Machine learning technologies to improve monoclonal antibody bioprocess engineering found in the 16 papers of this study address more deterministic approaches to receive the same answer for each identical input. Although these approaches are effective and necessary at addressing specific processes in industry, the methods shown in this work represent a scalable and all-encompassing approach to processing substantial volumes of high dimensional and complex data for new conversational AI utilities. The use-case for LLM inferencing in improving biological drug production will therefore be based on near-real-time decision-making handling of tabular data, and text from a variety of sources verified by human researchers.