaffold inside a perfusion bioreactor and exposed to microscopic flow. The immersed boundary model permits the prediction of mechanical effects of the local flow conditions on the cell. Incorporating stiffness values measured with atomic force microscopy and micro-flow boundary conditions obtained from computational fluid dynamics simulations on the entire scaffold, we compared cell deformation, cortical tension, normal and shear pressure between different cell shapes and locations. We observed a large effect of the precise cell location on the local shear stress and we predicted flow-induced cortical tensions in the order of 5 pN/μm, at the lower end of the range reported in literature. The proposed method provides an interesting tool to study perfusion bioreactors processes down to the level of the individual cell’s micro-environment, which can further aid in the achievement of robust bioprocess control for regenerative medicine applications.

Maximizing neotissue growth kinetics in a perfusion bioreactor: An in silico strategy using model reduction and Bayesian optimization

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.

Computational modelling of local calcium ions release from calcium phosphate-based scaffolds

A variety of natural or synthetic calcium phosphate (CaP)-based scaffolds are currently produced for dental and orthopaedic applications. These scaffolds have been shown to stimulate bone formation due to their biocompatibility, osteoconductivity and osteoinductivity. The release of the

A computational model for cell/ECM growth on 3D surfaces using the level set method: a bone tissue engineering case study

\hbox {Ca}^{2+}

Model-Based Optimization of the Medium Refreshment Regime During Neotissue Growth in a Perfusion Bioreactor

Ca2+ ions from these scaffolds is of great interest in light of the aforementioned properties. It can depend on a number of biophysicochemical phenomena such as dissolution, diffusion and degradation, which in turn depend on specific scaffold characteristics such as composition and morphology. Achieving an optimal release profile can be challenging when relying on traditional experimental work alone. Mathematical modelling can complement experimentation. In this study, the in vitro dissolution behaviour of four CaP-based scaffold types was investigated experimentally. Subsequently, a mechanistic finite element method model based on biophysicochemical phenomena and specific scaffold characteristics was developed to predict the experimentally observed behaviour. Before the model could be used for local