预测 Δ-9-Tetrahydrocannabinol 诱导的精神活性和认知效应:一个 PBPK-PD 方法来量化感觉高和降低警觉
1Department of Chemistry, York College, City University of New York, Jamaica, New York 11451, United States.
ACS chemical neuroscience
|July 22, 2025
概括
开发了基于生理学的药理动力学-药理动力学 (PBPK-PD) 模型,以预测 Δ-9-四大麻素 (THC) 的精神活性效应. 这些模型准确地量化了THC如何通过不同的管理途径影响高和警觉的感觉.
科学领域:
- 药理学和毒理学 药理学和毒理学
- 计算建模 计算建模
- 大麻素研究 研究 大麻素研究
背景情况:
- 越来越多的医疗和娱乐大麻使用需要了解其精神活性作用.
- Δ-9-四大麻 (THC) 是大麻中主要的精神活性化合物,负责高兴度和警觉性降低.
- 量化THC的影响需要强大的预测模型.
研究的目的:
- 开发和验证THC及其活性代谢物11-基THC的生理学基础的药理动力学-药理动力学 (PBPK-PD) 模型.
- 量化THC对主观高警觉感和客观警觉降低的影响.
- 建立一个工具来预测大麻诱导的精神活性和认知效应.
主要方法:
- 使用了Simcyp软件,基于一个先前存在的经过验证的THC PBPK模型.
- 采用直接响应模型与Emax函数用于主观"感觉高"VAS分数 (IV,口服,吸入THC).
- 使用一个间接响应模型与一个Emax函数的客观警觉VAS得分 (吸入THC).
主要成果:
- 模型准确地捕获了THC对"感觉高" (2-86毫克) 影响的剂量反应关系.
- 模型准确地预测了THC对降低警觉 (2-69.4毫克) 的剂量反应.
- 经过验证的PBPK-PD模型显示出强大的预测能力.
结论:
- 开发的PBPK-PD模型提供了一种可靠的方法来预测THC的精神活性和认知效应.
- 这些模型可以帮助评估各种人群中大麻诱导的反应.
- 这项研究支持更好地了解THC对人类感知和认知的影响.
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