Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Pharmaceutical Alternatives: Polymorphic Form-Related and Particle Size-Related Therapeutic Nonequivalence01:27

Pharmaceutical Alternatives: Polymorphic Form-Related and Particle Size-Related Therapeutic Nonequivalence

131
Changes in polymorphic forms can significantly influence the bioavailability of poorly soluble drugs. Although the FDA defines pharmaceutical equivalence based on having the same active ingredient, dosage form, and route of administration, it does not automatically disqualify products with different polymorphic forms. This means two products with different polymorphs can still be deemed pharmaceutically equivalent. However, polymorphic differences can affect properties like wettability,...
131
Biopharmaceutical Factors Influencing Drug Product Design: Overview01:22

Biopharmaceutical Factors Influencing Drug Product Design: Overview

217
Rational drug product design integrates knowledge of the drug’s physicochemical properties, formulation components, manufacturing techniques, and intended route of administration. Each factor influences the drug’s performance, including how it is released, absorbed, and eliminated in the body.The physicochemical properties of a drug—such as solubility, stability, and particle size—affect its compatibility with excipients and the choice of dosage form. Excipients, though...
217
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

223
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...
223
Drug Discovery: Overview01:26

Drug Discovery: Overview

10.9K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
10.9K
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

1.8K
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...
1.8K
Drug Delivery: Overview01:16

Drug Delivery: Overview

700
The selection of a drug's delivery route depends upon its physicochemical properties, including lipid or water solubility and ionization, as well as the therapeutic requirement, such as immediate or sustained effect. These routes can be divided into three primary categories: enteral, parenteral, and topical.
Enteral delivery involves administering drugs directly through swallowing, sublingual placement, or buccal application. Orally administered drugs predominantly navigate the...
700

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Modeling Drying Behavior of an Aqueous Chitosan Single Droplet Using the Reaction Engineering Approach.

AAPS PharmSciTech·2020
查看所有相关文章

相关实验视频

Updated: Jan 7, 2026

Author Spotlight: Process Development for the Spray-Drying of Probiotic Bacteria and Evaluation of the Product Quality
05:45

Author Spotlight: Process Development for the Spray-Drying of Probiotic Bacteria and Evaluation of the Product Quality

Published on: April 7, 2023

4.2K

制药喷雾干燥的最新发展:建模,过程优化和机器学习的新兴趋势.

Waasif Wahab1, Raya Alshamsi1, Bouta Alharsousi1

  • 1Department of Chemical and Petroleum Engineering, United Arab Emirates University, Sheikh Khalifa Bin Zayed Street, Al-Ain 15551, United Arab Emirates.

Pharmaceutics
|December 31, 2025
PubMed
概括
此摘要是机器生成的。

喷雾干燥建模正在推进机器学习 (ML) 和计算流体动力学 (CFD). 结合ML和CFD的混合模型显示出优化制药喷雾干燥过程的前景.

关键词:
在 CFD 交易中,我们可以看到 CFD.美国FDA/EMA的指导方针在XAI,XAI就是XAI.数字双胞胎数字双胞胎是什么意思药物输送是药物输送的过程.混合ML模型的混合ML模型机器学习是机器学习.单滴滴建模 单滴滴建模喷雾干燥 喷雾干燥转移学习转移学习

更多相关视频

Measuring Spray Droplet Size from Agricultural Nozzles Using Laser Diffraction
08:14

Measuring Spray Droplet Size from Agricultural Nozzles Using Laser Diffraction

Published on: September 16, 2016

17.5K
Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols
15:04

Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols

Published on: May 20, 2016

11.3K

相关实验视频

Last Updated: Jan 7, 2026

Author Spotlight: Process Development for the Spray-Drying of Probiotic Bacteria and Evaluation of the Product Quality
05:45

Author Spotlight: Process Development for the Spray-Drying of Probiotic Bacteria and Evaluation of the Product Quality

Published on: April 7, 2023

4.2K
Measuring Spray Droplet Size from Agricultural Nozzles Using Laser Diffraction
08:14

Measuring Spray Droplet Size from Agricultural Nozzles Using Laser Diffraction

Published on: September 16, 2016

17.5K
Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols
15:04

Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols

Published on: May 20, 2016

11.3K

科学领域:

  • 制药技术 制药技术 制药技术
  • 化学工程是化学工程的组成部分.
  • 计算建模计算建模

背景情况:

  • 喷雾干燥对于制造制药粉末至关重要,过程参数显著影响产品质量.
  • 像计算流体动力学 (CFD) 这样的传统建模方法在复杂的喷雾干燥场景中面临精度和计算成本的限制.

研究的目的:

  • 审查制药应用喷雾干燥工艺建模方面的进展和挑战.
  • 探索机器学习 (ML) 和混合建模方法的潜力.

主要方法:

  • 审查现有的关于喷雾干燥建模技术的文献.
  • 计算流体动力学 (CFD) 局限性的分析.
  • 机器学习 (ML) 模型的评估,以优化喷雾干燥.
  • 讨论新兴的混合ML-CFD模型,数字双胞胎,转移学习和可解释AI (XAI).

主要成果:

  • 虽然CFD模型已经建立,但它存在一些局限性,包括高计算成本和在复杂条件下的准确性问题.
  • 机器学习模型为喷雾干燥提供了有希望的准确性,但需要高质量的数据,并可能与新参数预测作斗争.
  • 结合ML和CFD的混合模型,以及数字双胞胎和XAI等技术,正在成为强大的工具.

结论:

  • 机器学习展示了一种新兴的技术,用于增强制药喷雾干燥过程.
  • 结合ML和CFD的混合建模方法提供了一条克服个体方法局限性的途径.
  • 对数字双胞胎和XAI等先进技术的进一步研究有必要,以优化制药喷雾干燥.