The medical use of marijuana is increasing, yet little is known about the exposure-response relationships resulting in its psychoactive effects. Δ9-tetrahydrocannabinol (THC) and its active metabolite (11-hydroxy-THC; THC-OH) are the principal psychoactive components in marijuana. It is well known that the plasma concentrations of the psychoactive components of marijuana do not directly relate to the observed psychoactive effects. The presence of a counter-clockwise hysteresis in the plasma concentrations-effect plot demonstrates a temporal delay between the plasma concentrations and observed effect following the intravenous administration of THC. The overarching objective of this research was to better understand the relationship between the plasma and brain concentrations of the psychoactive components (THC and THC-OH) and the observable psychoactive effects after intravenous administration of THC, utilizing model-based approaches. Specifically, the pharmacokinetics were explored using population pharmacokinetic (Pop PK) and physiologically-based pharmacokinetic (PBPK) modeling whereas the pharmacodynamics (PD) of the psychoactive effect (“highness”) were explored using effect-compartment modeling and linking the PD to the PBPK-derived concentrations predicted in the brain and an assumed effect-site. A “hypothetical” effect compartment model was developed to characterize the observed delay in peak “highness” ratings. A direct relationship was established between the reported psychoactive effects (“highness” or intoxication) and the predicted effect-site concentrations of both components (THC and THC-OH) using this effect-compartment modeling approach. The faster plasma to effect compartment equilibration for THC-OH indicated a more rapid equilibration of the active metabolite between plasma and the effect-site (biophase) than for the parent THC. In addition, a PBPK modeling approach was pursued to predict and relate the brain concentrations of THC and THC-OH to the psychoactive effect. The relationship between the effect and the predicted unbound brain concentration of THC indicated an indirect relationship, suggesting a temporal delay between brain concentrations of THC and observed effect. However, a direct relationship was observed between the observed effect and the unbound brain THC-OH concentrations. In addition, the unbound concentrations of THC-OH in the brain were predicted to be higher than the corresponding THC concentrations. These findings highlight the importance for the inclusion of THC-OH, in addition to THC, when relating the observed effect to the concentrations of the psychoactive components of marijuana. These models contribute to the understanding of the PK-PD relationships associated with marijuana use and are important steps in the prediction of the pharmacodynamic effects related to the psychoactive components in marijuana and establish an approach for investigating other THC-related effects.

Electrochemical biosensors are renowned for their ability to detect a wide range of analytes in biological fluids for clinical diagnosis. The implementation of biomarkers in electrochemical biosensors for clinical diagnosis is essential for the specific and accurate diagnosis of the disease with high sensitivity and selectivity. Therefore, this thesis evaluates the challenges pertaining to the stability, reproducibility, and obtaining a low limit of detection for the internal/external biomarkers associated with two distinct electrochemical biosensors. The first study tackles the challenge of detecting low analyte concentrations in a label-free biosensor. It introduces an innovative label-free electrochemical biosensing method for the detection of glycosylated hemoglobin (HbA1c) and C-reactive protein (CRP) to predict Coronary Heart Disease (CHD) progression using tailored redox probes, proposing a dual biomarker biosensing platform for future research. Calibration curves reveal an LOD of 5 mg/mL in PBS (8) FeCN (II) and 6 mg/mL in SB for a linear range of 0 – 30 mg/mL of HbA1c. Similarly, an LOD of 0.007 mg/mL and 0.008 mg/mL in PBS (7.4) PcA-NO2 and SB, respectively, is reported for a linear range of 0 – 0.05 mg/mL of CRP. The second study focuses on stabilizing a biomolecule-free sensor for the ultra-low detection of Δ9-tetrahydrocannabinol (THC) in roadside testing. Pre-depositing THC, an external biomarker for drug-impaired driving, onto the biosensor's working electrode enhances its interaction with analytes. However, THC's oxidative nature compromises sensor stability during manufacturing. Consequently, optimal electrode storage conditions were explored, indicating frozen storage as ideal for up to six months, effectively preventing THC oxidation at -18°C, while degradation occurs at 4°C. Modified electrodes stored under optimal conditions exhibit improved calibration curves when exposed to various THC samples. / Thesis / Master of Applied Science (MASc) / An electrochemical biosensor is a sensing device with the ability to detect biological species via the transduction of a specific biological event into electrochemical signals. These sensors are extremely useful for the detection of analytes in biological fluids for clinical diagnostics, to determine the presence or absence of diseases. This manuscript addresses the challenges associated with the stability, reproducibility, and the low limits of detection associated with screen-printed carbon electrodes used in electrochemical biosensing. Subsequently, due to the strong correlation between glycated hemoglobin (HbA1c) and C-reactive protein (CRP) to connote the risk of contracting coronary heart disease (CHD), the manuscript presents a novel label-free electrochemical biosensing method for the detection of HbA1c and CRP with low detection limits. Secondly, the manuscript identifies ambient storage conditions for the long-term stability of a biomolecule-free sensing device for the roadside detection of ultra-low concentrations of Δ9-tetrahydrocannabinol (THC).