An Adaptive Pipeline From Scientific Data to Models

Under DARPA's Synergistic Discovery and Design program, a team composed of scientists from Duke, Rutgers, Montana State, and Florida Atlantic Universities, as well as Geometric Data Analytics, and Netrias, Inc., broadly researched and developed data driven techniques for scientific discovery and robust design, proving feasibility through program challenge problems with Yeast States, Novel Chassis, Protein Stability, and Perovskite.

Air Force Research Laboratory, Rome, NY

The Duke Team, composed of scientists from Duke University, Rutgers The State University of New Jersey (Rutgers), Montana State University, Florida Atlantic University, Geometric Data Analytics (GDA), and Netrias, Inc., has worked broadly within the Defense Advanced Research Projects Agency (DARPA) Synergistic Discovery and Design (SD2) program, contributing to efforts in the Yeast States, Novel Chassis, Protein Stability, and Perovskite challenge problems (CP).

The SD2 program was structured across five technical areas (TAs), TA1 - Data-Centric Scientific Discovery, TA2 - Design in the Context of Uncertainty, TA3 - Hypothesis and Design Evaluation, TA4 - Data and Analysis Hub, and TA5 - Challenge Problem Integrator, where the Duke Team supported TA1 and TA3 capabilities. Early in the program it was realized that some of the data needed to achieve goals of this effort could not be produced by the automated and semi-automated TA3 laboratories. To merge the data collected in the benchtop laboratory of the Duke Team with the automated labs, it was necessary to utilize approaches for protocol execution and data collection that were utilized by the TA3 labs. In collaboration with the University of Washington (UW) Biofab team, Aquarium for the benchtop was developed, enabling the Duke Team's benchtop lab to execute protocols and collect data, that when delivered to the database, was indistinguishable from data collected at the automated TA3 labs.