Robert C. Chang

Numerical investigation of dynamic microorgan devices as drug screening platforms. Part II: Microscale modeling approach and validation

The authors have previously reported a rigorous macroscale modeling approach for an in vitro 3D dynamic microorgan device (DMD). This paper represents the second of a two‐part model‐based investigation where the effect of microscale (single liver cell‐level) shear‐mediated mechanotransduction on drug biotransformation is deconstructed. Herein, each cell is explicitly incorporated into the geometric model as single compartmentalized metabolic structures. Each cells metabolic activity is coupled with the microscale hydrodynamic Wall Shear Stress (WSS) simulated around the cell boundary through a semi‐empirical polynomial function as an additional reaction term in the mass transfer equations. Guided by the macroscale model‐based hydrodynamics, only 9 cells in 3 representative DMD domains are explicitly modeled. Dynamic and reaction similarity rules based on non‐dimensionalization are invoked to correlate the numerical and empirical models, accounting for the substrate time scales. The proposed modeling approach addresses the key challenge of computational cost towards modeling complex large‐scale DMD‐type system with prohibitively high cell densities. Transient simulations are implemented to extract the drug metabolite profile with the microscale modeling approach validated with an experimental drug flow study. The results from the authors study demonstrate the preferred implementation of the microscale modeling approach over that of its macroscale counterpart. Biotechnol. Bioeng. 2016;113: 623–634.

Numerical investigation of dynamic microorgan devices as drug screening platforms. Part II: Microscale modeling approach and validation: Numerical Investigation of Dynamic Microorgan

The dynamic nature of in vitro drug metabolism models demands reliable numerical tools to determine key design parameter values towards high‐fidelity cell‐based platforms of in vivo drug metabolism. This paper represents the first of a two‐part model‐based investigation of a 3D dynamic microorgan device (DMD). The prescribed tissue model in this paper is precisely embedded within a DMD by 3D bioprinting hydrogel encapsulated liver cells into a patterned array of microchannels. A perfusing drug substrate is biotransformed by liver cells encapsulated within porous hydrogel walls. Therefore, the free and porous flow regime equations are first solved in tandem to derive the laminar velocity profile and wall shear stresses in the entire shear‐mediated flow regime. These equations are then coupled with a convection‐diffusion equation and Michaelis‐Menten reaction terms, resulting in an effective convection‐diffusion‐cell kinetics model. A key consideration addressed herein is mechanotransduction where shear stresses on the encapsulated cells alter subcellular liver enzyme reaction rates. Cells are incorporated into the geometric model implicitly (macroscale) as enzyme reaction structures uniformly distributed throughout the DMD length. Transient simulations enable effluent drug metabolite profile determination wherein the proposed macroscale modeling approach is validated with an experimental drug flow study. Biotechnol. Bioeng. 2016;113: 612–622.

Comparison of photometric stereo and spectral analysis for visualization and assessment of burn injury from hyperspectral imaging

Burn wounds resulting from thermal insult to the skin are typically classified according to varying depth and therefore require differential levels of medical intervention. In this paper, two methods are proposed for assessing burn injury. The two methods compared are photometric stereo (PS) and spectral analysis. Firstly, PS represents a robust topography recovery algorithm that is implemented to reconstruct the burn and normal skin tissue from multiple hyperspectral images under different illumination conditions. This enabled the visualization of a 3D skin depth map which is used to assess the burn degree. Next, the hyperspectral measurement data of the skin are analyzed to assess partial thickness thermal injury with functional correlation through hemodynamic parameters related to tissue perfusion and oxygen delivery. Two dimensional principle component analysis (2DPCA) is used for noise reduction towards extracting features from the hyperspectral images within the wavelength range from 375 nm to 1050 nm. This is followed by applying the spectral analysis algorithm to calculate oxygen saturation fraction and concentration of total hemoglobin, where each parameter provided a biomarker of injured tissue. The two methods yielded alternative indicators for burn assessment that could be correlated with each other. Specifically, the spectral measurement result could be used as a reference value for the physical skin site depth map.

