Literature DB >> 25316574

Population pharmacokinetic model of THC integrates oral, intravenous, and pulmonary dosing and characterizes short- and long-term pharmacokinetics.

Jules A A C Heuberger1, Zheng Guan, Olubukayo-Opeyemi Oyetayo, Linda Klumpers, Paul D Morrison, Tim L Beumer, Joop M A van Gerven, Adam F Cohen, Jan Freijer.   

Abstract

Δ(9)-Tetrahydrocannobinol (THC), the main psychoactive compound of Cannabis, is known to have a long terminal half-life. However, this characteristic is often ignored in pharmacokinetic (PK) studies of THC, which may affect the accuracy of predictions in different pharmacologic areas. For therapeutic use for example, it is important to accurately describe the terminal phase of THC to describe accumulation of the drug. In early clinical research, the THC challenge test can be optimized through more accurate predictions of the dosing sequence and the wash-out between occasions in a crossover setting, which is mainly determined by the terminal half-life of the compound. The purpose of this study is to better quantify the long-term pharmacokinetics of THC. A population-based PK model for THC was developed describing the profile up to 48 h after an oral, intravenous, and pulmonary dose of THC in humans. In contrast to earlier models, the current model integrates all three major administration routes and covers the long terminal phase of THC. Results show that THC has a fast initial and intermediate half-life, while the apparent terminal half-life is long (21.5 h), with a clearance of 38.8 L/h. Because the current model characterizes the long-term pharmacokinetics, it can be used to assess the accumulation of THC in a multiple-dose setting and to forecast concentration profiles of the drug under many different dosing regimens or administration routes. Additionally, this model could provide helpful insights into the THC challenge test used for the development of (novel) compounds targeting the cannabinoid system for different therapeutic applications and could improve decision making in future clinical trials.

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Year:  2015        PMID: 25316574     DOI: 10.1007/s40262-014-0195-5

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  33 in total

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Review 2.  Pharmacology and effects of cannabis: a brief review.

Authors:  C H Ashton
Journal:  Br J Psychiatry       Date:  2001-02       Impact factor: 9.319

3.  Surinabant, a selective cannabinoid receptor type 1 antagonist, inhibits Δ9-tetrahydrocannabinol-induced central nervous system and heart rate effects in humans.

Authors:  Linda E Klumpers; Christine Roy; Geraldine Ferron; Sandrine Turpault; Franck Poitiers; Jean-Louis Pinquier; Johan G C van Hasselt; Lineke Zuurman; Frank A S Erwich; Joop M A van Gerven
Journal:  Br J Clin Pharmacol       Date:  2013-07       Impact factor: 4.335

4.  Does intravenous Δ9-tetrahydrocannabinol increase dopamine release? A SPET study.

Authors:  Emma Barkus; Paul D Morrison; D Vuletic; John C Dickson; Peter J Ell; Lyn S Pilowsky; Rudolf Brenneisen; David W Holt; John Powell; Shitij Kapur; Robin M Murray
Journal:  J Psychopharmacol       Date:  2010-09-17       Impact factor: 4.153

5.  Determination and characterization of a cannabinoid receptor in rat brain.

Authors:  W A Devane; F A Dysarz; M R Johnson; L S Melvin; A C Howlett
Journal:  Mol Pharmacol       Date:  1988-11       Impact factor: 4.436

6.  Concentration-effect relationship of delta-9-tetrahydrocannabiol and prediction of psychotropic effects after smoking marijuana.

Authors:  S Harder; S Rietbrock
Journal:  Int J Clin Pharmacol Ther       Date:  1997-04       Impact factor: 1.366

7.  Marijuana effect and delta-9-tetrahydrocannabinol plasma level.

Authors:  C W Chiang; G Barnett
Journal:  Clin Pharmacol Ther       Date:  1984-08       Impact factor: 6.875

8.  Manipulating brain connectivity with δ⁹-tetrahydrocannabinol: a pharmacological resting state FMRI study.

Authors:  Linda E Klumpers; David M Cole; Najmeh Khalili-Mahani; Roelof P Soeter; Erik T Te Beek; Serge A R B Rombouts; Joop M A van Gerven
Journal:  Neuroimage       Date:  2012-08-01       Impact factor: 6.556

