AbstractDiazepam is an effective pharmaceutical used for both medicinal and illicit purposes and its popularity has led to the sale of both diverted pharmaceutical tablets and illicitly manufactured products. The aim of this project was to characterise 65 different cases of illicit tablets seized from the Tayside area. Physical and chemical analysis was compared with known pharmaceutical tablets and resulting data was statistically evaluated, to reveal potential links between illicit cases and distinguish pharmaceutically manufactured diverted products.
Physical differences between cases revealed many of the tablets were not pharmaceutically manufactured for the UK market. This was supported by chemical analysis using GC-MS and HPLC, which indicated that only 39 of the 63 cases analysed contained diazepam as the main active ingredient, with diazepam levels varying between 8 – 48 mg and more potent substances found in many tablets. An innovative use of DSC demonstrated great sensitivity in distinguishing between cases, based largely on excipients. A novel approach for forensic analysis was taken both through visual comparison of thermograms and by statistical analysis of resulting data.
The statistical clustering techniques of AHC and k-means were used to explore combined results and potential links between a subset of cases were visualised in a heat map. DSC data points were then explored by PCA and LDA to further distinguish between the pharmaceutical tablets and seized cases.
Overall, a combination of physical characteristics, chemical properties and statistical analysis were able to distinguish between the small number of pharmaceutically manufactured diverted cases and the majority revealed to be illicitly produced. This is important new research into street drugs, which reveals an insight into the illicit market and the dangerous nature of blue tablets being sold, providing valuable information to both police and medical services.
|Date of Award||25 May 2020|
|Supervisor||Isobel Stewart (Supervisor), Anne Savage (Supervisor) & David Bremner (Supervisor)|
- Physical characterisation
- Chemical properties
- Black market
- Principal component analysis
- Agglomerative hierarchical clustering
- Differential scanning calorimetry
- K-means clustering