{"title":"Predicting Δ-9-Tetrahydrocannabinol-Induced Psychoactive and Cognitive Effects: A PBPK-PD Approach to Quantifying Feeling High and Reduced Alertness.","authors":"Lixuan Qian, Zhu Zhou","doi":"10.1021/acschemneuro.5c00417","DOIUrl":null,"url":null,"abstract":"<p><p>The increasing use of cannabis for medicinal and recreational purposes highlights the need to understand its psychoactive effects. Δ-9-tetrahydrocannabinol (THC), the primary psychoactive cannabinoid, is responsible for feeling high and reduced alertness after cannabis use. This study aimed to develop and verify physiologically based pharmacokinetic-pharmacodynamic (PBPK-PD) models to quantify the effects of THC and its active metabolite, 11-hydroxy-THC, on feeling high and reduction in alertness in healthy adults. The models were developed using Simcyp, based on our previously verified THC PBPK model. A direct response model with a maximum effect (<i>E</i><sub>max</sub>) function driven by the brain concentrations and an effect compartment was used to describe visual analogue scale (VAS) scores for feeling high after intravenous, oral, and inhaled THC administration. An indirect response model with an <i>E</i><sub>max</sub> function driven by the brain concentrations was used to describe the reduction in VAS alertness scores after inhaled THC. Our models accurately captured the dose-response relationships for THC doses ranging from 2 to 86 mg for feeling high, and 2 to 69.4 mg for alertness reduction. The verified PBPK-PD model provides a robust tool for predicting the psychoactive and cognitive effects of THC, enabling improved assessment of cannabis-induced responses across diverse populations.</p>","PeriodicalId":13,"journal":{"name":"ACS Chemical Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Chemical Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1021/acschemneuro.5c00417","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The increasing use of cannabis for medicinal and recreational purposes highlights the need to understand its psychoactive effects. Δ-9-tetrahydrocannabinol (THC), the primary psychoactive cannabinoid, is responsible for feeling high and reduced alertness after cannabis use. This study aimed to develop and verify physiologically based pharmacokinetic-pharmacodynamic (PBPK-PD) models to quantify the effects of THC and its active metabolite, 11-hydroxy-THC, on feeling high and reduction in alertness in healthy adults. The models were developed using Simcyp, based on our previously verified THC PBPK model. A direct response model with a maximum effect (Emax) function driven by the brain concentrations and an effect compartment was used to describe visual analogue scale (VAS) scores for feeling high after intravenous, oral, and inhaled THC administration. An indirect response model with an Emax function driven by the brain concentrations was used to describe the reduction in VAS alertness scores after inhaled THC. Our models accurately captured the dose-response relationships for THC doses ranging from 2 to 86 mg for feeling high, and 2 to 69.4 mg for alertness reduction. The verified PBPK-PD model provides a robust tool for predicting the psychoactive and cognitive effects of THC, enabling improved assessment of cannabis-induced responses across diverse populations.
期刊介绍:
ACS Chemical Neuroscience publishes high-quality research articles and reviews that showcase chemical, quantitative biological, biophysical and bioengineering approaches to the understanding of the nervous system and to the development of new treatments for neurological disorders. Research in the journal focuses on aspects of chemical neurobiology and bio-neurochemistry such as the following:
Neurotransmitters and receptors
Neuropharmaceuticals and therapeutics
Neural development—Plasticity, and degeneration
Chemical, physical, and computational methods in neuroscience
Neuronal diseases—basis, detection, and treatment
Mechanism of aging, learning, memory and behavior
Pain and sensory processing
Neurotoxins
Neuroscience-inspired bioengineering
Development of methods in chemical neurobiology
Neuroimaging agents and technologies
Animal models for central nervous system diseases
Behavioral research