A study on application of combinatorial methods (CM) and high-throughput methods (HTM) to biomaterials design, characterization, and screening are reported in this thesis - focusing on screening the effects of biomaterial surface features on adherent bone cell cultures. Polymeric biomaterials were prepared on two-dimensional combinatorial libraries that systematically varied the size and shape of chemically-distinct microstructural patterns - generated from blends of biodegradable polyurethanes and polyesters. Characterization and screening were performed with high-throughput optical and fluorescence microscopy. A unique advance of this work is the application of data mining techniques to identify the controlling structural features that affect cell behavior from among the myriad variety of metrics from the microscope images.
The results from this study demonstrated the potentials of CM/HTS to be applied to exploratory studies involving complex systems in life sciences. This study accomplishes the goal to demonstrate the efficient screening and exploration of vast and complex dataset, extracting important and meaningful information to narrow down the future path of study in this field.
Further study aimed to tuning cellular responses via signals from surface cues will be necessary to examine the causal relationships beyond the observed correlations shown in this exploratory study. It is recommended for further studies to narrow down the range for surface patterning around each of the three 'activation' ranges found in this study: apoptotic, viable, and one unknown state to be studied further. Different cellular-function staining methods will be necessary to be used in cellular imaging techniques in order to explore this unknown state further.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/31735 |
Date | 21 August 2009 |
Creators | Wingkono, Gracy A. |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Detected Language | English |
Type | Dissertation |
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