Application of Machine Learning to Improve Biobased Glucaric Acid Production

Research output: NRELPresentation


Kalion, Inc. is an industrial biotechnology manufacturer of high-purity chemicals from biomass including glucaric acid to be used in the industrial, material, and pharmaceutical markets. The project goal is application of machine learning in conjunction with high-throughput cultivations and metabolomics to understand and overcome two different challenges: (i) improve glucaric acid productivity (the rate of production slows considerably after 48 hours, which limits the overall productivity that can be achieved in the process), and (ii) decrease its production costs (components from complex media are necessary to achieve robust production). Through a series of experiments, a set of metabolites contained in rich media that improved performance were identified using metabolomics, high throughput cultivations in bioreactors, and machine learning-friendly experimental designs. It was found that the substrate feeding strategy was the potential major driver to enhance bacterial performance of glucaric acid production. The major industrial impacts by this project are the improvement of the production process technology, as well as advancing infrastructures and workflows (where machine learning approaches in conjunction with high-throughput cultivation and metabolomics are used) to improve the analyses by making them more rapid and comprehensive.
Original languageAmerican English
Number of pages10
StatePublished - 2023

Publication series

NamePresented at the 2023 U.S. Department of Energy's Bioenergy Technologies Office (BETO) Project Peer Review, 3-7 April 2023, Denver, Colorado

NREL Publication Number

  • NREL/PR-2800-85693


  • glucaric acid
  • machine learning


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