人工智能时代发酵优化与放大技术的机遇与挑战

Opportunities and challenges for fermentation optimization and scale-up technology in the artificial intelligence era

摘要:

人工智能(artificial intelligence, AI)技术正引发一场新的产业革命，其成功应用正从信息产业迅速渗透到各行各业。传统的发酵工程技术受到巨大挑战的同时更多地迎来了发展变革的机遇。首先，合成生物技术飞速发展使高性能菌株的可获得性及获取效率显著提升，对传统低效的发酵优化放大技术提出很大挑战，亟需对发酵优化放大技术进行升级，以满足高通量菌种性能验证及工艺开发能力的需求；其次，发酵装备技术的持续发展为高效发酵优化技术的进步奠定了良好基础，加之人工智能技术特别是数字孪生与知识图谱等技术的应用，将为传统发酵技术的颠覆性发展带来巨大推动力。本文分别从合成生物时代对发酵优化技术的挑战、发酵优化与放大的核心技术、高通量发酵装备技术、数据可视化技术、数字孪生及知识图谱等智能技术在发酵优化放大中的应用等几个方面进行综述，并对未来工业发酵优化技术的场景以及未来发酵技术对人才培养等提出的新要求进行了展望。

Abstract:

Artificial intelligence (AI) technology is booming up a new industrial revolution, and its successful application is rapidly spreading from the information industry to many other fields. The Artificial intelligence (AI) technology is booming up a new industrial revolution, and its successful application is rapidly spreading from the information industry to many other fields. The traditional fermentation industry also faces more opportunities and great challenges for reforming. First of all, the rapid development of synthetic biotechnology has greatly enhanced the availability and efficiency for obtaining high-performance strains, which poses great opportunities to the traditional fermentation optimization and scale-up technology. It is urgent to upgrade fermentation optimization technology to cope with the requirement for high-throughput verification of strain performance. Secondly, the development of fermentation equipment technology has laid a good foundation for advancing fermentation optimization technology. The application of AI technology, especially the digital twin and knowledge graph technology, will further boost the upgrade of the traditional fermentation technology. This review summarizes the challenges of fermentation optimization technology in the era of synthetic biology, the core technology of fermentation optimization and scale-up, the equipment technology of high-throughput fermentation, data visualization technology, as well as the application of digital twin and knowledge graph in fermentation optimization and scale-up. This review also prospects future industrial fermentation technology, and the associated new requirements for personnel training.