A Novel Melt Electrospinning System for Studying Cell Substrate Interactions

Controlling cell behavior has generated immense attention in the fields of tissue engineering and regenerative medicine. Particular emphasis has been given to the creation of 3D biomimetic cellular microenvironments that replicate the complex nature of the extracellular matrix (ECM). A key factor that has not been rigorously deconstructed using scalable, layered manufacturing approaches is the structural dimension or scale aspect of in vitro culture models. Melt electrospinning represents a bio-additive manufacturing process that has been relatively under-reported. Although complex in nature, the melt electrospinning process can furnish a 3D cell delivery format with physiologically relevant 3D structural cues. In the present work, poly-e-caprolactone (PCL) has been chosen as the biomaterial substrate. Rheological studies that guide the design phase of the reported system have been performed for the entire PCL melt processing range, implicating the governing effect of the experimental melt temperature on the scale and the topography in the final processed material. Notable challenges that arise from the nature of the process with respect to the electrospun fiber stability and resolution have been overcome through the design of a novel heating element configuration. In this paper, a reliable biofabrication process with tunable processing of the fiber diameter and alignment is reported. Fundamental parametric studies utilizing the major processing parameters demonstrate the potential for the system to precisely fabricate 3D PCL scaffolds with microstructural features.Copyright

Chapter 15 – Organ Printing

Organ printing encompasses bioadditive, digitally controlled manufacturing processes for layered, patterned deposition of complex 3D cell-bearing biological structures. This chapter discusses printing techniques that have evolved to process high-density biopolymer cell suspensions. A review of state-of-art technologies points to a need to address the competing requirements of manufacturing scalability with large-volume patterning for clinical translation with biological exigencies to present cells with an in vivo microscale niche. To instruct process design and development, computational models of printed micro-organ testbeds, in tandem with an integrated strategy of materials processing, process modeling, and metrology for benchmarking functional tissue, will be critical.

Computational Modeling of 3D Printed Tissue-on-a-Chip Microfluidic Devices as Drug Screening Platforms

Physiological tissue-on-a-chip technology is enabled by adapting microfluidics to create micro scale drug screening platforms that replicate the complex drug transport and reaction processes in the human liver. The ability to incorporate three-dimensional (3d) tissue models using layered fabrication approaches into devices that can be perfused with drugs offer an optimal analog of the in vivo scenario. The dynamic nature of such in vitro metabolism models demands reliable numerical tools to determine the optimum tissue fabrication process, flow, material, and geometric parameters for the most effective metabolic conversion of the perfused drug into the liver microenvironment. Thus, in this modeling-based study, the authors focus on modeling of in vitro 3d microfluidic microanalytical microorgan devices (3MD), where the human liver analog is replicated by 3d cell encapsulated alginate hydrogel based tissue-engineered constructs. These biopolymer constructs are hosted in the chamber of the 3MD device serving as walls of the microfluidic array of channels through which a fluorescent drug substrate is perfused into the microfluidic printed channel walls at a specified volumetric flow rate assuring Stokes flow conditions (Re<<1). Due to the porous nature of the hydrogel walls, a metabolized drug product is collected as an effluent stream at the outlet port. A rigorous modeling approached aimed to capture both the macro and micro scale transport phenomena is presented. Initially, the Stokes Flow Equations (free flow regime) are solved in combination with the Brinkman Equations (porous flow regime) for the laminar velocity profile and wall shear stresses in the whole shear mediated flow regime. These equations are then coupled with the Convection-Diffusion Equation to yield the drug concentration profile by incorporating a reaction term described by the Michael-Menten Kinetics model. This effectively yields a convection-diffusion–cell kinetics model (steady state and transient), where for the prescribed process and material parameters, the drug concentration profile throughout the flow channels can be predicted. A key consideration that is addressed in this paper is the effect of cell mechanotransduction, where shear stresses imposed on the encapsulated cells alter the functional ability of the liver cell enzymes to metabolize the drug. Different cases are presented, where cells are incorporated into the geometric model either as voids that experience wall shear stress (WSS) around their membrane boundaries or as solid materials, with linear elastic properties. As a last step, transient simulations are implemented showing that there exists a tradeoff with respect the drug metabolized effluent product between the shear stresses required and the residence time needed for drug diffusion.Copyright

