Evidence mapPaperPMID 41937422Full record

ArticleSociology of health & illness2026

At the Right Time: Temporal Precision in Personalised Medicine.

Dominik Hofmann, Elena Esposito

Abstract read
In one paragraph

Article in Sociology of health & illness, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Dominik HofmannFaculty of Sociology, Bielefeld University, Bielefeld, Germany.ORCID 0000-0002-3392-8644
Elena EspositoFaculty of Sociology, Bielefeld University, Bielefeld, Germany.ORCID 0000-0002-3075-292X

Funding

European Research Council 833749
6 · The paper itself

Abstract

Personalised medicine was initially heralded as delivering 'the right drug to the right patient at the right time'. Although molecular precision has dominated recent developments, the temporal dimension has remained underexplored. This paper examines how temporal precision is emerging as a defining feature of next-generation precision medicine, driven by algorithmic tools and multiomics data integration. Drawing on qualitative interviews with leading experts in personalised immunotherapy and chronic inflammatory disease (CID) medicine, we identify five ways in which temporal precision is reshaping therapeutic practice: extended prediction, timing, synchronisation, coordination of treatments and feedback effects. We show how personalised cancer vaccines and precision inflammation approaches rely on algorithmic assemblages to anticipate therapy effects, coordinate interventions and dynamically adapt treatment schedules. These innovations highlight a shift from molecular precision to personalisation that incorporates the evolving temporality of both disease and therapy, signalling a new development in precision medicine: Diseases are increasingly treated as dynamic processes, therapies as sequences of timed interventions and patients as embedded in feedback loops between body rhythms, pathology and treatment regimens.

Indexed as

Precision MedicineTime FactorsAlgorithmsHumansImmunotherapyInterviews as TopicMultiomicsQualitative Researchalgorithmspersonalisationprecision medicinepredictionsynchronisationtime

Identifiers

PMID41937422
PMCPMC13051249

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.