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相关概念视频

Hybridoma Technology01:31

Hybridoma Technology

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Hybridoma technology is used for the large-scale production of monoclonal antibodies. Monoclonal antibodies bind to only a single antigenic determinant or epitope. Such antibodies are used in research, diagnostics, and disease therapy. The hybridoma technology established in 1975 by Georges Köhler and Cesar Milstein was awarded the Nobel Prize in Medicine in 1984 for revolutionizing research and therapy.
Hybridoma Selection
Commonly used fusion techniques — electroporation,...
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相关实验视频

Updated: Jun 6, 2025

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application
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机器学习模型用于从分子动力学模拟和基于深度学习的表面描述器预测单克隆抗体的生物物理性质.

I-En Wu1, Lateefat Kalejaye1, Pin-Kuang Lai1

  • 1Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, Hoboken 07030 New Jersey.

Molecular pharmaceutics
|November 28, 2024
PubMed
概括

这项研究引入了机器学习和深度学习模型,以预测单克隆抗体 (mAb) 开发能力. 这些模型准确地预测了关键的生物物理性质,加速了治疗性抗体的开发并降低了成本.

关键词:
深度学习是一种深度学习.开发能力 开发能力机器学习是机器学习.分子动力学模拟模拟这是一种单克隆抗体.

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Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System
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科学领域:

  • 生物技术是生物技术.
  • 计算生物学 计算生物学
  • 制药科学 制药科学

背景情况:

  • 单克隆抗体 (mAbs) 是关键的治疗药物,但它们的开发是漫长而昂贵的.
  • 早期评估mAb的可发育性对于治疗成功至关重要.
  • 关键因素包括生物物理特性,如聚合性,溶解性和粘度.

研究的目的:

  • 开发和验证机器学习 (ML) 和深度学习 (DL) 模型,用于预测 mAb 的生物物理性质.
  • 评估这些模型的预测性能与现有方法相比.
  • 引入一个新的DL模型,DeepSP,用于预测空间聚合和电荷特性.

主要方法:

  • 利用12个生物物理性质的数据集对137个抗体进行分析.
  • 采用全长抗体分子动力学模拟.
  • 应用机器学习技术和新的深度学习模型 (DeepSP) 用于财产预测.

主要成果:

  • 开发了ML模型,在预测大多数生物物理性质方面超过了以前的方法.
  • DeepSP模型实现了与分子动力学模拟相比较的预测准确性.
  • DeepSP显著减少了对财产预测的计算时间.

结论:

  • 开发的ML和DL模型提供了有效和准确的mAb可开发性预测.
  • DeepSP为评估抗体特性提供了比传统模拟更快的替代方案.
  • 自由可用的代码和Web应用程序 (AbDev) 促进了更广泛的采用,并加速了药物开发.