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Paper short abstract

This paper compares laboratory tests and real-world data (RWD) as epistemic practices. It asks how RWD stabilizes knowledge through cleaning, purification, and signal/noise separation, and how health policy links testing and RWD infrastructures.

Paper long abstract

The creation of medicals test was a significant outcome of particular types of laboratory research. The lab created conditions that involved a stabilization of the world, by cleaning it, purifying it, until specific elements could be controlled and verified. When tests emanated from this work, testing methodologies became boundary objects that could travel out of the research laboratory and allow pathogens in the world to travel back into clinical laboratories. In medicine, the randomized clinical trial (RCT) was later invented to also make pharmaceutical effects testable in populations. While STS have partly lost interest in the laboratory, tests and RCTs have also become taken-for-granted epistemic objects among health policymakers. The buzz is now about real-world data (RWD), which could be said to be about exploring all that the structured methodologies of tests and RCTs could not capture. European policymakers currently invest billions of euros in establishing infrastructures for RWD exploration. How do laboratory tests and RWD science compare? How do people in RWD settings work with cleaning and purification to stabilize knowledge objects? How do they stabilize the world and make it fit their models? How do they separate noise from signal? And what is the social fate of clinical test results in this emerging environment? With point of departure in these questions, I wish to reflect on the RWD as a new arena for STS work on the purification and stabilization practices once associated with the development of the test.