Paper long abstract:

The developing field of personalized medicine aims to tailor the medical treatment according to the specific genetic make-up of the individual patient. It strives to act in the present based on predictions of risks to develop pathologies in the future.

Through the analysis of a case-study of a personalized cancer treatment clinical trial, I aim to shed light on configurations of risk in the context of these recent developments in biomedicine, focusing particularly on the dynamics of clinical decision making. In this trial an algorithm was developed to assess the efficacy of drugs for each individual patient. The algorithm processes the products of DNA and RNA sequencing along with additional data on the patient, and produces in turn a quantified prediction score. The oncologists and specialists then convene to decide whether to accept this assessment and determine the treatment path.

I will draw on the analysis of texts, computerized outputs and records, as well as on the analysis of recordings and interviews, to show how the performative capacity of bioinformatic systems manages and produces risk, uncertainty and chance, how these feed into clinical decision making in the trial, and how both these aspects reflect logics of governmental practices. I suggest that risk in personalized medicine can be viewed as an assemblage of governmental practices of power, technological artifacts, biological and genetic matter and information, and various actors. I will discuss the implications of this perspective for conceptualizing risk and biopolitics in new contexts and for recent shifts in medical practices.