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相关概念视频

Factors Influencing Drug Absorption: Pharmaceutical Parameters01:28

Factors Influencing Drug Absorption: Pharmaceutical Parameters

392
Solid dosage forms such as tablets and capsules undergo rigorous manufacturing processes to ensure stability and effectiveness. Their dissolution and absorption properties are influenced significantly by the choice of excipients (inactive ingredients that serve various roles in the formulation), and the methodology applied during production. The manufacturing parameters, such as compression force and granulation techniques, significantly affect dissolution rates. Elevated compression forces...
392
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

238
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...
238
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

282
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
282
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

328
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.
328
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

671
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...
671
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

519
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...
519

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Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
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基于随机森林和近接政策优化算法的平板电脑压缩过程参数优化模型.

Jianqiang Du1, Ting Wang2, Weifeng Zhu3

  • 1School of Intelligent Medicine and Information Engineering, Jiangxi University of Chinese Medicine, Nanchang 330004, China; Nanchang Normal University, Nanchang 330032, China.

International journal of pharmaceutics
|October 28, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了一种随机森林近接政策优化 (RF-PPO) 模型,以优化平板电脑制造工艺,减少手工干预,并确保稳定的平板电脑重量,以改善制药生产.

关键词:
功能选择 功能选择乳酸菌片 乳酸菌片过程参数优化过程参数优化邻近政策优化 政策优化随机的森林随机的森林平板电脑质量的平板电脑质量

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科学领域:

  • 制药制造业 制药制造业 制药制造业
  • 过程优化 过程优化
  • 机器学习应用 机器学习应用

背景情况:

  • 平板电脑的制造质量通常会受到工艺参数波动和手动调整的影响.
  • 当前的自动调节系统缺乏精度,需要人为干预.
  • 药片压缩的变化会影响产品的整体质量和一致性.

研究的目的:

  • 开发用于平板电脑制造的智能过程参数优化模型.
  • 为了应对平板电脑压缩线的质量波动.
  • 在制药生产中减少对手工干预的依赖.

主要方法:

  • 将集成的随机森林 (RF) 和近接政策优化 (PPO) 算法集成到一个新的RF-PPO模型中.
  • 使用特征选择来识别关键过程参数 (CPP).
  • 在线验证和 MATLAB/Simulink 模拟用于模型评估.

主要成果:

  • 射频预测模型表现出高精度 (R2>0.92,低RMSE).
  • 射频-PPO模型优化了参数,具有毫秒级响应时间 (0.0030秒).
  • 该模型有效地减少了与标称药片重量 (0.8 g) 的偏差.

结论:

  • 射频-PPO模型为智能制药制造提供了一个有前途的解决方案.
  • 它显著减少了手工干预,并保持了平板电脑的重量在优质产品系列.
  • 该模型通过确保一致的重量和优化过程参数来提高平板电脑质量.