  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.
