A smart automation platform for cultured meat advancement

While the world population continues to grow and demand for protein increases, there are growing difficulties with conventional livestock farming practices. Traditional meat production is a relatively long process, sensitive to environmental factors and supply chain issues. Ranching is resource-intensive and a large contributor to climate change. Lab-grown meat seeks to address these issues by providing a more sustainable method of gathering protein for consumption. The process starts with primary animal cells found through a tissue biopsy or with a cell line. The cells are then proliferated in growth media where conditions are tightly controlled. Once enough mass is grown, the cells morph into other cell types where they can be formed into tissue resembling a cut of meat associated with that animal. With evermore research on cell types, growth media, and techniques, discoveries are being made; yet there is limited ability to make predictions from past findings. A major barrier in the discipline is automated and accurate data collection. While experiments take a long time to complete, they often come with nonstandard practices, contamination, or other human errors. The lack of data makes artificial intelligence (AI) algorithms inaccessible which further slows discoveries in the field. To confront these challenges, this paper proposes an automation platform using robotics and sensing technology to streamline the experimental process. The system is poised to combat data scarcity allowing computer scientists to support the field through AI models promoting future breakthroughs.