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Qualitative case study explores personalized cancer treatment decisions using predictive technologies, suggesting inconsistencies in practice.
This article explores the ways in which predictive information technologies are used in the field of personalized medicine and the relations between this use and how patients and disease are perceived. This is examined in a qualitative case study of a personalized cancer clinical trial, where oncologists made clinical decisions for each patient based on drug matchings and efficacy predictions produced by bioinformatic technologies and algorithms. I focus on personalized practice itself, as a postgenomic phenomenon, rather than on epistemic, ethical and institutional critiques. Personalized medicine aims to process molecular, clinical, environmental and social data into individually tailored decisions. In this case, however, the engagement of clinicians with data and digital artefacts that processed multiple information sources resulted in treatment choices that were paradoxically both immutable and uncertain. In contrast to the situatedness of the body in postgenomics, this practice subverted the personalized medical approach while decontextualizing both cancer and patients.
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Nadav Even Chorev (2019) studied this question.
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