Population pharmacokinetics model of THC used by pulmonary route in occasional cannabis smokers

Measuring the diversity gap of cannabis clinical trial participants compared to people who report using cannabis

Little is known about the demographics of people who use cannabis, including how use trends within population subgroups have evolved over time. It is therefore challenging to know if the demographics of participants enrolled in cannabis clinical trials are representative of those who use cannabis. To fill this knowledge gap, data from the National Survey on Drug Use and Health (NSDUH) on "past-month" cannabis use across various population subgroups in the United States was examined from 2002 to 2021. The most notable increases in "past-month" cannabis use prevalence occurred in those aged 65 and older (2,066.1%) and 50-64-year-olds (472.4%). In 2021, people reporting "past-month" cannabis use were 56.6% male and 43.4% female. Distribution across self-reported race and ethnicity was 64.1% White, 14.3% Black, 14.1% Hispanic, and 3.1% more than one race. And many ages were represented as 24.4% were 26-34, 24.1% were 35-49, 22.4% were 18-25, and 17.6% were 50-64 years old. To understand if these population subgroups are represented in cannabis clinical trials, participant demographics were extracted from peer-reviewed clinical trials reporting on pharmacokinetic and/or pharmacodynamic models of cannabis or cannabinoids. Literature was grouped by publication year (2000-2014 and 2015-2022) and participant prior exposure to cannabis. Results identified that cannabis clinical trial participants are skewed toward overrepresentation by White males in their 20s and 30s. This represents structural discrimination in the research landscape that perpetuates social and health inequities.

Assessment of delta-9-tetrahydrocannabinol (THC) in saliva and blood after oral administration of medical cannabis with respect to its effect on driving abilities

Medical cannabis has recently been legalized in many countries, and it is currently prescribed with increasing frequency, particularly for treatment of chronic pain resistant to conventional therapy. The psychoactive substance delta-9-tetrahydro-cannabinol (THC) contained in cannabis may affect driving abilities. Therefore, the aims of this study (open-label, monocentric, nonrandomized) were to evaluate blood and saliva concentrations of THC after oral administration of medical cannabis and to assess the time needed for THC levels to decline below a value ensuring legal driving. The study involved 20 patients with documented chronic pain using long-term medical cannabis therapy. They were divided into two groups and treated with two different doses of cannabis in the form of gelatin capsules (62.5 mg or 125 mg). In all patients, the amount of THC was assessed in saliva and in blood at pre-defined time intervals before and after administration. THC levels in saliva were detected at zero in all subjects following administration of both doses at all-time intervals after administration. Assessment of THC levels in blood, however, showed positive findings in one subject 9 h after administration of the lower dose and in one patient who had been given a higher dose 7 h after administration. Our finding suggested that for an unaffected ability to drive, at least 9-10 h should elapse from the last cannabis use.

A Δ9-Tetrahydrocannabinol Physiologically-Based Pharmacokinetic Model Development in Humans

BACKGROUND AND OBJECTIVE

∆⁹-Tetrahydrocannabinol (THC) exhibits several therapeutic effects, such as analgesics, anti-emetic, antispastic, and muscle relaxation properties. Knowledge concerning THC disposition in target organs is crucial for THC therapy. The objective of this study was to develop a physiologically-based pharmacokinetic (PBPK) model of THC in humans to characterize tissue-specific pharmacokinetics of THC in organs of interest.

METHODS

The model was extrapolated from the previously developed PBPK model conducted in mice, rats, and pigs. The model consisted of seven compartments: brain, lungs, liver, kidneys, fat, and rapidly perfused and slowly perfused tissues. P-glycoprotein was included in the brain compartment to characterize an efflux of THC from the brain. Physiologic, biochemical, and physicochemical parameters were determined and acquired from the literature. Model validation was performed by comparisons of the predicted and observed THC concentrations acquired from published studies.

RESULTS

The developed PBPK model resulted in good agreement between the predicted and observed THC concentrations across several studies conducted following IV bolus, IV infusion, oral, and smoking and inhalation, with the coefficient of determination (R²) ranging from 0.54 to 0.95.

CONCLUSIONS

A PBPK model of THC in humans was developed. The model could describe THC concentration-time profiles in several dosing scenarios (i.e., IV bolus, IV infusion, oral administration and inhalation).

