We describe the formulation of a novel, multi-level, computational framework to comprehensively model mammalian metabolism from the point of nutrient uptake, through the entire known network of catabolic (energetic) and anabolic (biosynthetic) cellular reactions, and ultimately to the point at which a large protein product is synthesized and possibly secreted. This framework extends core concepts of an established systems modeling approach (“state-space”) onto biological systems – a previously unexplored application of this technique. Further, we will demonstrate the ability of this framework to identify valid, yet non-intuitive, metabolic chemistry when tasked with the optimization of cellular processes relative to the maximum yield of a protein product. Finally, to integrate this computational effort with the experimental laboratory, we explore specific challenges in the engineering of cell lines to adopt this non-intuitive metabolic chemistry. It is our hope that such engineered cell lines will demonstrate the improved productivity predicted by our model.