AI-Driven Insights into the complexities of Chinese hamster ovary cells death in order to optimize production processes

Abstract

AbstractChinese hamster ovary (CHO) cells are a multipurpose and high-performance cell line for recombinant protein production in biopharmaceutical industry. They have proven their ability to produce a wide range of therapeutic proteins with high efficiency and quality. Designing novel and high-performance CHO cell lines has an incredible impact in biopharmaceutical industry that can reduce prices and increase product efficiency. One of the best ways is to prevent CHO cells death during Bioprocessing. Apoptosis is the most common form of CHO cells death during Bioprocessing. Analyzing Apoptosis and cell-cycle complex signaling pathways are necessary for the control of cell growth, efficiency, and the death of CHO cells. Therefore, analyzing and understanding interactions of these pathways and their interactions with other cellular processes can help optimize the performance and quality of CHO cell lines. AI-driven insight solutions and Advanced machine learning algorithms like GAT (Graph Attention Network) used in this project indicate most important Targets in complex signaling pathways. Pathways such as the TNF signaling pathway, and also viruses like: Hepatitis C, HIV1 and Bacteria like: Salmonella have High intersection size and Low P-value with complex signaling pathways. These microorganisms should be used to design high-performance CHO cell lines because they are master in these pathways. This method can be used to find novel and high efficiency targets for curing cancer in humans.