7 Limitations and Future Work Many of the six machine learning techniques mentioned in prompts and LLM generations to improve monoclonal antibody production are most effectively implemented during the slower training phase of models. For instance, combinatorial opitmization is used to optimize weights and parameters with methods like stochastic gradient descent (SGD), while bayesian optimization assists hyperparameter tuning to improve efficiency and performance. Faster and more approximative LLM conversational inferencing methods used in this work tend to use efficient search strategies such as monte carlo sampling, beam search, or greedy search that rely more on hueuristics than exhaustive search in order to maintain near-real-time decision-making.