This thesis focuses on selected areas of biomedical research in order to benefit from current computational infrastructures established in scientific community in european and global area. The theory of computation, parallelism and distributed computing, with focus on grid computing and cloud computing, is briefly introduced. Exchange of medical images was studied and a seamless integration of grid-based PACS system was established with the current distributed system in order to share DICOM medical images. Voice science was studied and access to real-time voice analysis application via remote desktop technology was introduced using customized protocol to transfer sound recording. This brings a possibility to access current legacy application remotely by voice specialists. The systems biology approach within domain of human physiology and pathophysiology was studied. Modeling methodology of human physiology was improved in order to build complex models based on acausal and object-oriented modeling techniques. Methods for conducting a parameter study (especially parameter estimation and parameter sweep) were introduced using grid computing and cloud computing technology. The identification of parameters gain substantial speedup by utilizing cloud computing deployment when performed on medium complex models of...

This thesis focuses on selected areas of biomedical research in order to benefit from current computational infrastructures established in scientific community in european and global area. The theory of computation, parallelism and distributed computing, with focus on grid computing and cloud computing, is briefly introduced. Exchange of medical images was studied and a seamless integration of grid-based PACS system was established with the current distributed system in order to share DICOM medical images. Voice science was studied and access to real-time voice analysis application via remote desktop technology was introduced using customized protocol to transfer sound recording. This brings a possibility to access current legacy application remotely by voice specialists. The systems biology approach within domain of human physiology and pathophysiology was studied. Modeling methodology of human physiology was improved in order to build complex models based on acausal and object-oriented modeling techniques. Methods for conducting a parameter study (especially parameter estimation and parameter sweep) were introduced using grid computing and cloud computing technology. The identification of parameters gain substantial speedup by utilizing cloud computing deployment when performed on medium complex models of...

<p>  </p> <p>Diabetes, a chronic condition characterized by elevated blood glucose levels, arises when pancreatic β-cells lose capacity to produce a robust, dynamic glucose-stimulated insulin secretion (GSIS) response. Accurate measurement of β-cell health and function <em>ex vivo</em> is thus fundamental to diabetes research, including studies evaluating disease mechanisms, novel drug candidates, and replacement β-cell populations. However, present-day dynamic GSIS assays typically represent end-point measurements, involve expensive commercial perifusion machines, and require time-consuming enzyme-linked immunosorbent assays (ELISA) for insulin detection. Microfluidic devices developed as accessible, low-cost alternatives still rely on secondary ELISAs and suspend islets in liquid medium, limiting their survival <em>in vitro</em>. Here, we present a novel, 3D-printed microphysiological system (MPS) designed to recreate components of <em>in-vivo</em> microenvironments through encapsulation in fibrillar type I collagen and restoration of favorable molecular transport conditions. Following computational-informed design and rapid prototyping, the MPS platform sustained collagen-encapsulated mouse islet viability and cytoarchitecture for 5 days and supported <em>in-situ</em> measurements of dynamic β-cell function. To rapidly detect insulin secretion from β-cells in the MPS, we then developed a highly sensitive electrochemical sensor for zinc (Zn2+), co-released with insulin, based on glassy carbon electrodes modified with bismuth and indium and coated with Nafion. Finally, we validated sensor detection of Zn2+ released from glucose-stimulated INS-1 β-cells and primary mouse islets, finding high correlation with insulin as measured by standard ELISA. Together, the 3D MPS and Zn2+ sensor developed in this dissertation represent novel platforms for evaluating β-cell health and function in a low-cost, user-friendly, and physiologically-relevant manner. </p>

<p dir="ltr">The brain is a dynamic tissue that is passively driven by a combination of the cardiac cycle, respiration, and slow wave oscillations. The function of the brain relies on its ability to maintain a normal homeostatic balance between its mechanical environment and metabolic demands, which can be greatly altered in the cases of neurodegeneration or traumatic brain injury. It has been a challenge in the field to quantify the dynamics of the tissue and cerebrospinal fluid flow in human subjects on a patient-specific basis over the many spatial and temporal scales that it relies upon. Non-invasive imaging tools like structural, functional, and dynamic MRI sequences provide modern researchers with an unprecedented view into the human brain. Our work leverages these sequences by developing novel, open-source pipelines to 1) quantify the biomechanical environment of the brain tissue over 133 functional brain regions, and 2) estimate real-time cerebrospinal fluid velocity from flow artifacts on functional MRI by employing breathing regimens to enhance fluid motion. These pipelines provide a comprehensive view of the macroscale tissue and fluid motion in a given patient. Additionally, we sought to understand how the transmission of macroscale forces, in the context of traumatic brain injury, contribute to neuronal damage by 3) developing a digital twin to simulate 30-200 g-force loading of 2D neuronal cultures and observing the morphological and electrophysiological consequences of these impacts in vitro by our collaborators. Taken together, we believe these works are a steppingstone that will enable future researchers to deeply understand the mechanical contributions that underly clinical neurological outcomes and perhaps lead to the development of earlier diagnostics, which is of dire need in the case of neurodegenerative diseases.</p>

