A computational analysis of the impact of mass transport and shear on three-dimensional stem cell cultures in perfused micro-bioreactors

Virtual cells in a virtual microenvironment recapitulate early development-like patterns in human pluripotent stem cell colonies

The mechanism by which morphogenetic signals engage the regulatory networks responsible for early embryonic tissue patterning is incompletely understood. Here, we developed a minimal gene regulatory network (GRN) model of human pluripotent stem cell (hPSC) lineage commitment and embedded it into "cellular" agents that respond to a dynamic morphogenetic signaling microenvironment. Simulations demonstrated that GRN wiring had significant non-intuitive effects on tissue pattern order, composition, and dynamics. Experimental perturbation of GRN connectivities supported model predictions and demonstrated the role of OCT4 as a master regulator of peri-gastrulation fates. Our so-called GARMEN strategy provides a multiscale computational platform to understand how single-cell-based regulatory interactions scale to tissue domains. This foundation provides new opportunities to simulate the impact of network motifs on normal and aberrant tissue development.

Numerical modelling of osteocyte growth on different bone tissue scaffolds

The most common solution for the regeneration or replacement of damaged bones is the implantation of prostheses comprising ceramic or metallic materials. However, these implants are known to cause problems such as post-operative infections, collapse of the prosthesis, and lack of osseointegration. Consequently, bone tissue engineering was established because of the limitations of such implants. Osteogenic implants offer promising solutions for bone regeneration; however, three-dimensional scaffolds should be used as supportive structures. It is challenging to correctly design these structures and their compositions or properties to provide a microenvironment that promotes tissue regeneration and expedites bone formation. Computational fluid dynamics can be used to model the main phenomena that occur in bioreactors, such as cell metabolism, nutrient transport, and cell culture growth, or to model the influence of several key mechanisms related to the fluid medium, in particular, the wall shear stress. In this work, a new numerical bone cell growth model was developed, which considered the oxygen and nutrient consumption as well as the wall shear stress effect on cell proliferation. The model was implemented using 35 three-dimensional scaffolds of different porosities, and the effect of the main geometrical parameters involved in each scaffold type was analysed. The porosity plays an important role, however, a similar porosity did not guarantee similar shear stress or cell growth among the scaffolds. Randomised trabecular scaffolds, that more closely resembled trabecular bone, showed the highest cell growth values, so these are the best candidates for cell growth in a bioreactor.

Respiratory healthcare by design: Computational approaches bringing respiratory precision and personalised medicine closer to bedside

Precision medicine represents a potentially powerful means to alleviate the growing burden of chronic respiratory diseases. To realise its potential, however, we need a systems level understanding of how biological events (signalling pathways, cell-cell interactions, tissue mechanics) integrate across multiple spatial and temporal scales to give rise to pathology. This can be achieved most practically in silico: a paradigm that offers tight control over model parameters and rapid means of testing and generating mechanistic hypotheses. Patient-specific computational models that can enable identification of pathological mechanisms unique to patients' (omics, physiological, and anatomical) profiles and, therefore, personalised drug targets represent a major milestone in precision medicine. Current patient-based models in literature, especially medical devices, cardiac modelling, and respiratory medicine, rely mostly on (partial/ordinary) differential equations and have reached relatively advanced level of maturity. In respiratory medicine, patient-specific simulations mainly include subject scan-based lung mechanics models that can predict pulmonary function, but they treat the (sub)cellular processes as "black-boxes". A recent advance in simulating human airways at a cellular level to make clinical predictions raises the possibility of linking omics and cell level data/models with lung mechanics to understand respiratory pathology at a systems level. This is significant as this approach can be extended to understanding pathologies in other organs as well. Here, I will discuss ways in which computational models have already made contributions to personalised healthcare and how the paradigm can expedite clinical uptake of precision medicine strategies. I will mainly focus on an agent-based, asthmatic virtual patient that predicted the impact of multiple drug pharmacodynamics at the patient level, its potential to develop efficacious precision medicine strategies in respiratory medicine, and the regulatory and ethical challenges accompanying the mainstream application of such models.

Fabrication and in vitro evaluation of a packed-bed bioreactor based on an optimum two-stage culture strategy

A packed-bed (PB) bioreactor for bioartificial liver (BAL) was fabricated based on an optimum two-stage culture strategy and evaluated in vitro in this research. Human induced hepatocytes (hiHeps) were first expanded using Cytodex 3 microcarriers and the choice of microcarrier concentration and fetal bovine serum (FBS) content was optimized. Then, the cells expanded under the optimum expansion condition were perfused into a perfusion system containing Fibra-Cel (FC) disks to fabricate a PB bioreactor. Operating parameters including flow rate and seeding density for perfusion culture were optimized, respectively. Results indicated that during suspension culture, rapid cell proliferation and favorable amino acid metabolism were achieved at 3 mg/mL microcarriers combined with 1% FBS. While for the perfusion culture, the most effective flow rate and seeding density were 2 mL/min and 1 × 10⁶ cells/mL, respectively. Under this optimum perfusion condition, hiHeps showed good proliferation ability, high viability, homogeneous distribution, high metabolism activities and efficient albumin secretion as well as high liver-specific genes expression. Therefore, the two-stage culture strategy based on operating parameters optimization provides a new method for the development of PB bioreactors.

2D µ-Particle Image Velocimetry and Computational Fluid Dynamics Study Within a 3D Porous Scaffold

Transport properties of 3D scaffolds under fluid flow are critical for tissue development. Computational fluid dynamics (CFD) models can resolve 3D flows and nutrient concentrations in bioreactors at the scaffold-pore scale with high resolution. However, CFD models can be formulated based on assumptions and simplifications. μ-Particle image velocimetry (PIV) measurements should be performed to improve the reliability and predictive power of such models. Nevertheless, measuring fluid flow velocities within 3D scaffolds is challenging. The aim of this study was to develop a μPIV approach to allow the extraction of velocity fields from a 3D additive manufacturing scaffold using a conventional 2D μPIV system. The μ-computed tomography scaffold geometry was included in a CFD model where perfusion conditions were simulated. Good agreement was found between velocity profiles from measurements and computational results. Maximum velocities were found at the centre of the pore using both techniques with a difference of 12% which was expected according to the accuracy of the μPIV system. However, significant differences in terms of velocity magnitude were found near scaffold substrate due to scaffold brightness which affected the μPIV measurements. As a result, the limitations of the μPIV system only permits a partial validation of the CFD model. Nevertheless, the combination of both techniques allowed a detailed description of velocity maps within a 3D scaffold which is crucial to determine the optimal cell and nutrient transport properties.