Background: We describe a prototype implementation of a platform that could underlie a Precision Oncology Rapid Learning system.
Results: We describe the prototype platform, and examine some important issues and details. In the Appendix we provide a complete walk-through of the prototype platform.
Conclusions: The design choices made in this implementation rest upon ten constitutive hypotheses, which, taken together, define a particular view of how a rapid learning medical platform might be defined, organized, and implemented.
Keywords: Controlled natural language; Nanopublication; Natural language processing; Precision oncology; Rapid learning; Targeted therapies; Treatment reasoning; Tumor boards.