Artificial intelligence and machine learning for smart bioprocesses

In recent years, the digital transformation of bioprocesses, which focuses on interconnectivity, online moni-toring, process automation, artificial intelligence (AI) and machine learning (ML), and real-time data acquisition, has gained considerable attention. AI can systematically analyze and forecast high-dimensional data obtained from the operating dynamics of bioprocess, allowing for precise control and synchronization of the process to improve performance and efficiency. Data-driven bioprocessing is a promising technology for tackling emerging challenges in bioprocesses, such as resource availability, parameter dimensionality, nonlinearity, risk mitigation, and complex metabolisms. This special issue entitled Machine Learning for Smart Bioprocesses (MLSB-2022) was conceptualized to incorporate some of the recent advances in applications of emerging tools such as ML and AI in bioprocesses. This VSI: MLSB-2022 contains 23 manuscripts, and summarizes the major findings that can serve as a valuable resource for researchers to learn major advances in applications of ML and AI in bioprocesses.

Automated summary

In recent years, there has been significant attention towards the digital transformation of bioprocesses, focusing on interconnectivity, online monitoring, process automation, AI and ML, and real-time data acquisition. AI can analyze and forecast high-dimensional data from bioprocess dynamics, allowing for precise control and synchronization to improve performance and efficiency. Data-driven bioprocessing is a promising technology for addressing challenges in bioprocesses. The MLSB-2022 special issue incorporates recent advances in ML and AI applications in bioprocesses, providing valuable resources for researchers to learn major developments.