The NSF Molecule Maker Lab Institute (MMLI): An AI Institute for Molecular Discovery, Synthetic Strategy, and Manufacturing is supported by National AI Research Institutes Program of the Directorate for Computer and Information Science and Engineering (CISE), in collaboration with the Division of Chemistry (CHE) and the Division of Chemical, Bioengineering, and Environmental Transport Systems (CBET). The institute brings together a team of chemists, engineers, and AI-experts from the University of Illinois Urbana-Champaign, Pennsylvania State University and the Rochester Institute of Technology. The goal of the MMLI is to accelerate the synthesis and manufacture of complex organic molecules. A new AI-enabled synthesis platform is being developed to integrate chemical and enzymatic catalysis with literature mining and machine learning to predict the best way to make new molecules with desirable biological and material properties. This institute is transforming chemical synthesis and generating use-inspired AI advances. Simultaneously, the MMLI is also acting as a training ground for the next generation of scientists with combined expertise in chemical synthesis, bioengineering, and AI-enabled tool development. Outreach efforts aimed towards high school students and the public are being used to show how AI-enable tools can help to make chemical synthesis accessible to non-experts.
Chemical synthesis is currently an intuition-driven field that requires experienced experts to design iterative test cycles to make progress towards targeted molecules. The MMLI is developing new AI-enabled tools for chemical synthesis planning, catalyst design, property prediction, and manufacturing to address this bottleneck and accelerate the synthesis and discovery of new molecules. The institute combines expertise in AI, organic synthesis, and bioengineering to achieve the integration of chemical and enzymatic catalysis with a versatile set of building blocks in a new AI-driven synthesis planning tool called AlphaSynthesis. Optimization of this tool is being supported by new foundational AI approaches to text- and image mining, advances in machine learning for synthesis planning and catalyst optimization, as well as the established automated synthesis and bioengineering facilities at the University of Illinois Urbana-Champaign. Demonstration of the utility of the AlphaSynthesis tool is being achieved through the preparation of target molecules and new materials. An open-access reactivity database is being assembled and a hit-list of desirable transformations is being accumulated to encourage collaboration. These foundational studies bridging AI, chemical synthesis, and bioengineering to accelerate the iterative design and test process of chemical synthesis are further serving to bolstering the competitiveness of pharmaceutical, chemical, and technology industries in the US.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