Influences of puff protocols and upper airway anatomy on cannabis pharmacokinetics: A CFPD-PK study

Predicting the optimal administration doses of the inhaled Δ9-tetrahydrocannabinol (THC), i.e., one of the major natural compounds in cannabis, is critical for maximizing the therapeutic outcomes and minimizing the toxic side effects. Thus, it is essential to developing an aerosol dosimetry model to simulate the transport, deposition, and translocation of inhaled THC aerosols from the human respiratory system to the systemic region. In this study, a computational fluid-particle dynamics (CFPD) plus pharmacokinetics (PK) model was developed and validated to quantify the localized vapor and particle uptake rates of THC and the resultant THC-plasma concentrations using two human upper airway geometries. In addition, two different puff protocols (4.0/10.0 s and 1.6/11.4 s as the inhalation/holding time ratios) were employed, associated with two different inhaled THC doses (2.0 mg and 8.82 mg, respectively). The computational results demonstrated that multiple parameters had noticeable influences on THC particle deposition and vapor absorption in the upper airways, as well as the resultant pharmacokinetic behaviors. These factors include anatomical features of the upper airway, puff flow rate, duration, and holding time. The results indicated that puff protocol with 4.0/10.0 s inhalation/holding time ratio would be recommended if the treatment needs THC delivery to the deeper lung. Furthermore, the inhaled THC dose had a dominant effect on the THC-plasma PK profiles, which could override the influences of anatomical variability and puff protocols. The developed CFPD-PK modeling framework has the potential to provide localized lung absorption data and PK profiles for in vitro-in vivo correlation, as well as supporting the development and assessment of drug products containing cannabis or cannabis-derived compounds.

Δ9-tetrahydrocannabinol (THC) is present in the body between smoking sessions in occasional non-daily cannabis users

BACKGROUND

THC can be measured in blood up to a month after last intake in heavy cannabis users. The cognitive deficits during abstinence have been hypothesized to be at least in part due to residual THC in brain. To which extent THC accumulation will occur after occasional cannabis use has gained limited attention. We aimed to predict THC-levels between smoking sessions in non-daily as well as daily cannabis users and to compare these predictions with published THC levels.

METHODS

Predictions were based on pharmacokinetic principles on drug accumulation after repeated dosing, applied to different cannabis smoking patterns, using data from a three-compartment model for THC pharmacokinetics and results on the terminal elimination half-life of THC in humans. We searched the literature for THC measurements which could be compared with these predictions. We found no such results from controlled studies of long-term repeated cannabis consumption of known THC amounts. Thirteen published studies contained, however, enough information on cannabis use and results from THC-measurements to make tentative comparisons with the predictions.

RESULTS

The predictions of THC-plasma levels present after different cannabis smoking patterns assuming terminal elimination half-lives of THC of 21.5 h or longer, had some support in published THC levels measured in individuals self-reporting their cannabis consumption. We found no consistent discrepancies between the predictions and reported THC plasma levels after non-daily or daily cannabis use. The predictions indicate that THC might be present in plasma between smoking sessions above usual analytical limits when smoking every third and second day, and at lower levels after once weekly smoking.

CONCLUSIONS

The study indicates that THC might be present continuously even in non-daily smokers at low levels, even if the smoking occasions are separated by a week. This is different from alcohol, where ethanol has disappeared after a day. From a toxicological point of view the persistance of THC in the brain, raises questions whether this should be given more attention as with other toxicological thinking where long-term presence of bioactive substances gives rise to concern. There are some uncertainties in this analysis, and controlled studies on THC-accumulation accompanying different use patterns seem warranted.

