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相关概念视频

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

129
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...
129
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

152
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.
152
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

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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...
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Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

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Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
167
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

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

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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...
154
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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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...
114

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Updated: Sep 15, 2025

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机器学习使纳米粒子边缘化和基于生理学的药理动力学的多尺度模型成为可能.

Sahil Kulkarni1, Benjamin Lin2,3, Ravi Radhakrishnan1,3

  • 1University of Pennsylvania, Chemical and Biomolecular Engineering, Philadelphia, 19104, PA, USA.

Computers & chemical engineering
|July 14, 2025
PubMed
概括

这项研究引入了一种多尺度模型,用于预测纳米粒子行为和生物分布,用于向药物输送. 它将流体动力学与药物动力学建模相结合,用于增强治疗应用.

关键词:
在DeepONet的深度网络.福克斯·普朗克 (Fokker 普朗克) 是一个血中克里特是什么意思 血中克里特是什么意思边缘化 边缘化 边缘化纳米颗粒 纳米颗粒PBPKK PBPK 的意思是什么意思

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相关实验视频

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科学领域:

  • 生物医学工程 生物医学工程
  • 计算生物学 计算生物学
  • 纳米技术纳米技术

背景情况:

  • 纳米粒子 (NP) 行为和生物分布对于向药物输送至关重要.
  • 准确的预测需要将血液流动动力学与全身药理动力学相结合.
  • 现有的模型往往缺乏复杂生物系统所需的多尺度集成.

研究的目的:

  • 开发和验证一个模拟纳米粒子行为和生物分布的多尺度建模框架.
  • 为了预测红细胞不含层 (RBCFL) 中的纳米粒子边缘化和度概况.
  • 使用生理学基础的药理动力学 (PBPK) 建模,以告知器官间纳米粒子生物分布.

主要方法:

  • 将一个支持DeepONet的福克-普朗克方程与血液学模型结合起来,以模拟RBCFL中的NP漂移扩散.
  • 使用血位和血管半径作为NP边缘和度概况预测的输入.
  • 将预测的微血管NP度集成到PBPK模型中,以评估全身生物分布.

主要成果:

  • 该框架成功模拟了RBCFL中的NP漂移扩散和边缘化.
  • 预测的NP度概况准确地为PBPK模型提供信息.
  • 多尺度方法提供了NP生物分布的全面预测.

结论:

  • 开发的多尺度建模框架能够准确地模拟和预测纳米粒子的行为和生物分布.
  • 这种方法提高了基于纳米粒子的向药物递送系统的设计和有效性.
  • 综合建模策略为纳米药物的临床前评估提供了一个强大的工具.