Evidence map›Paper›PMID 40766547›Full record

ArticlebioRxiv : the preprint server for biology2025

Label-Free Longitudinal Imaging of Single Cell Drug Response with a 3D-Printed Cell Culture Platform.

Erin L Dunnington, King Wai Chiu, Brian S Wong, Anthony Chales-Antonio, Victoria Pang, Yiyi Wu, Dan Fu

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

7 authors.

Erin L DunningtonDepartment of Chemistry, University of Washington, Seattle, WA, 98195, USA.
King Wai ChiuDepartment of Chemistry, University of Washington, Seattle, WA, 98195, USA.
Brian S WongDepartment of Chemistry, University of Washington, Seattle, WA, 98195, USA.
Anthony Chales-AntonioDepartment of Chemistry, University of Washington, Seattle, WA, 98195, USA.
Victoria PangDepartment of Chemistry, University of Washington, Seattle, WA, 98195, USA.
Yiyi WuDepartment of Chemistry, University of Washington, Seattle, WA, 98195, USA.
Dan FuDepartment of Chemistry, University of Washington, Seattle, WA, 98195, USA.

Funding

Non-perturbative imaging of intracellular drug exposure and drug response of kinase inhibitors - Admin SuppR35GM133435 · NIGMS · UNIVERSITY OF WASHINGTON · PI Dan Fu · 2019 to 2026
$2.8M
NIGMS NIH HHS R35 GM133435
6 · The paper itself

Abstract

Image-based phenotypic screening has emerged as a powerful tool for revealing single-cell heterogeneity and dynamic phenotypic responses in preclinical drug discovery. Compared to traditional static end-point assays, live-cell longitudinal imaging captures the temporal trajectories of individual cells, including transient morphological adaptations, motility shifts, and divergent subpopulation behaviors, enabling high content features and more robust early prediction of treatment outcomes. Fluorescence-based screening, while highly specific, is constrained in live-cell contexts by broad spectral overlaps (limiting multiplexing to fewer than six channels), bulky fluorophores that may perturb small-molecule interactions, and photobleaching or phototoxicity under repeated excitation. Stimulated Raman scattering (SRS) microscopy overcomes these barriers by delivering label-free, quantitative chemical contrasts alongside morphological information. Here, we present a low-cost, 3D printed cell culture platform compatible with the stringent optical requirements of SRS microscopy. This set up enables real-time drug delivery and continuous monitoring of biochemical and morphological changes in living cells during 24-hour time-lapse imaging with minimal photodamage. We outline a processing pipeline for longitudinal SRS images to extract chemical and morphological features of single live cells. Using this system, we showcase time-lapse SRS microscopy as a tool to map heterogenous drug-induced single-cell response over time, enabling the identification of varying trajectories within complex cell populations. By parallelizing multi-well perfusion with label-free chemical imaging, our approach offers a pathway toward high-throughput pharmacodynamic assays for the acceleration of phenotypic screening and personalized medicine.

Identifiers

PMID40766547
PMCPMC12324531

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Registered trials

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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 OpenQuestion graph.