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.
Current opinion in biotechnology
|November 29, 2025
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.
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.
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