Maarten Sonnaert

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.

Human periosteal-derived cell expansion in a perfusion bioreactor system: proliferation, differentiation and extracellular matrix formation

Perfusion bioreactor systems have shown to be a valuable tool for the in vitro development of three‐dimensional (3D) cell–carrier constructs. Their use for cell expansion, however, has been much less explored. Since maintenance of the initial cell phenotype is essential in this process, it is imperative to obtain insight into the bioreactor‐related variables determining cell fate. Therefore, this study investigated the influence of fluid flow‐induced shear stress on the proliferation, differentiation and matrix deposition of human periosteal‐derived cells in the absence of additional differentiation‐inducing stimuli; 120 000 cells were seeded on additive manufactured 3D Ti6Al4V scaffolds and cultured for up to 28 days at different flow rates in the range 0.04–6 ml/min. DNA measurements showed, on average, a three‐fold increase in cell content for all perfused conditions in comparison to static controls, whereas the magnitude of the flow rate did not have an influence. Contrast‐enhanced nanofocus X‐ray computed tomography showed substantial formation of an engineered neotissue in all perfused conditions, resulting in a filling (up to 70%) of the total internal void volume, and no flow rate‐dependent differences were observed. The expression of key osteogenic markers, such as RunX2, OCN, OPN and Col1, did not show any significant changes in comparison to static controls after 28 days of culture, with the exception of OSX at high flow rates. We therefore concluded that, in the absence of additional osteogenic stimuli, the investigated perfusion conditions increased cell proliferation but did not significantly enhance osteogenic differentiation, thus allowing for this process to be used for cell expansion. Copyright

Model-based cell number quantification using online single-oxygen sensor data for tissue engineering perfusion bioreactors †

Online and non‐invasive quantification of critical tissue engineering (TE) construct quality attributes in TE bioreactors is indispensable for the cost‐effective up‐scaling and automation of cellular construct manufacturing. However, appropriate monitoring techniques for cellular constructs in bioreactors are still lacking. This study presents a generic and robust approach to determine cell number and metabolic activity of cell‐based TE constructs in perfusion bioreactors based on single oxygen sensor data in dynamic perfusion conditions. A data‐based mechanistic modeling technique was used that is able to correlate the number of cells within the scaffold (R2 = 0.80) and the metabolic activity of the cells (R2 = 0.82) to the dynamics of the oxygen response to step changes in the perfusion rate. This generic non‐destructive measurement technique is effective for a large range of cells, from as low as 1.0 × 105 cells to potentially multiple millions of cells, and can open‐up new possibilities for effective bioprocess monitoring. Biotechnol. Bioeng. 2014;111: 1982–1992.

Bioreactor-Based Online Recovery of Human Progenitor Cells with Uncompromised Regenerative Potential: A Bone Tissue Engineering Perspective.

The use of a 3D perfusion culture environment for stem cell expansion has been shown to be beneficial for maintenance of the original cell functionality but due to several system inherent characteristics such as the presence of extracellular matrix, the continued development and implementation of 3D perfusion bioreactor technologies is hampered. Therefore, this study developed a methodology for harvesting a progenitor cell population from a 3D open porous culture surface after expansion in a perfusion bioreactor and performed a functional characterization of the expanded cells. An initial screening showed collagenase to be the most interesting reagent to release the cells from the 3D culture surface as it resulted in high yields without compromising cell viability. Subsequently a Design of Experiment approach was used to obtain optimized 3D harvest conditions by assessing the interplay of flow rate, collagenase concentration and incubation time on the harvest efficiency, viability and single cell fraction. Cells that were recovered with the optimized harvest protocol, by perfusing a 880 U/ml collagenase solution for 7 hours at a flow rate of 4 ml/min, were thereafter functionally analyzed for their characteristics as expanded progenitor cell population. As both the in vitro tri-lineage differentiation capacity and the in vivo bone forming potential were maintained after 3D perfusion bioreactor expansion we concluded that the developed seeding, culture and harvest processes did not significantly compromise the viability and potency of the cells and can contribute to the future development of integrated bioprocesses for stem cell expansion.

Large-Scale Mesenchymal Stem/Stromal Cell Expansion: A Visualization Tool for Bioprocess Comparison.

Large-scale and cost-effective cell expansion processes are a prerequisite for the clinical and commercial translation of cell-based therapies. A large variety of cell expansion processes are described in literature, utilizing different cell types, culture vessels, and medium formulations. Consequently there are no straightforward means for the comparison or benchmarking of these processes in terms of efficiency, scale, or costs. The purpose of this study was to systematically review the available mesenchymal stromal cell (MSC) expansion literature and develop an interactive visualization tool for comparing the expansion processes. By using this computational tool, process data could be concentrated, standardized, and analyzed to facilitate a more general understanding of the parameters that define a cell culture process, and in the future allow rational selection or design of these bioprocesses. Additionally, a set of bioprocess metrics were defined that assured the comparability between different processes. Currently, the literature-based data repository holds 73 individual cell expansion processes on seven different types of human MSCs in five different types of culture vessels. The visualization tool allowed benchmarking of these processes against each other, serving as a reference point for cell expansion process efficiency.

Multifactorial Optimization of Contrast-Enhanced Nanofocus Computed Tomography for Quantitative Analysis of Neo-Tissue Formation in Tissue Engineering Constructs.

To progress the fields of tissue engineering (TE) and regenerative medicine, development of quantitative methods for non-invasive three dimensional characterization of engineered constructs (i.e. cells/tissue combined with scaffolds) becomes essential. In this study, we have defined the most optimal staining conditions for contrast-enhanced nanofocus computed tomography for three dimensional visualization and quantitative analysis of in vitro engineered neo-tissue (i.e. extracellular matrix containing cells) in perfusion bioreactor-developed Ti6Al4V constructs. A fractional factorial ‘design of experiments’ approach was used to elucidate the influence of the staining time and concentration of two contrast agents (Hexabrix and phosphotungstic acid) and the neo-tissue volume on the image contrast and dataset quality. Additionally, the neo-tissue shrinkage that was induced by phosphotungstic acid staining was quantified to determine the operating window within which this contrast agent can be accurately applied. For Hexabrix the staining concentration was the main parameter influencing image contrast and dataset quality. Using phosphotungstic acid the staining concentration had a significant influence on the image contrast while both staining concentration and neo-tissue volume had an influence on the dataset quality. The use of high concentrations of phosphotungstic acid did however introduce significant shrinkage of the neo-tissue indicating that, despite sub-optimal image contrast, low concentrations of this staining agent should be used to enable quantitative analysis. To conclude, design of experiments allowed us to define the most optimal staining conditions for contrast-enhanced nanofocus computed tomography to be used as a routine screening tool of neo-tissue formation in Ti6Al4V constructs, transforming it into a robust three dimensional quality control methodology.

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.

Product and Process Design: Toward Industrial TE Manufacturing

Abstract As the field of tissue engineering matures and the transition from bench-scale to large-scale industrialized production is realized, a new set of biological and technological challenges arises. To bring tissue-engineered products to the clinic and subsequently to the market will require the application of engineering principles and practices to achieve control, reproducibility, automation, validation, and safety of the process and the product. The successful translation will require contributions not only from fundamental research (from developmental biology to advanced modeling mathematical approaches) but also from existing industrial practice (biopharma), especially on automation, quality assurance, and regulation.