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- All Subjects: Biomaterials
- All Subjects: Creative Project
- All Subjects: Neuroscience
- Creators: Harrington Bioengineering Program
- Status: Published
The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.
There is a wide intersection where animal and human lives interact or mimic each other behaviorally or biologically. A lot of the products that are part of our day-to-day were first validated by animals, and eventually found their way to us. From food to beauty products to scientific developments, animals deal with a lot behind the scenes. Some humans are cognizant of what is happening backstage, while others only see the final presentation. Either way, all of us have our opinions in support or against animal treatment. The project is heavily inspired from my experience in a neurorehabilitation lab, so the foundation is similar to the structure and function of neurons. Through this project, I am focusing on one aspect of this debate, which is animal testing in the scietific setting. The goal of the project is not to force the viewer to choose one side, but to understand the big picture and the reasoning of the opposing side.
commands designed to streamline post-processing of MRI images. Using this partnership, the Applied Neuroscience and Technology Lab at PCH has been able to complete production of a post-processing pipeline which integrates locally sourced smoothing techniques to help identify lesions in patients with evidence of Focal Cortical Dysplasia. The end result is a system in which a patient with epilepsy may experience more successful post-surgical results due to the
combination of a lesion detection mechanism and the radiologist using their trained eye in the presurgical stages. As one of the main points of this work is the global aspect of it, Barrett thesis funding was dedicated for a trip to London in order to network with other MELD project collaborators. This was a successful trip for the project as a whole in addition to this particular thesis. The ability to troubleshoot problems with one another in a room full of subject matter
experts allowed for a high level of discussion and learning. Future work includes implementing machine learning approaches which consider all morphometry parameters simultaneously.