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相关概念视频

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

333
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
333
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

242
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...
242
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

1.9K
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
1.9K
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

249
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
249
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

335
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
335
Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

1.3K
Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
When administered orally, drugs establish a substantial concentration gradient between the gastrointestinal (GI) lumen and the bloodstream, expediting...
1.3K

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相关实验视频

Updated: Jan 17, 2026

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

Published on: February 23, 2018

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PharmacoForge:通过扩散模型生成药.

Emma L Flynn1,2, Riya Shah1, Ian Dunn1,2

  • 1Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, United States.

Frontiers in bioinformatics
|September 24, 2025
PubMed
概括
此摘要是机器生成的。

新的扩散模型PharmacoForge产生了基于结构的3D药,用于基于结构的药物设计. 这种方法产生了有效的,商业上可用的分子,提高了虚拟查效率和药物发现.

关键词:
计算机化药物发现.扩散模型的扩散模型生成型模型是一种生成型模型.分子生成分子的产生.作为一个药物学家,他做了一些药物学.基于结构的药物发现.虚拟选 虚拟选 虚拟选

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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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相关实验视频

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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
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Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro
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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

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科学领域:

  • 计算化学是一种计算化学.
  • 机器学习在药物发现中的作用

背景情况:

  • 基于结构的药物设计 (SBDD) 使用机器学习 (ML) 进行虚拟查和新设计.
  • 目前的ML方法在选速度和生成分子的合成可访问性方面存在局限性.

研究的目的:

  • 介绍PharmacoForge,这是一个扩散模型,用于生成蛋白质口袋上调节的3D药.
  • 通过生成有效的,商业上可用的连接体查询来改进虚拟选.
  • 解决现有的基于ML的药物设计策略的局限性.

主要方法:

  • 开发了PharmacoForge,这是一个条件扩散模型用于3D药生成.
  • 使用LIT-PCBA基准,对PharmacoForge进行了评估,并与自动制药生成进行了对比.
  • 通过对DUD-E数据集的回顾性选来评估生成的药.
  • 通过对接和应变能量分析,比较了PharmacoForge衍生的连接物与使用de novo生成的连接物.

主要成果:

  • 在LIT-PCBA基准测试中,PharmacoForge的表现优于现有的制药生成方法.
  • 通过PharmacoForge药识别的配体在对接研究中显示出与新设计的配体相似的性能.
  • 通过PharmacoForge产生的分子表现出比de novo设计的分子更低的应变能量.

结论:

  • PharmacoForge提供了一种有效的方法来生成3D药,增强基于结构的药物设计.
  • 该模型生成有效和合成可访问的分子查询,克服当前生成模型的局限性.
  • PharmacoForge代表了ML驱动药物发现的重大进步,提高了效率和可靠性.