Multiscale spatio-temporal modeling of cell population in tissue architecture and drug delivery nanoparticles

<p>"Multiscale nature of a biological system span at many order of magnitudes in time and space. Molecular interaction at lower scale is connected with the higher scale behavior of tissue or organism. Integrating the dynamics and information at different time and space can give a fundamental physiological understanding of the higher level phenomena. But complex features, functions, interconnectivity between different scales and lack of information on the fundamental physiological property make the model difficult and computationally challenging. The multiscale modeling approach can bridge the gap between different scale by a systemic integration of the complex dynamic behavior.</p><p>Here, the focus is on developing multiscale modeling approaches to study the dynamic behavior of tissue. First, a multiscale spatiotemporal model is designed to investigate the tissue scale dispersion and penetration of nanoparticles from lower scale particle-cell interaction. The results obtained suggest that the size of nanoparticles may play less significant roles in tissue scale penetration and dispersion. The effect of nanoparticle size is less prominent due to the presence of particle-cell interaction and advection. This scalable spatiotemporal model can simulate the dynamics of drug delivery particles in the extracellular domain of a tissue.</p><p>Furthermore, a parallel framework is developed to study the collective behavior of the cell population in a tissue architecture from their intracellular and extracellular reaction kinetics. The framework can model population dynamics at the tissue scale from a single cell biochemical reaction network accurately and efficiently. Finally, the framework's capability is demonstrated by simulating a full-scale model of bacterial quorum sensing, where the dynamics of a population of bacterial cells is dictated by the intercellular communications in a time-evolving growth environment"--Abstract, page iii.</p>

Name thesis:degree_name

Ph. D. in Chemical Engineering

Grantor

Missouri University of Science and Technology

Author dc:creator

• Islam, Mohammad Aminul

• Cell signaling
• Computational biology
• Multiscale modeling
• Parallelism
• Systems biology
• Tissue transport
• Chemical Engineering

Repository record dc:identifier

https://scholarsmine.mst.edu/doctoral_dissertations/2817

OAI identifier oai:identifier

oai:scholarsmine.mst.edu:doctoral_dissertations-3822