MIT researchers developed the first publicly accessible artificial intelligence model that predicts long-term stability of Chinese Hamster Ovary (CHO) cells used extensively in biotherapeutic production. This model forecasts productivity retention across 72 passages, aligning with FDA definitions of cell line stability. By integrating epigenetic data and machine learning techniques, such as random forests, the model enhances manufacturing consistency and product quality. The research and tools promise to improve efficiency in biologics development, with code to be available on GitHub.