In silico model development and optimization of in vitro lung cell population growth.

Tissue engineering predominantly relies on trial and error in vitro and ex vivo experiments to develop protocols and bioreactors to generate functional tissues. As an alternative, in silico methods have the potential to significantly reduce the timelines and costs of experimental programs for tissue engineering. In this paper, we propose a methodology to formulate, select, calibrate, and test mathematical models to predict cell population growth as a function of the biochemical environment and to design optimal experimental protocols for model inference of in silico model parameters. We systematically combine methods from the experimental design, mathematical statistics, and optimization literature to develop unique and explainable mathematical models for cell population dynamics. The proposed methodology is applied to the development of this first published model for a population of the airway-relevant bronchio-alveolar epithelial (BEAS-2B) cell line as a function of the concentration of metabolic-related biochemical substrates. The resulting model is a system of ordinary differential equations that predict the temporal dynamics of BEAS-2B cell populations as a function of the initial seeded cell population and the glucose, oxygen, and lactate concentrations in the growth media, using seven parameters rigorously inferred from optimally designed in vitro experiments.

A Comparison of Vessel Patch Materials in Tetralogy of Fallot Patients Using Virtual Surgery Techniques.

Tetralogy of Fallot (ToF) is characterized by stenosis causing partial obstruction of the right ventricular outflow tract, typically alleviated through the surgical application of a vessel patch made from a biocompatible material. In this study, we use computational simulations to compare the mechanical performance of four patch materials for various stenosis locations. Nine idealized pre-operative ToF geometries were created by imposing symmetrical stenoses on each of three anatomical sub-regions of the pulmonary arteries of three patients with previously repaired ToF. A virtual surgery methodology was implemented to replicate the steps of vessel de-pressurization, surgical patching, and subsequent vessel expansion after reperfusion. Significant differences in patch average stress (p < 0.001) were found between patch materials. Biological patch materials (porcine xenopericardium, human pericardium) exhibited higher patch stresses in comparison to synthetic patch materials (Dacron and PTFE). Observed differences were consistent across the various stenosis locations and were insensitive to patient anatomy.

Combinatorial screening of 3D biomaterial properties that promote myofibrogenesis for mesenchymal stromal cell-based heart valve tissue engineering.

The physical and chemical properties of a biomaterial integrate with soluble cues in the cell microenvironment to direct cell fate and function. Predictable biomaterial-based control of integrated cell responses has been investigated with two-dimensional (2D) screening platforms, but integrated responses in 3D have largely not been explored systematically. To address this need, we developed a screening platform using polyethylene glycol norbornene (PEG-NB) as a model biomaterial with which the polymer wt% (to control elastic modulus) and adhesion peptide types (RGD, DGEA, YIGSR) and densities could be controlled independently and combinatorially in arrays of 3D hydrogels. We applied this platform and regression modeling to identify combinations of biomaterial and soluble biochemical (TGF-ß1) factors that best promoted myofibrogenesis of human mesenchymal stromal cells (hMSCs) in order to inform our understanding of regenerative processes for heart valve tissue engineering. In contrast to 2D culture, our screens revealed that soft hydrogels (low PEG-NB wt%) best promoted spread myofibroblastic cells that expressed high levels of α-smooth muscle actin (α-SMA) and collagen type I. High concentrations of RGD enhanced α-SMA expression in the presence of TGF-ß1 and cell spreading regardless of whether TGF-ß1 was in the culture medium. Strikingly, combinations of peptides that maximized collagen expression depended on the presence or absence of TGF-ß1, indicating that biomaterial properties can modulate MSC response to soluble signals. This combination of a 3D biomaterial array screening platform with statistical modeling is broadly applicable to systematically identify combinations of biomaterial and microenvironmental conditions that optimally guide cell responses. STATEMENT OF SIGNIFICANCE: We present a novel screening platform and methodology to model and identify how combinations of biomaterial and microenvironmental conditions guide cell phenotypes in 3D. Our approach to systematically identify complex relationships between microenvironmental cues and cell responses enables greater predictive power over cell fate in conditions with interacting material design factors. We demonstrate that this approach not only predicts that mesenchymal stromal cell (MSC) myofibrogenesis is promoted by soft, porous 3D biomaterials, but also generated new insights which demonstrate how biomaterial properties can differentially modulate MSC response to soluble signals. An additional benefit of the process includes utilizing both parametric and non parametric analyses which can demonstrate dominant significant trends as well as subtle interactions between biochemical and biomaterial cues.