Artificial intelligence and machine learning applications for cultured meat
It targets researchers in cultured meat and machine learning to identify opportunities for reducing environmental and ethical impacts, but is incremental as it reviews existing work.
This review addresses the technological challenges in cultured meat by exploring how machine learning can accelerate research and development in areas like cell line establishment and bioprocessing optimization, though its application is still nascent.
Cultured meat has the potential to provide a complementary meat industry with reduced environmental, ethical, and health impacts. However, major technological challenges remain which require time- and resource-intensive research and development efforts. Machine learning has the potential to accelerate cultured meat technology by streamlining experiments, predicting optimal results, and reducing experimentation time and resources. However, the use of machine learning in cultured meat is in its infancy. This review covers the work available to date on the use of machine learning in cultured meat and explores future possibilities. We address four major areas of cultured meat research and development: establishing cell lines, cell culture media design, microscopy and image analysis, and bioprocessing and food processing optimization. This review aims to provide the foundation necessary for both cultured meat and machine learning scientists to identify research opportunities at the intersection between cultured meat and machine learning.