Spectroscopy and other optical methods can often be employed with limited or no sample preparation, making them well suited for in situ and in vivo analysis. This dissertation focuses on the use of a near-infrared spectroscopy (NIRS) and polarized light scatter for two such applications: the assessment of cardiovascular disease, and the validation of cleaning processes for pharmaceutical equipment.There is a need for more effective in vivo techniques for assessing intravascular disorders, such as aortic aneurysms and vulnerable atherosclerotic plaques. These, and other cardiovascular disorders, are often associated with structural remodeling of vascular walls. NIRS has previously been demonstrated as an effective technique for the analysis of intact biological samples. In this research, traditional NIRS is used in the analysis of aortic tissue samples from a murine knockout model that develops abdominal aortic aneurysms (AAAs) following infusion of angiotensin II. Effective application of NIRS in vivo, however, requires a departure from traditional instrumental principles. Toward this end, the groundwork for a fiber optic-based catheter system employing a novel optical encoding technique, termed molecular factor computing (MFC), was developed for differentiating cholesterol, collagen and elastin through intervening red blood cell solutions. In MFC, the transmission spectra of chemical compounds are used to collect measurements directly correlated to the desired sample information.Pharmaceutical cleaning validation is another field that can greatly benefit from novel analytical methods. Conventionally cleaning validation is accomplished through surface residue sampling followed by analysis using a traditional analytical method. Drawbacks to this approach include cost, analysis time, and uncertainties associated with the sampling and extraction methods. This research explores the development of in situ cleaning validation methods to eliminate these issues. The use of light scatter and polarization was investigated for the detection and quantification of surface residues. Although effective, the ability to discriminate between residues was not established with these techniques. With that aim in mind, the differentiation of surface residues using NIRS and MFC was also investigated.
| Identifer | oai:union.ndltd.org:uky.edu/oai:uknowledge.uky.edu:gradschool_diss-1529 |
| Date | 01 January 2007 |
| Creators | Urbas, Aaron Andrew |
| Publisher | UKnowledge |
| Source Sets | University of Kentucky |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | University of Kentucky Doctoral Dissertations |
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