<p dir="ltr">Fibromuscular Dysplasia (FMD) is a non-inflammatory, non-atherosclerotic blood vessel disorder characterized by a series of narrowed and dilated regions of vasculature. These patients are prescribed blood thinners or anti-platelet therapeutics as treatment to this systemic disease. Current image-based diagnostic methods cannot reliably predict a patient’s risk of stroke in order to properly manage medication. There are also challenges in distinguishing FMD from other diseases that can cause arterial obstructions, like atherosclerosis or vasculitis.</p><p dir="ltr">The ultimate goal of this research is to develop a methodology for evaluating the risk of mechanical platelet activation based on medical imaging. Our hypothesis is that subject-specific assessment of platelet activation due to hemodynamic stress can improve risk stratification of FMD patients. The aims of the projects were therefore to 1) Develop a CFD-based methodology for estimating platelet activation state, and 2) Test this methodology on a small cohort of subjects with FMD, carotid artery stenosis, and healthy controls. A modeling workflow was developed, combining Eulerian and Lagrangian approaches to compute flow fields and evaluate shear stress history of particles advected through the vascular geometries. From this stress history, predictive estimates of mechanical platelet activation can be calculated utilizing a platelet activation state (PAS) metric. We applied this modeling workflow to assess platelet activation in segments of carotid arteries of patients with Fibromuscular Dysplasia, Carotid Artery Stenosis, and healthy controls for comparison against experiments performed at the Cleveland Clinic assessing mechanical platelet activation in patients with each of these conditions. This work supports the development of a patient-specific determination of these same metrics, in order to more precisely assess patient risk of stroke.</p>

<p>Subcutaneous administration has become a common approach for drug delivery of biotherapeutics, such as monoclonal antibodies, which is achieved mainly by absorption through the lymphatic system. This dissertation focuses on the computational modeling of the fluid flow and solute transport in the skin tissue and the quantitative investigation of lymphatic uptake. First, the various mechanisms governing drug transport and lymphatic uptake of biotherapeutics through subcutaneous injection are investigated quantitatively through high-fidelity numerical simulations, including lymphatic drainage, blood perfusion, binding, and metabolism. The tissue is modeled as a homogeneous porous medium using both a single-layered domain and a multi-layered domain, which includes the epidermis, dermis, hypodermis (subcutaneous tissue), and muscle layers. A systematic parameter study is conducted to understand the roles of different properties of the tissue in terms of permeability, porosity, and vascular permeability. The role of binding and metabolism on drug absorption is studied by varying the binding parameters for different macromolecules after coupling the transport equation with a pharmacokinetic equation. The interstitial pressure plays an essential role in regulating the absorption of unbound drug proteins during the injection, while the binding and metabolism of drug molecules reduce the total free drugs. </p> <p>  </p> <p>The lymphatic vessel network is essential to achieve the functions of the lymphatic system. Thus, the drug transport and lymphatic uptake through a three-dimensional hybrid discrete-continuum vessel network in the skin tissue are investigated through high-fidelity numerical simulations. The explicit heterogeneous vessel network is embedded into the continuum model to investigate the role of explicit heterogeneous vessel network in drug transport and absorption. The solute transport across the vessel wall is investigated under various transport conditions. The diffusion of the drug solutes through the explicit vessel wall affects the drug absorption after the injection, while the convection under large interstitial pressure dominates the drug absorption during the injection. The effect of diffusion cannot be captured by the previously developed continuum model. Furthermore, the effects of injection volume and depth on the lymphatic uptake are investigated in a multi-layered domain. The injection volume significantly affects lymphatic uptake through the heterogeneous vessel network, while the injection depth has little influence. At last, the binding and metabolism of drug molecules are studied to bridge the simulation to the experimentally measured drug clearance. </p> <p><br></p> <p>Convective transport of drug solutes in biological tissues is regulated by the interstitial fluid pressure, which plays a crucial role in drug absorption into the lymphatic system through the subcutaneous (SC) injection.  An approximate continuum poroelasticity model is developed to simulate the pressure evolution in the soft porous tissue during an SC injection. This poroelastic model mimics the deformation of the tissue by introducing the time variation of the interstitial fluid pressure. The advantage of this method lies in its computational time efficiency and simplicity, and it can accurately model the relaxation of pressure. The interstitial fluid pressure obtained using the proposed model is validated against both the analytical and the numerical solution of the poroelastic tissue model. The decreasing elasticity elongates the relaxation time of pressure, and the sensitivity of pressure relaxation to elasticity decreases with the hydraulic permeability, while the increasing porosity and permeability due to deformation alleviate the high pressure. </p> <p><br></p> <p>At last, an improved Kedem-Katchalsky model is developed to study solute transport across the lymphatic vessel network, including convection and diffusion in the multi-layered poroelastic tissue with a hybrid discrete-continuum vessel network embedded inside. The effect of different drug solutes with different Stokes radii and different structures of the lymphatic vessel network, such as fractal trees and Voronoi structure, on the lymphatic uptake is investigated. The drug solute with a small size has a larger partition coefficient and diffusivity across the openings of the lymphatic vessel wall, which favors drug absorption. The Voronoi structure is found to be more efficient in lymphatic uptake. </p> <p><br></p> <p>The systematic and quantitative investigation of subcutaneous absorption based on high-fidelity numerical simulations can provide guidance on the optimization of drug delivery systems and is valuable for the translation of bioavailability from the pre-clinical species to humans. We provide a novel approach to studying the diffusion and convection of drug molecules into the lymphatic system by developing the hybrid discrete-continuum vessel network. The study of the solute transport across the discrete lymphatic vessel walls further improves our understanding of lymphatic uptake. The novel and time-efficient computational model for solute transport across the lymphatic vasculature connects the microscopic properties of the lymphatic vessel membrane to macroscopic drug absorption. The comprehensive hybrid vessel network model developed here can be further used to improve our understanding of the diseases caused by the disturbed lymphatic system, such as lymphedema, and provide insights into the treatment of diseases caused by the malfunction of lymphatics.</p>