SPRINT: Scalable Protein Research for INnovative Training
Members: University of California, Davis, MiraCosta College, Modesto Junior College
Project dates: 2026 – present
This project will expand, implement, and publicly share a scalable biomanufacturing training model to prepare thousands of undergraduate students for careers in the bioindustrial manufacturing economy. Known as SPRINT (Scalable Protein Research for INnovative Training), this effort builds on the successful Design to Data (D2D) initiative—an undergraduate research network founded at UC Davis that engages students in real-world enzyme characterization projects rooted in protein science.
Through this project, SPRINT will grow the D2D network from 40 to 100 institutions, including community colleges and primarily undergraduate institutions, to provide access to cutting edge, hands-on biomanufacturing training. Faculty at participating institutions will receive curriculum resources, train-the-trainer support, and professional development aligned with emerging workforce needs. Students will engage in authentic research experiences tied to next-generation protein engineering and data science, producing real enzyme characterization data that feeds into a national research platform.
The work will result in publicly available teaching modules, defined placement pathways for D2D students, open-access instructional videos, and a redesigned D2D website where educators, learners, and BioMADE members can access tools, data, and curriculum. Student participation and learning outcomes will be tracked across the network and shared in a peer-reviewed publication. Industry partners will advise the project and offer internships to participating students.
By combining open access, real research, and scalable resources, SPRINT is building a broadly accessible early-career training program for protein science and biomanufacturing for the nation—laying a foundation for a strong and successful bioindustrial manufacturing workforce.
Funding source: U.S. Department of Defense