Oops!... you are doing it again : pharmacogenomics and the biologisation of ethnoracial categories on drug labels

In this paper I explore how pharmacogenomic findings regarding the impact of genetic variability on patients’ responses to drugs translate into drug labels. Despite growing recognition that such categories fail to reflect human genetic diversity, they continue to be applied in prescribing information, reinforcing outdated notions of race in medicine. By analysing pharmacogenomic data, I demonstrate that racialised labels offer no epistemic benefits and are methodologically flawed. Moreover, their widespread use in the pharmaceutical industry not only undermines scientific accuracy but also risks perpetuating racial biases in healthcare. Finally, I argue that guidelines and standards established by various stakeholders – including research funders, pharmaceutical regulators, global databases, and standards-developing organisations – can inadvertently reproduce frameworks rooted in race (and racist) science. They should therefore be subject to critical examination and, where necessary, revision.

Publication Details

Journal
FreiDok plus (Universitätsbibliothek Freiburg)
Published
2025-10-01
DOI
https://doi.org/10.6094/behemoth.2025.18.1.1117
Citations
1
Primary Topic
Library Science and Administration
Type
article
Field-Weighted Citation Impact
11.53
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Oops!... you are doing it again : pharmacogenomics and the biologisation of ethnoracial categories on drug labels

1 citations
FreiDok plus (Universitätsbibliothek Freiburg)
Library Science and Administration
11.53
article

Oops!... you are doing it again : pharmacogenomics and the biologisation of ethnoracial categories on drug labels

article en
1 citations

Abstract

In this paper I explore how pharmacogenomic findings regarding the impact of genetic variability on patients’ responses to drugs translate into drug labels. Despite growing recognition that such categories fail to reflect human genetic diversity, they continue to be applied in prescribing information, reinforcing outdated notions of race in medicine. By analysing pharmacogenomic data, I demonstrate that racialised labels offer no epistemic benefits and are methodologically flawed. Moreover, their widespread use in the pharmaceutical industry not only undermines scientific accuracy but also risks perpetuating racial biases in healthcare. Finally, I argue that guidelines and standards established by various stakeholders – including research funders, pharmaceutical regulators, global databases, and standards-developing organisations – can inadvertently reproduce frameworks rooted in race (and racist) science. They should therefore be subject to critical examination and, where necessary, revision.

FreiDok plus (Universitätsbibliothek Freiburg)
Openalex Percentile: Top 2%
Library Science and Administration
11.53
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.