Evidence map›Paper›PMID 41508397›Full record

ArticleAdvanced healthcare materials2026

Automating Vascular Biology: An End-to-End Automated Workflow for High-Throughput Blood Vessel-on-a-Chip Production and Multi-Site Validation.

Dawn S Y Lin, Hanieh Mohammad Hashemi, Kimia Asadi Jozani, Anushree Chakravarty, Sonya Kouthouridis, Jessica Bonanno, Nicky Anvari, Shravanthi Rajasekar, Feng Zhang, Richard Y Cheng and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced healthcare materials, 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

15 authors.

Dawn S Y LinDepartment of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada.ORCID https://orcid.org/0000-0002-4134-8957
Hanieh Mohammad HashemiDepartment of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada.
Kimia Asadi JozaniSchool of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.
Anushree ChakravartyDepartment of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada.
Sonya KouthouridisDepartment of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada.
Jessica BonannoDepartment of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada.
Nicky AnvariSchool of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.
Shravanthi RajasekarDepartment of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada.
Feng ZhangSchool of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.
Richard Y ChengMerck & Co., Inc., Rahway, New Jersey, USA.
Narendra Kumar SinghMerck & Co., Inc., Rahway, New Jersey, USA.
Luis Miguel MedinaMerck & Co., Inc., Rahway, New Jersey, USA.
Marc DuranteMerck & Co., Inc., Rahway, New Jersey, USA.
Yufang HeMerck & Co., Inc., Rahway, New Jersey, USA.
Boyang ZhangDepartment of Chemical Engineering, McMaster University, Hamilton, Ontario, Canada.ORCID https://orcid.org/0000-0002-2060-5555

Funding

CIHR PJT-166052Natural Sciences and Engineering Research Council of Canada CGS D-547268-2020
6 · The paper itself

Abstract

There is a growing demand for automated organ-on-a-chip platforms that are compatible with off-the-shelf robotic liquid-handling systems and plate readers to improve reproducibility and scalable analysis. In this work, we present an end-to-end automated method for fabricating tubular blood vessel models at scale using a custom 384-well open-top platform (AngioPlate384), designed to support integration with liquid-handling systems and large-scale analysis. Our approach enables the generation of over 100 perfusable blood vessels fully embedded in hydrogel and supported by stromal cells (fibroblasts and pericytes), allowing both luminal and interstitial flow. Using this platform, we demonstrated that stromal co-culture significantly enhances vascular barrier function, and results in an altered response to chemotherapeutics and to inflammatory stressors. This platform offers a robust and scalable approach to generating customizable blood vessel-on-a-chip models for vascular biology studies, disease modeling, and preclinical testing. Its compatibility with automation and standardized workflows positions it as a powerful tool to accelerate the adoption of microphysiological systems in pharmaceutical research.

Indexed as

Blood VesselsLab-On-A-Chip DevicesAnimalsAutomationCoculture TechniquesFibroblastsHumansMicrophysiological Systemsautomationblood vessel‐on‐a‐chiphigh‐throughput modelingvascular biologyvascular disease

Identifiers

PMID41508397
PMCPMC13015779

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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.