2D and 3D Multiscale Computational Modeling of Dynamic Microorgan Devices as Drug Screening Platforms

The ability to incorporate three-dimensional (3D) hepatocyte-laden hydrogel constructs using layered fabrication approaches into devices that can be perfused with drugs enables the creation of dynamic microorgan devices (DMDs) that offer an optimal analog of the in vivo liver metabolism scenario. The dynamic nature of such in vitro metabolism models demands reliable numerical tools to determine the optimum process, material, and geometric parameters for the most effective metabolic conversion of the perfused drug into the liver microenvironment. However, there is a current lack of literature that integrates computational approaches to guide the optimum design of such devices. The groundwork of the present numerical study has been laid by our previous study [1], where the authors modeled in 2D an in vitro DMD of arbitrary dimensions and identified the modeling challenges towards meaningful results. These constructs are hosted in the chamber of the microfluidic device serving as walls of the microfluidic array of channels through which a fluorescent drug substrate is perfused into the microfluidic printed channel walls at a specified volumetric flow rate assuring Stokes flow conditions (Re<<1). Due to the porous nature of the hydrogel walls, a metabolized drug product is collected at the outlet port. A rigorous FEM based modeling approach is presented for a single channel parallel model geometry (1 free flow channel with 2 porous walls), where the hydrodynamics, mass transfer and pharmacokinetics equations are solved numerically in order to yield the drug metabolite concentration profile at the DMD outlet. The fluid induces shear stresses are assessed both in 3D, with only 27 cells modeled as single compartment voids, where all of the enzymatic reactions are assumed to take place. In this way, the mechanotransduction effect that alters the hepatocyte metabolic activity is assessed for a small scale model. This approach overcomes the numerical limitations imposed by the cell density (∼1012 cells/m3) of the large scale DMD device. In addition, a compartmentalization technique is proposed in order to assess the metabolism process at the subcellular level. The numerical results are validated with experiments to reveal the robustness of the proposed modeling approach and the necessity of scaling the numerical results by preserving dynamic and biochemical similarity between the small and large scale model.Copyright

Design of a Personalized Skin Grafting Methodology Using an Additive Biomanufacturing System Guided by 3D Photogrammetry

In this paper, the authors propose a novel method whereby a prescribed simulated skin graft is 3D printed, followed by the realization of a 3D model representation using an open-source software AutoDesk 123D Catch to reconstruct the entire simulated skin area. The methodology is photogrammetry, which measures the 3D model of a real-word object. Specifically, the principal algorithm of the photogrammetry is structure from motion (SfM) which provides a technique to reconstruct a 3D scene from a set of images collected using a digital camera. This is an efficient approach to reconstruct the burn depth compared to other non-intrusive 3D optical imaging modalities (laser scanning, optical coherence tomography). Initially, an artificial human hand with representative dimensions is designed using a CAD design program. Grooves with a step-like depth pattern are then incorporated into the design in order to simulate a skin burn wound depth map. Then, the *.stl format file of the virtually wounded artificial hand is extruded as a thermoplastic material, acrylonitrile butadiene styrene (ABS), using a commercial 3D printer. Next, images of the grooves representing different extents of burned injury are acquired by a digital camera from different directions with respect to the artificial hand. The images stored in a computer are then imported into AutoDesk 123D Catch to process the images, thereby yielding the 3D surface model of the simulated hand with a burn wound depth map. The output of the image processing is a 3D model file that represents the groove on the plastic object and thus the burned tissue area. One dimensional sliced sections of the designed model and reconstructed model are compared to evaluate the accuracy of the reconstruction methodology. Finally, the 3D CAD model is designed with a prescribed internal tissue scaffold structure and sent to the dedicated software of the 3D printing system to print the design of the virtual skin graft with biocompatible material poly-e-caprolactone (PCL).Copyright