The Agile BioFoundry selected new collaborations from its joint funding opportunity with the National Science Foundation. The selected projects all directly contribute to the production of renewable biochemicals and biofuels and build foundational technologies critical for the decarbonization of the industrial and transportation sectors.
The Agile BioFoundry (ABF) hosted its virtual 2021 Industry Day on November 19, 2021 to showcase its capabilities and opportunities for joint research efforts. ABF team members presented on a variety of topics, including ABF operations and capabilities, methods for collaboration, and engagement through directed funding opportunities.
Today, the U.S. Department of Energy (DOE) announced the selection of 6 projects totaling over $5 million to conduct research and development needed to accelerate the U.S. biomanufacturing sector. As part of the DOE Bioenergy Technologies Office (BETO) Agile BioFoundry (ABF) consortium, these projects will leverage national laboratory capabilities to address challenges in biomanufacturing.
Every day the average person encounters tens, if not hundreds, of items that are made from petroleum and petroleum-based components. From the keyboard this article was typed with, to our daily grooming products and their containers, and the textiles we wear – petroleum products are everywhere: be it plastics, fragrances, dyes, or additives. Not only is petroleum in limited supply, the refining and production processes can cause air pollution and other environmentally unfriendly effects.
Several programs and research groups within the Biosciences area are working hard to find biologically derived components to find a sustainable and high-quality replacement for those that come from petroleum. Read on for a round-up of just some of the research we are doing to create sustainable bioproducts.
The Agile BioFoundry and Lygos, Inc. are joining forces to generate the largest multi-omics dataset for guiding the development of organic acids. Over the course of the project, scientists will produce more than 500,000 data points from a series of experiments. ABF is now using its artificial neural networks to train machine learning algorithms and provide actionable recommendations to help optimize strain performance, increase operational efficiencies and enhance production.