Evidence mapPaperPMID 41872333Full record

ReviewNature reviews. Drug discovery2026

Wearable technologies in clinical trials for drug development: trends and emerging opportunities.

Zahi A Fayad, Robert P Hirten, Girish N Nadkarni, Yun Soung Kim

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Drug discovery, 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

4 authors.

Zahi A FayadThe BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0002-3439-7347
Robert P HirtenThe Dr. Henry D. Janowitz Division of Gastroenterology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Girish N NadkarniThe Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA.
Yun Soung KimThe BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. yunsoung.kim@mssm.edu.ORCID http://orcid.org/0000-0002-3892-7560

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable technologies are increasingly being integrated into clinical trials, offering new tools to capture physiological and behavioural endpoints in real-world settings. By enabling continuous, remote, participant-friendly monitoring, wearables address key limitations of traditional trials, such as frequent site visits, sparse sampling and limited ecological validity, while supporting the development of digital biomarkers. To characterize how wearables are used in drug development, we curated 1,021 interventional trials registered between 2001 and 2025 that incorporated wearable-derived data into study protocols. We identified five application archetypes - drug effects, dosing optimization, adherence, delivery medium and delivery technique optimization - through which wearables are deployed in trials, underscoring a broadening role across study objectives. Adhesive patches, largely driven by continuous glucose monitoring, now dominate trial deployments, with expanding coverage of physiological domains including sleep, cardiovascular function, motor activity and brain signals. Despite this progress, formal regulatory qualification of wearable-derived measures remains rare, with SV95C in Duchenne muscular dystrophy the only such example to date. Looking ahead, we highlight emerging biochemical sensing modalities beyond glucose, as well as transdermal spectroscopy and wearable ultrasound. This Review provides a structured, forward-looking overview of wearables in trials and supports their responsible, effective integration into clinical development.

Indexed as

Clinical Trials as TopicDrug DevelopmentWearable Electronic DevicesDigital HealthHumans

Identifiers

PMID41872333

What Socratic holds

Textmetadata
Read underepoch 390

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.