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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

96
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...
96
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

81
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...
81
Typical Model Studies01:30

Typical Model Studies

382
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
382
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

182
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
182

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相关实验视频

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Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
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迈向先进的生物工艺优化:一种多尺度建模方法.

Mariana Monteiro1, Sarah Fadda1, Cleo Kontoravdi1

  • 1Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom.

Computational and structural biotechnology journal
|July 31, 2023
PubMed
概括

这项研究介绍了一种新的实时养策略,用于使用模型预测控制 (MPC) 进行中国仓鼠卵巢 (CHO) 细胞培养. 这种可适应的方法通过响应当前的工艺状态来优化蛋白质的生产,提高生物制药制造的效率.

科学领域:

  • 生物技术是生物技术.
  • 生物工艺工程 生物工艺工程
  • 细胞培养技术 细胞培养技术

背景情况:

  • 哺乳动物细胞培养,特别是使用中国仓鼠卵巢 (CHO) 细胞,对于生产治疗性蛋白质至关重要,占商业供应的高达80%.
  • 目前的料批处理过程依赖于预先确定的料策略,往往忽视实时工艺条件,这可能会限制最佳蛋白质产量和质量.
  • 适应性和高效的生物制造战略的需求至关重要,以满足对生物制药品日益增长的需求.

研究的目的:

  • 开发和验证一种模型预测控制 (MPC) 配方,以优化CHO细胞食批量培养中的养政策.
  • 创建一种不依赖培养的控制策略,可以在不同的CHO细胞培养系统中转移.
  • 为了证明与传统的开环方法相比,实时,状态意识的养控制的有效性.

主要方法:

  • 开发一种混合动力-静态反应堆模型,以捕捉细胞生长和蛋白质生产动态.
  • 实施模型预测控制 (MPC) 框架,利用开发的模型实时优化料速率.
  • 使用数字双胞胎作为过程模拟器进行验证,将闭环MPC控制与开环模拟进行比较.

主要成果:

  • 该MPC配方成功地在实时生成了最佳的养策略,适应细胞培养的动态状态.
  • 与开放循环策略相比,模拟显示在闭环MPC控制下过程性能显著改善.
关键词:
生物过程控制控制在CHO细胞中.数字双胞胎 数字双胞胎 数字双胞胎代谢优化优化 代谢优化过程系统 过程系统

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  • 建议的控制策略被证明是对特定培养条件的不可知,这表明在CHO细胞制造中具有广泛的适用性.
  • 结论:

    • 模型预测控制提供了一种强大的实时优化料批量CHO细胞培养的方法.
    • 开发的文化不可知MPC战略提高了生物制药生产的效率和稳定性.
    • 这种先进的控制方法有望改善治疗蛋白质的制造.