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相关概念视频

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

78
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
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Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

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Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
268
Opioid Analgesics: Synthetic and Semisynthetic Opioids01:15

Opioid Analgesics: Synthetic and Semisynthetic Opioids

311
Synthetic and semisynthetic opioids are pivotal in pain management and tackling opioid addiction. Semisynthetic opioids, including morphinans (morphine derivatives), oxycodone, oxymorphone, hydrocodone, and hydromorphone, have improved pharmacokinetic profiles compared to morphine. Additionally, heroin and 6-MAM (6-Monoacetylmorphine) show better CNS penetration than morphine due to heightened lipid solubility. Hydromorphone, a potent opioid, undergoes hepatic metabolism to form the active...
311
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

112
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
112
Drug Distribution as One-Compartment Model and Elimination by Nonlinear Pharmacokinetics: Overview01:25

Drug Distribution as One-Compartment Model and Elimination by Nonlinear Pharmacokinetics: Overview

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Drug administration can occur through various routes, each of which may result in a different process of elimination. This process is often mixed with nonlinear and linear processes. It's important to understand that a single drug can be metabolized into different metabolites through parallel processes.
For instance, consider the metabolism of sodium salicylate. This compound is metabolized into two distinct substances: a glucuronide and a glycine conjugate. The rate of conjugation depends...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
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High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
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一个个别细分的轨迹方法用于识别阿片类药物使用模式,使用纵向发行数据.

Stanley Xu1,2, Komal J Narwaney3, Anh P Nguyen3

  • 1Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.

Pharmacoepidemiology and drug safety
|October 10, 2023
PubMed
概括

这项研究引入了一种新方法,从发行数据中识别出13种不同的阿片类药物使用模式. 这些模式可以帮助研究人员了解阿片类药物使用与药物过量风险之间的联系.

关键词:
变化系数的变化系数降低剂量减少剂量个别的细分轨迹的轨迹.长期的阿片类药物治疗处方阿片类药物的处方过量服用过量服用过量

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科学领域:

  • 药理学和毒理学 药理学和毒理学
  • 数据科学和分析数据科学和分析
  • 公共卫生和流行病学

背景情况:

  • 阿片类药物使用障碍对公共卫生构成重大挑战.
  • 了解个人阿片类药物使用轨迹对于风险评估至关重要.
  • 电子健康记录为分析药物使用模式提供了丰富的数据.

研究的目的:

  • 为确定阿片类药物使用模式开发个别细分轨迹方法.
  • 利用电子阿片类药物分发数据进行模式识别.
  • 为了能够检查已识别的阿片类药物使用模式和药物过量服用之间的关联.

主要方法:

  • 长期阿片类药物治疗 (LTOT) 成员 (≥18年) 在三个美国医疗保健系统 (2006-2019) 的回顾性队列研究.
  • 使用纵向分配数据开发一个单独的细分轨迹分析.
  • 基于变化 (变化系数) 和趋势 (毫克吗啡等价物) 的模式识别.

主要成果:

  • 对31,865名LTOT成员的分析,随访时间为152,557人年.
  • 确定了13种不同的阿片类药物使用模式,包括"稳定" (42.1%) 和"增加" (13.8%) 模式.
  • 量化各种剂量减少模式,范围从≤10%到>30%.

结论:

  • 一种新的方法成功地从个人纵向分发数据中识别出13种不同的阿片类药物使用模式.
  • 这些已识别的模式为在特定时期的阿片类药物使用中检查过量风险提供了基础.
  • 该方法为公共卫生研究提供了对阿片类药物使用动态的细粒度理解.