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相关概念视频

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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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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...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

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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...
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A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
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理性纳米粒子设计:利用实验和数学模型的见解进行优化.

Owen Richfield1, Alexandra S Piotrowski-Daspit1, Kwangsoo Shin1

  • 1Department of Biomedical Engineering, Yale University, New Haven, CT 06511, USA.

Journal of controlled release : official journal of the Controlled Release Society
|July 13, 2023
PubMed
概括
此摘要是机器生成的。

使用数学模型的聚合物纳米粒子的理性设计可以优化药物输送. 然而,复杂性需要大量的数据来准确建模和定量设计框架.

关键词:
多尺度数学建模 多尺度数学建模纳米粒子的药理动力学基于生理学的药理动力学.聚合物纳米颗粒的分子.有理性的纳米粒子设计.

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科学领域:

  • 生物材料科学 生物材料科学
  • 纳米技术 纳米技术
  • 药品制造 药品制造 药品制造

背景情况:

  • 聚合物纳米粒子是具有针对性治疗潜力的多功能药物输送系统.
  • 理性设计,在数学模型的帮助下,提供了一条优化纳米粒子性能的途径.
  • 由于系统的复杂性,当前的挑战阻碍了合理设计的充分实现.

研究的目的:

  • 审查聚合物纳米颗粒合理设计的关键方面.
  • 突出需要综合数据来建模纳米粒子行为.
  • 提出量化设计框架,考虑到数据限制.

主要方法:

  • 对聚合物纳米粒子的合理设计原则的文献综述.
  • 讨论纳米粒子优化中的数学建模方法.
  • 探索整合实验数据不确定性的方法.

主要成果:

  • 聚合物纳米粒子的行为是复杂的,涉及复杂的结构-属性关系.
  • 准确的建模需要大型,多尺度的实验数据集.
  • 现有的设计策略需要改进,以应对数据的变化.

结论:

  • 完全实现理性纳米粒子设计需要广泛的实验数据来进行多尺度建模.
  • 量化纳米粒子设计框架被提议用于解决数据限制和不确定性.
  • 这种方法旨在提高治疗效率,减少实验冗余.