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人工智能在生物过程自动化中的发展前景

Laura Marie Helleckes1, Sebastian Putz2, Kshitiz Gupta3

  • 1The Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London, United Kingdom; I-X Centre for AI in Science, Imperial College London, London, United Kingdom.

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概括

混合自动驾驶实验室 (SDLs) 将人工智能 (AI) 与人类监督相结合,为推动生物工艺开发提供了一条实用途径. 这种方法解决了有效科学发现的独特生物处理挑战.

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科学领域:

  • 生物技术是生物技术.
  • 人工智能的人工智能
  • 实验室自动化 实验室自动化

背景情况:

  • 人工智能 (AI) 正在改变实验室自动化,导致自动驾驶实验室 (SDL) 进行自主发现.
  • 生物工艺开发面临着独特的挑战,如生物复杂性,监管要求和多规模实验,使其与其他自动化领域区别开来.

研究的目的:

  • 审查AI和SDL在生物工艺开发中的应用.
  • 探索用于生物处理的混合人机决策模型.
  • 在AI驱动生物处理的背景下,研究实验室设计和扩展挑战.

主要方法:

  • 关于人工智能在实验室自动化和生物工艺开发中的文献评论.
  • 对混合人机决策框架的分析.
  • 检查人工智能集成的实验室设计原则.
  • 讨论从生物工艺查到制造业的扩大挑战.

主要成果:

  • 混合SDL将人工智能与人类监督相结合,被认为是生物工艺开发中最实用的短期解决方案.
  • 关键的挑战包括生物复杂性,监管障碍和多规模实验.
  • 数据标准化和社区协作的差距对于实现自主生物工艺创新至关重要.

结论:

  • 混合SDL提供了一个务实的方法来利用人工智能在生物处理中.
  • 处理数据标准化和促进社区努力对于未来的进步至关重要.
  • 在人工智能驱动的生物工艺开发中,持续的人类监督仍然至关重要.