9.  Opposite effects of delta-9-tetrahydrocannabinol and cannabidiol on human brain function and psychopathology.

Authors:  Sagnik Bhattacharyya; Paul D Morrison; Paolo Fusar-Poli; Rocio Martin-Santos; Stefan Borgwardt; Toby Winton-Brown; Chiara Nosarti; Colin M O' Carroll; Marc Seal; Paul Allen; Mitul A Mehta; James M Stone; Nigel Tunstall; Vincent Giampietro; Shitij Kapur; Robin M Murray; Antonio W Zuardi; José A Crippa; Zerrin Atakan; Philip K McGuire
Journal:  Neuropsychopharmacology       Date:  2009-11-18       Impact factor: 7.853

10.  The acute effects of synthetic intravenous Delta9-tetrahydrocannabinol on psychosis, mood and cognitive functioning.

Authors:  P D Morrison; V Zois; D A McKeown; T D Lee; D W Holt; J F Powell; S Kapur; R M Murray
Journal:  Psychol Med       Date:  2009-04-01       Impact factor: 7.723

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  11 in total

1.  Toward a comprehensive model of ∆(9)-tetrahydrocannabinol pharmacokinetics using a population pharmacokinetics approach.

Authors:  Brett C Ginsburg
Journal:  Clin Pharmacokinet       Date:  2015-02       Impact factor: 6.447

2.  Population pharmacokinetic modeling of plasma Δ9-tetrahydrocannabinol and an active and inactive metabolite following controlled smoked cannabis administration.

Authors:  Cristina Sempio; Marilyn A Huestis; Susan K Mikulich-Gilbertson; Jost Klawitter; Uwe Christians; Thomas K Henthorn
Journal:  Br J Clin Pharmacol       Date:  2020-01-20       Impact factor: 4.335

Review 3.  A marijuana-drug interaction primer: Precipitants, pharmacology, and pharmacokinetics.

Authors:  Emily J Cox; Neha Maharao; Gabriela Patilea-Vrana; Jashvant D Unadkat; Allan E Rettie; Jeannine S McCune; Mary F Paine
Journal:  Pharmacol Ther       Date:  2019-05-07       Impact factor: 12.310

Review 4.  Cannabinoids for Symptom Management in Patients with Kidney Failure: A Narrative Review.

Authors:  Hayley Worth; Daniel V O'Hara; Neeru Agarwal; David Collister; Frank Brennan; Brendan Smyth
Journal:  Clin J Am Soc Nephrol       Date:  2022-01-05       Impact factor: 10.614

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

Authors:  Zheng Liu; Jennifer H Martin
Journal:  Br J Clin Pharmacol       Date:  2018-06-07       Impact factor: 4.335

Review 6.  Pharmacokinetics of Cannabis in Cancer Cachexia-Anorexia Syndrome.

Authors:  Stephanie E Reuter; Jennifer H Martin
Journal:  Clin Pharmacokinet       Date:  2016-07       Impact factor: 6.447

Review 7.  The pharmacokinetics and the pharmacodynamics of cannabinoids.

Authors:  Catherine J Lucas; Peter Galettis; Jennifer Schneider
Journal:  Br J Clin Pharmacol       Date:  2018-08-07       Impact factor: 4.335

8.  Pharmacokinetic and Pharmacodynamic Characterization of Tetrahydrocannabinol-Induced Cannabinoid Dependence After Chronic Passive Cannabis Smoke Exposure in Rats.

Authors:  Abhigyan Ravula; Hardik Chandasana; Darin Jagnarine; Shannon C Wall; Barry Setlow; Marcelo Febo; Adriaan W Bruijnzeel; Hartmut Derendorf
Journal:  Cannabis Cannabinoid Res       Date:  2019-12-06

9.  Food effects on the formulation, dosing, and administration of cannabidiol (CBD) in humans: A systematic review of clinical studies.

Authors:  Lucy H Silmore; Andrew R Willmer; Edmund V Capparelli; Gus R Rosania
Journal:  Pharmacotherapy       Date:  2021-03-18       Impact factor: 4.705

10.  Using Population Pharmacokinetic Modeling to Estimate Exposure to Δ9-Tetrahydrocannabinol in an Observational Study of Cannabis Smokers in Colorado.

Authors:  Cristina Sempio; L Cinnamon Bidwell; Kent Hutchison; Marilyn A Huestis; Jost Klawitter; Uwe Christians; Thomas K Henthorn
Journal:  Ther Drug Monit       Date:  2021-08-01       Impact factor: 3.118

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