Evidence map›Paper›PMID 42882452›Full record

ReviewCells2026

Emerging Technologies in Cardiovascular Disease Modeling: Bridging Basic Science and Clinical Translation.

Ramcharan Singh Angom, Sophie K Ashbrook, Carter Magnano, Riya Kar, Anya Dorairaj, Hari Krishnareddy Rachamala, Debabrata Mukhopadhyay

Abstract readReview
In one paragraph

Review in Cells, 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

7 authors.

Ramcharan Singh AngomDepartment of Biochemistry & Molecular Biology, Mayo Clinic College of Medicine and Sciences, Jacksonville, FL 32224, USA.ORCID 0000-0002-5894-1108
Sophie K AshbrookDepartment of Biochemistry & Molecular Biology, Mayo Clinic College of Medicine and Sciences, Jacksonville, FL 32224, USA.ORCID 0009-0008-4222-7509
Carter MagnanoDepartment of Biochemistry & Molecular Biology, Mayo Clinic College of Medicine and Sciences, Jacksonville, FL 32224, USA.ORCID 0009-0003-9570-507X
Riya KarDepartment of Biochemistry & Molecular Biology, Mayo Clinic College of Medicine and Sciences, Jacksonville, FL 32224, USA.
Anya DorairajDepartment of Biochemistry & Molecular Biology, Mayo Clinic College of Medicine and Sciences, Jacksonville, FL 32224, USA.
Hari Krishnareddy RachamalaDepartment of Biochemistry & Molecular Biology, Mayo Clinic College of Medicine and Sciences, Jacksonville, FL 32224, USA.
Debabrata MukhopadhyayDepartment of Biochemistry & Molecular Biology, Mayo Clinic College of Medicine and Sciences, Jacksonville, FL 32224, USA.ORCID 0000-0003-1858-5054

Funding

Distinct Pathways of VPF/VEGF ReceptorsR01HL140411 · NHLBI · MAYO CLINIC JACKSONVILLE · PI DEBABRATA MUKHOPADHYAY · 2018 to 2026
$4.0M
National Heart Lung and Blood Institute 2R01HL140411-05A1NHLBI NIH HHS R01 HL140411
6 · The paper itself

Abstract

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide, yet therapeutic development is limited by experimental models that incompletely recapitulate human physiology, disease heterogeneity, and treatment responses. Emerging human-relevant models, including patient-derived induced pluripotent stem cells, cardiac organoids, engineered tissues, organ-on-chip systems, genome editing, multi-omics, and computational approaches, are improving the ability to investigate cardiovascular disease mechanisms and therapeutic responses. In this review, we critically compare these technologies with respect to physiological relevance, reproducibility, scalability, throughput, and translational potential. We highlight their applications in disease modeling, drug discovery, toxicity assessment, and precision medicine while examining persistent limitations, including cellular immaturity, incomplete vascularization and systemic integration, model variability, and limited clinical validation. We further discuss how integration of bioengineering, genome editing, multi-omics, and computational methods may improve predictive performance. Standardization, interlaboratory validation, regulatory qualification, and prospective benchmarking against human clinical outcomes will be essential for translating these platforms into reliable tools for cardiovascular research and therapeutic development. Collectively, the convergence of stem cell biology, bioengineering, genome editing, multi-omics, and computational approaches is establishing a new generation of human-centered cardiovascular models with the potential to strengthen mechanistic discovery and accelerate the development of more predictive and personalized therapies.

Indexed as

Cardiovascular DiseasesModels, BiologicalTranslational Research, BiomedicalAnimalsGene EditingHumansInduced Pluripotent Stem CellsMicrophysiological SystemsMultiomicsPrecision Medicineartificial intelligencecardiac organoidscardiovascular disease modelingCRISPR genome editinghuman induced pluripotent stem cellsmulti-omicsorgan-on-chipprecision medicinetissue engineering

Identifiers

PMID42882452
PMCPMC13664009

What OpenQuestion 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 OpenQuestion graph.