The PI will spend a year in the Program of Biomedical Engineering at her home institution, Louisiana Tech University, where she will work in two research areas while advising a PhD student in each area. The first project will integrate neuroscience, nano- and micro-technology engineering, mathematical modeling, and feedback control. Data sets of calcium ion dynamics will be the basis for mathematical analysis and modeling of brain cell network activity, to include development of a computational brain cell controller. As one of the most important secondary messengers in the body, calcium ions are involved in both intracellular and intercellular coordination. Mathematical model development of neuron dynamics will lay the foundation for design of a feedback controller to estimate calcium concentration in brain cells, which has the potential to further understanding of how the human body reacts to disorders of the brain and the predictive behavior of the brain.
The second project will integrate nanotechnology engineering, mathematical modeling, and feedback control design. The mathematical modeling involved will result in the development of an accurate prediction of the amount of a nano-therapeutic agent that reaches a tumor site based on real-time estimates of drug bioavailability. This, in turn, will lay the groundwork for the design of a computational feedback controller that would be used to noninvasively measure and regulate drug concentration in the body. Although the current treatment of cancerous tumors can be very effective, there is no way of monitoring the therapy as it is being administered. In fact, the only way the amount of chemotherapy to be administered is determined by the patient's body mass. By joining together mathematical modeling and feedback control techniques, this project seeks to provide a mechanism for prediction of the effects of the nano-particle chemotherapy drugs in a patient's body, thus leading to better models for drug regimen and administration.
Normal 0 false false false EN-US X-NONE X-NONE This project involves two research thrusts. The first area relates to modeling and quantification of brain cell calcium dynamics. As one of the most important secondary messengers in the body, calcium ions are involved in both intracellular and intercellular coordination. In this work, data sets of calcium ion dynamics have been analyzed from the perspective of activity as well as sustained calcium load, i.e. calcium influx below a toxic level that would lead to cell death. Analysis supports the finding that cellular calcium load is a good prediction of how a cell will behave in the future when subjected to new neurotransmitter stimulation. It was also observed that increasing neurotransmitter concentration leads to increased calcium load but decreased neuronal dynamic response. When considering stimulation by large neurotransmitter concentration followed by smaller concentration, cell recovery after a large stimulus will be slow initially, but subsequent stimuli will result in faster recovery. This observation may have relevance to understanding desensitization for how the brain processes information, potentially explaining waiting periods necessary for cells to handle one stimulus before a second can be integrated. The second area of this project relates to modeling and control of bloodstream nanoparticle concentration for cancer therapeutics. Although the current treatment of cancerous tumors can be very effective, there is no way of monitoring the therapy as it is being administered. In fact, the only way the amount of chemotherapy to be administered is determined by the patient’s body mass. By joining together mathematical modeling and feedback control techniques, this project has quantified the bloodstream nanoparticle concentration during uptake and clearance for two different dosing groups of mice experimental trials. Statistical analysis was also performed to assess the likelihood future experimental data would fit to these curves. These models were implemented to interface with existing nanoparticle detection hardware so that data from current animal experiments identified in real-time to lie outside the statistical model bounds will signal a possible adverse nanoparticle reaction in a subject. Several control strategies were implemented to regulate bloodstream nanoparticle concentration, with one particular controller yielding low error with minimal total injection and short computational time. This control strategy was also able to keep the absorbance value very close to the target for the majority of the length of the experiment. This controller will be implemented in current animal experiments to increase the circulation time of nanoparticles, while administering a smaller amount of nanoparticles than presently used, which will thereby increase the quantity of nanoparticles reaching a tumor site and increase the therapeutic effect. This work is likely to have clinical implications in human cancer therapy because it represents a step toward better models for drug regimen and administration.
