Personalized Medicine in Practice: Postgenomics from Multiplicity to Immutability

Abstract

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.

Patients’ and professionals’ views related to ethical issues in precision medicine: a mixed research synthesis

“…A comparative study with oncologists, cardiologists and family doctors concluded that oncologists felt better informed, were more able to interpret test results and more confident in discussing the results with their patients [ 27 ]. Nevertheless, even among oncologists there seems to be some uncertainty at times regarding the choice of the right treatment [ 28 , 31 ] and the interpretation [ 30 – 32 ] or explanation [ 31 ] of genomic data. Another exception of better knowledge was also demonstrated among clinical geneticists and genetic counsellors.…”

Precision patients: Selection practices and moral pathfinding in experimental oncology

“…Our analysis adds to their work by foregrounding how the targeted trial design, which has been hailed as a ‘paradigm shift’ (Tan et al, 2009), rests on the selection of very specific patients, who we term ‘precision patients’. Other scholars have examined how genetic patient screening shapes drug development (Keating & Cambrosio, 2014; Nelson et al, 2014), the organisation of scientific and clinical practice (Cambrosio et al, 2018; Chorev, 2020), and how cancer patienthood is developing in the context of molecular information (Day et al, 2017; Kerr et al, 2021). Building on these important scholarships on experimental oncology, our analysis of patient selection illuminates how precision—even in the context of universal cancer care—comes at the cost of patient exclusion.…”

Introducing AI to the molecular tumor board: one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information

“…The human genome project, which began in 1990 to analyze the entire human sequence, was declared complete in April 2003 after 13 years and a budget of approximately US$3 billion [ 1 – 3 ]. The world then entered the post-genomic era, and expectations grew for the development of “personalized medicine,“ in which genomic information is applied to medical treatment [ 4 – 6 ]. When the 454 Genome Sequencer 20 (GS20), the first next-generation sequencing (NGS) technology, was introduced in 2005, genetic analysis using NGS became actively pursued.…”