Research Project
10399790
PROJECT ABSTRACT Chemical, physical, and biological processes interact across multiple length and time scales and lead to consequences for human physiology, disease progression, and medical therapeutics. Clinical outcomes and other dynamic effects emerge from the collective behavior across multiple scales and cannot be explained simply by studying the isolated parts at a single scale. Multiscale systems engineering approaches allow for quantitative descriptions of interconnected processes, which aids understanding of the mechanisms for the links between the processes that cannot be decoupled easily in experiments. The overall vision for the PI's research program titled the Systems Biomedicine & Pharmaceutics Lab is to develop multiscale computational models and methods for building and solving those models to enhance understanding of the mechanisms governing tissue remodeling and damage as a result of diseases and infections and to simulate the treatment of those conditions to improve human health. Tissue damage considered in the proposed research focuses on processes that involve changes to the extracellular matrix (ECM), which provides biochemical and structural support to surrounding cells. Building multiscale computational models for the chemical and biological processes that result in structural addition or depletion of ECM, which damages various tissues, will increase fundamental mechanistic understanding of human tissues and lay the foundation for advances in disease treatment and prevention. The rationale is that multiscale computational models provide insights into the complex network of the effects of molecular level actions of chemicals such as glucose, hormones, and pharmaceuticals on the cellular, tissue, and whole body levels of physiology. The proposed research addresses the critical need to compile the multiple processes that contribute to the onset and progression of chronic tissue damage into user-friendly systematic computational frameworks capable of taking the interconnected chemical, physical, and biological factors into account in a coupled fashion and in the appropriate magnitudes and sequences to make testable predictions. In the absence of such frameworks, unraveling the network of events in the chronic injury of tissues will continue to be perplexing, and the development of effective pharmaceutical treatments will likely remain piecemeal and slow. The goals for the next five years are 1) to develop methods to accelerate and facilitate the construction and reuse of the multiscale models and 2) to create new multiscale models to improve physiological understanding of how local and systemic immune stimulants affect damage in arthritic autoimmune inflammation and cancer immunotherapy. These goals build upon methods the PI's lab has adopted for quantitative systems biomedicine and pharmacology and the recent results they have produced related to computational models applied to multiscale tissue damage in diabetic kidney disease, tuberculosis, and metastatic cancer.
