For the Part II intracellular metabolites table, ChatGPT-4o again was used for document retrieval of Paper 06 and prompt processing, but this time in regards to intracellular metabolites or intracellular metabolite relationship improvements. The 101 intracellular metabolite table was combined in similar methods to Part II extracellular, but focused on auto-scaled CE-MS intracellular values for each of the steps leading up to metabolite forecasts based on future LLM use or other author methods. Many of the original author values checked were verified against the original table to all be correct. 3 Opus was able to provide accurate forecasts for 71 of the metabolites, but had a longer generation time of 154 seconds before its run had ended. Due to the smaller sized intracellular table vs. the extracellular table, o1-preview was able to provide the largest and most convincing 101 metabolite forecasting table for Prompt IIe. Given these feats of AI being faster than the manuscript author on 25 occasions at up to a 666x maximum multiplier speed across 3 LLM speed advantages, combined with effective literature insights by ChatGPT-4o regarding bioprocess improvements, and the o1-preview processing of 136 and 101 metabolite tables, this work marks the 1st mAb bioprocess engineering conversational AI revolution. #01 Large Language Models for Early Phase GenAI Drug Discovery -New Prompt Upgrades to Bran, Chen Synthesis 10Jul24 [43] Direct prompt using LLM prior knowledge High creativity, ideation Contextual understanding Detailed generations of cancer drug syntheses GPT-4o 9.5/10 L3.0-70B 8.7/10 Mix8x7B 6.4/10