Date Available
12-14-2011
Year of Publication
2009
Degree Name
Doctor of Philosophy (PhD)
Document Type
Dissertation
College
Arts and Sciences
Department
Chemistry
First Advisor
Dr. Robert A. Lodder
Abstract
Acoustic methods can often be used with limited or no sample preparations making them ideal for rapid process analytical technologies (PATs). This dissertation focuses on the possible use of acoustic resonance spectroscopy as a PAT in the pharmaceutical industry. Current good manufacturing processes (cGMP) need new technologies that have the ability to perform quality assurance testing on all products. ARS is a rapid and non destructive method that has been used to perform qualitative studies but has a major drawback when it comes to quantitative studies. Acoustic methods create highly non linear correlations which usually results in high level computations and chemometrics.
Quantification studies including powder contamination levels, hydration amounts and active pharmaceutical ingredient (API) concentrations have been used to test the hypothesis that bootstrap enhanced n-dimensional deformation of space (BENDS) could be used to overcome the highly non linear correlations that occur with acoustic resonance spectroscopy (ARS) eliminating a major drawback with ARS to further promote the device as a possible process analytical technology (PAT) in the pharmaceutical industry. BENDS is an algorithm that has been created to calculate a reduced linear calibration model from highly non linear relationships with ARS spectra. ARS has been shown to correctly identify pharmaceutical tablets and with the incorporation of BENDS, determine the hydration amount of aspirin tablets, D-galactose contamination levels of Dtagatose powders and the D-tagatose concentrations in resveratrol/D-tagatose combinatory tablets.
Recommended Citation
Link, David John, "BOOTSTRAP ENHANCED N-DIMENSIONAL DEFORMATION OF SPACE WITH ACOUSTIC RESONANCE SPECTROSCOPY" (2009). University of Kentucky Doctoral Dissertations. 728.
https://uknowledge.uky.edu/gradschool_diss/728
