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相关概念视频

Time Course of Drug Effect01:14

Time Course of Drug Effect

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The progression of a drug's impact can be analyzed by examining both the concentration-time course and the effect-time course. The concentration-time course is determined by the drug's half-life and is influenced by factors such as its pharmacokinetics, including absorption, distribution, metabolism, and elimination. The effect of the drug is often related to its concentration in the plasma and is calculated using the maximum drug effect and the plasma concentration that generates 50...
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Dose-Response Relationship: Overview01:03

Dose-Response Relationship: Overview

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Agonists can bind with and activate receptors, resulting in the formation of drug-receptor complexes. Once formed, these complexes catalyze many biochemical processes at the cellular level and subsequently induce a pharmacologic response. The degree of response is directly proportional to the fraction of activated receptors, which in turn, depends on the concentration of the drug at the receptor site as well as the sensitivity of the receptor. An increase in the administered dose contributes to...
4.7K
Agonism and Antagonism: Quantification01:14

Agonism and Antagonism: Quantification

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When drugs are administered, they can elicit either an agonist or antagonist effect on the body. Agonism occurs when a drug activates a specific receptor, triggering a biological response. On the other hand, antagonism happens when a drug binds to the same receptors but blocks their activation, thereby preventing a biological response.
To quantify these effects, researchers use a dose-response curve, which provides valuable information about the potency and efficacy of a drug. Potency refers to...
939
Dose Size and Dosing Frequency: Determination Methods01:21

Dose Size and Dosing Frequency: Determination Methods

244
Determining the optimal dose size and dosing frequency in pharmacotherapy is crucial for achieving therapeutic effectiveness while minimizing adverse effects. This article explores the methodologies employed in determining these parameters, focusing on their significance and interplay to tailor dosing regimens.Dose Size: Dose size refers to the amount of a drug administered in a single dose. It is determined based on the drug's pharmacodynamics and pharmacokinetics properties and...
244
Drug Classes and Categories01:25

Drug Classes and Categories

2.8K
Drugs can be classified according to their chemical composition or their intended therapeutic application. For instance, anti-infective agents that possess the ability to eliminate pathogens or suppress their growth and reproduction can be grouped based on the organisms they target or their chemical structure. Furthermore, drugs can be divided into prescription, nonprescription, or controlled substances. Prescription medications, such as antibiotics, require oversight from a licensed healthcare...
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Effects of Chemicals: Overview01:27

Effects of Chemicals: Overview

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Drugs, encompassing various chemical compounds from natural sources, lab synthesis, or genetic engineering, elicit different biological responses in living organisms. Some of these responses are desirable or therapeutic, while others are undesirable. The primary goal of administering a drug is to achieve a therapeutic effect, that is, to address a specific disease or health condition. Any concurrent effects outside of this therapeutic outcome are considered undesirable. These undesirable...
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Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
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使用基于频率的图形横向方法对药物效应进行分类.

Aishik Chanda, Ashmita Dey, Mrittika Chakraborty

    IEEE transactions on computational biology and bioinformatics
    |December 26, 2025
    PubMed
    概括

    这项研究引入了一种基于图表的新方法,用于将药物分类为症状或疾病修饰,改善药物重新用途. 该方法识别了药物疾病通路中的关键基因,以便进行准确的分类和解释性.

    科学领域:

    • 计算生物学是一种计算生物学.
    • 药理学 药理学是指药理学的学科.
    • 网络科学 网络科学

    背景情况:

    • 将药物分类为症状性 (SYM) 或疾病修饰性 (DM) 对于理解治疗效果和药物重新用途至关重要.
    • 现有的计算方法往往忽视了药物对疾病进展的影响,主要关注的是药物向相互作用.

    研究的目的:

    • 根据药物对疾病治疗的影响,制定基于图形的策略,将药物分类为SYM或DM.
    • 通过准确地分类药物机制来增强药物重用.
    • 提高药物分类模型的可解释性.

    主要方法:

    • 构建一个整合基因,疾病和药物的异质网络.
    • 应用一个指导最短路径穿越框架来识别药物疾病转移的复发基因.
    • 基于与特定治疗类型相关的复发基因存在的药物分类.

    主要成果:

    • 拟议的基于图形的方法在药物分类准确性方面明显优于先进的机器学习和深度学习技术.
    • 识别复发基因提供了对药物机制的生物学见解.
    • 一个关于多发性硬化症的案例研究表明了该方法的生物相关性和有效性.

    结论:

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    • 开发的基于图形的策略提供了一个强大的和可解释的方法来分类药物效应.
    • 这种方法具有很大的潜力,可以促进药物的重新用途和了解疾病治疗机制.
    • 该研究提供了公开可用的数据和脚本,用于可复制性和进一步研究.