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Title: Optimisation of analytical methods for the detection of cannabinoids and nicotine in hair
Author: Alzahrani, Farouq Faisal
ISNI:       0000 0004 6498 9049
Awarding Body: University of Glasgow
Current Institution: University of Glasgow
Date of Award: 2016
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Unlike conventional biological samples (blood and urine), hair samples have a much wider detection period and can provide a retrospective timeline of an individual’s drug use. However, the most crucial issue facing hair analysis is the avoidance of false-positive results caused by passive exposure to the drug. Passive exposure could be a result of direct contact with the consumed material or its smoke. This issue is of great concern especially with the drugs that have a greater potential for external contamination. Common examples of these are cannabis and nicotine, two drugs that are by far the most used drugs worldwide. The work presented in this thesis describes the development and validation of three analytical methods for cannabis and nicotine in hair matrices. These methods were then employed to analyse authentic hair samples and their washes. The first method involved liquid-liquid extraction (LLE) of the cannabinoids, Δ9- tetrahydrocannabinol (THC), cannabidiol (CBD), cannabinol (CBN) and metabolite 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC) from hair followed by analysis using standard gas chromatography-mass spectrometry (GC-MS). Cyclohexane: EtOAc (3/1, v/v) was found be the best extracting solvent for THC, CBD, CBN and 11-OH-THC. The percentage of extraction recovery for all four analytes ranged from 87.9% to 97.2%. The second method involved solid-phase extraction (SPE) of the main metabolite 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid (THC-COOH) from hair followed by analysis using two-dimensional gas chromatography-mass spectrometry (2D GC-MS). The SPE method provided a clean extract with an acceptable extraction recovery (approximately 50%). Authentic hair samples were then collected from 20 known cannabis users admitted to Al-Amal addiction hospital in Jeddah, Saudi Arabia. Cannabis users were interviewed at the time of sample collection and self-reported their cannabis use history. Concentrations of different cannabinoids were then measured using the validated methods. The aim of this project was to investigate the potential value of measuring cannabinoid concentrations in hair. The detected concentrations ranged from 0.11 to 0.34 ng/mg for THC, 0.2 to 4.42 ng/mg for 3 CBD, 0.31 to 1.02 for CBN, and 2.14 to 7.01 pg/mg for THC-COOH. Surprisingly, THC has a very low detection rate, whereas, CBD and THC-COOH had the highest detection rate of all cannabinoids. The relationship between measured concentrations and use history was then subject to statistical analysis. There was no significant correlation found between concentrations of cannabinoids in hair and the use history. The third method involved methanolic extraction of nicotine and cotinine from pet dogs’ fur followed by analysis by zwitterionic hydrophilic interaction liquid chromatography tandem mass spectrometry (ZICHILIC-MSMS). Further clean-up of the fur methanolic extract was found to be problematic. Centrifugation and direct analysis was found to be the best approach. The tandem MS allowed for low detection limits. The aim of this project was to investigate the association between dog fur nicotine and cotinine concentrations and owner-reported exposure to environmental tobacco smoke. 66 fur samples were collected from 41 dogs at two time points. Total nicotine and total cotinine were quantified in unwashed fur samples using the validated method. Statistical analysis revealed a significant difference in the mean concentrations of nicotine and cotinine in different exposure groups. By providing information on dog’s exposure to environmental tobacco smoke (ETS) over time, fur analysis may be useful in assessing dogs and companion owner’s histories of exposure to ETS.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: R Medicine (General) ; RA1001 Forensic Medicine. Medical jurisprudence. Legal medicine