Minimal Physiologically Based Pharmacokinetic Model of Intravenously and Orally Administered Delta-9-Tetrahydrocannabinol in Healthy Volunteers

BACKGROUND AND OBJECTIVES

Lack of information on the pharmacokinetics of the active moiety of Cannabis or the metabolites of delta-9-tetrahydrocannabinol (THC) does not seem to be discouraging medical or recreational use. Cytochrome P450 (CYP) 2C9, the primary enzyme responsible for THC metabolism, has two single nucleotide polymorphisms-Arg144Cys (*2) and Ile359Leu (*3). In the Caucasian population, allelic frequency is between 0.08 and 0.14 for CYP2C9*2 and between 0.04 and 0.16 for CYP2C9*3. In vitro data suggest that metabolic capacity for the variants CYP2C9*2 and CYP2C9*3 is about one-third compared to wild-type CYP2C9. Previous work has suggested exposure to the terminal metabolite is genetically determined. We therefore sought to characterize the pharmacokinetics of THC and its major metabolites 11-hydroxy-delta-9-tetrahydrocannabinol (THC-OH) and 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH) in healthy volunteers with known CYP2C9 status by non-compartmental analysis (NCA), compartmental modeling (CM) and minimal physiologically based pharmacokinetic (mPBPK) modeling.

METHODS

Blood samples drawn for THC, THC-OH and THC-COOH after a single intravenous (IV) bolus of 0.1 mg/kg (0.32 μM/kg) THC were analyzed using a validated LC-MS/MS method. NCA generated initial estimates and CM and the mPBPK model were then fit to plasma concentration data using non-linear mixed-effects modeling. Blood samples from orally dosed (10, 25 and 50 mg) THC brownies were added to validate the model.

RESULTS

THC can be described as a high hepatic extraction ratio drug with blood flow-dependent metabolism not restricted by protein binding. THC hepatic clearance is dependent on the CYP2C9 genetic variant in the population. High extraction drugs display route-dependent metabolism. When administered via the IV or inhalation routes, induction or inhibition of CYP2C9 should be non-contributory as the elimination of THC is dependent only on liver blood flow. THC-OH is also a high extraction ratio drug, but its hepatic clearance is significantly impacted by the hepatic diffusional barrier that impedes its access to hepatic CYP2C9. THC-COOH is glucuronidated and renally cleared; subjects homozygous for CYP2C9*3 have reduced exposure to this metabolite as a result of the polymorphism reducing THC production, the hepatic diffusional barrier impeding egress from the hepatocyte, and increased renal clearance.

CONCLUSION

It has recently been reported that the terminal metabolite THC-COOH is active, implying the exposure difference in individuals homozygous for CYP2C9*3 may become therapeutically relevant. Defining the metabolism of THC in humans is important, as it is increasingly being used as a drug to treat various diseases and its recreational use is also rising. We have used NCA, CM, and mPBPK modeling of THC and its metabolites to partially disentangle the complexity of cannabis disposition in humans.

Gaps in predicting clinical doses for cannabinoids therapy: Overview of issues for pharmacokinetics and pharmacodynamics modelling

Model-based prediction on clinical doses for cannabinoids therapy is beneficial in the clinical setting, especially for seriously ill patients with both altered pharmacokinetics and pharmacodynamic responses. The objective of this article is to review the currently available PK and/or PD models of Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) and to highlight the major issues for modelling this complex therapeutic area. A systematic search was conducted in the electronic databases PubMed and EMBASE using the key words 'cannabis', 'cannabinoid', 'tetrahydrocannabinol', 'THC', 'cannabidiol', 'CBD', 'pharmacokinetic model', 'pharmacodynamics model' and their combinations. Twelve empirical PK and/or PD models for THC for humans were identified. Among them, ten were developed from data of healthy participants and two were from ill patients. Models for CBD were not found. Model-based prediction on appropriate doses for cannabinoids therapy for ill patients is currently limited due to insufficiency of relevant PK and PD data. High-quality PK and PD data of cannabinoids for patients with different illnesses is needed for model development. Mechanism-based PK and PD models are promising for improved predictive dosing performance for ill and comorbid patients.

Medical cannabis in the treatment of cancer pain and spastic conditions and options of drug delivery in clinical practice

The use of cannabis for medical purposes has been recently legalised in many countries including the Czech Republic. As a result, there is increased interest on the part of physicians and patients in many aspects of its application. This mini review briefly covers the main active substances of the cannabis plant and mechanisms of action. It focuses on two conditions, cancer pain and spasticity in multiple sclerosis, where its effects are well-documented. A comprehensive overview of a few cannabis-based products and the basic pharmacokinetics of marijuana's constituents follows. The review concludes with an outline for preparing cannabis (dried inflorescence) containing drug dosage forms that can be produced in a hospital pharmacy.