The first part of this work utilized five papers and two prompts aimed at LLMs providing quotations from papers and forecasting its improvement in a report regarding mAb production through dimension reduction and combinatorial optimization, with o1-preview providing the most consistently detailed and convincing solutions, including: "Accelerated Literature Review: LLMs can process vast amounts of scientific literature to extract relevant metabolic pathways and modeling techniques, thereby speeding up the development of comprehensive models." Part B LLM conversations featured selections of numerical data from five additional papers to yield a large formatted table of data with corresponding mAb production projections using monte carlo simulations and markov chain models. Of the two examples in the manuscript, ChatGPT-4o offered a number of refinements in table quality vs 3.5 Sonnet primarily on the basis of completion, detail, and how convincing its solution was, which included a Process Mass Intensity (PMI) forecast improvement from "7700 kg/kg" to "6500 kg/kg".