| dc.description.abstract | Consumption of illegal drugs of abuse remains a major social issue aligned with a
global law-enforcement priority. Forensic analysts are faced with the challenge of
continually developing sophisticated methods of analysis to combat the increasing
variability that occurs in illicit drug samples. Research work for this thesis has
focused on the development of High Performance Liquid Chromatography (HPLC)
methods for the analysis of major drug constituents associated with ecstasy and
cocaine illicit drug samples. Emphasis has been placed on method development with
strategies of univariate or multivariate experimental approaches used in the selection
and optimisation of procedures. Considerations with regard to the choice of
chromatographic factors, solutes under investigation and the provision of quality
assurance data throughout the research work have been the main criteria in methods
developed. Two HPLC methods were developed to qualitatively and quantitatively
assay for the major drug components and analogue derivatives found in ecstasy and
cocaine. Methods developed have undergone validation studies including intra- and
inter- reproducibility, accuracy, and linearity of calibration, limit of detection (LOD)
and limit of quantification (LOQ) and the use of internal standards. Applications of
methods to ecstasy and cocaine samples seized in Ireland ensured their suitability for
routine analysis of illicit drug samples.
As part of this study, chemical profiling of 183 ecstasy tablets seized in Ireland during
2002-2004 were recorded as discrete data sets. Chemical data sets include both the
quantification and occurrence in individual tablets of the major amphetamine
components (i.e. MDA, MDMA, MDEA, MBDB methamphetamine and
amphetamine), adulterant components (i.e. caffeine, phenacetin, acetaminophen and
acetylsalicylic acid), excipients components (i.e. sucrose, glucose, lactose, fructose,
mannitol, sorbitol and inositol) and inorganic components (i.e. Al, Zn, Fe, Mg, Ca, Cr,
Pb, Na and K ). Chemometrics, including unsupervised methods of principal
component analysis (PCA), hierarchical cluster analysis (HCA) and Pearson’s
correlation coefficient, as well as supervised methods of linear discriminant analysis
(LDA) and artificial neural networks (ANN) was applied to the chemical data sets to
demonstrate the ability of the statistical approach to linking sample seizures. HCA
and ANN were the numerical methods that most efficiently distinguished between
5HPLC method development & chemometric analysis of ecstasy & cocaine
linked and unlinked seizures. Eleven groups were identified from the chemical data
sets with group classification dependant on the main amphetamine, adulterant and
excipient components present. The benefits from this study can provide strategic
intelligence and an understanding of the operational level on the Irish ecstasy market
and help evaluate the changing profile or dynamics associated with this illegal market
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