In Wisconsin, researchers from the DOE Great Lakes Bioenergy Research Center developed a framework for the identification of the most promising biobased chemicals that have the highest economic prospect.
They developed a genome‐scale constraint‐based metabolic modeling approach, which is used to identify a candidate pool of 209 chemicals (together with the estimated yield, productivity, and residence time for each) from the intersection of the high‐production‐volume chemicals and the KEGG and MetaCyc databases. Second, they designed three screening criteria based on a chemical’s profit margin, market volume, and market size. The total process cost, including the downstream separation cost, is systematically incorporated into the evaluation. Third, given the three aforementioned criteria, they identified 32 products as economically promising if the maximum yields can be achieved, and 22 products if the maximum productivities can be achieved.
The proposed framework provides important guidance for future studies in the production of bio‐based chemicals. It is also flexible in that the databases, yield estimations, and criteria can be modified to customize the screening.