Evidence map›Paper›PMID 41701155›Full record

ReviewExpert opinion on drug metabolism & toxicology

Potential integration of multiple organs-on-a-chip for comprehensive drug-drug interaction prediction.

Eric W Hsu, Kai Wang, Yik Pui Tsang, Jonathan Himmelfarb, Catherine K Yeung, Edward J Kelly

Abstract readReview
In one paragraph

Review in Expert opinion on drug metabolism & toxicology. 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

6 authors.

Eric W HsuDepartment of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, USA.
Kai WangDepartment of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, USA.
Yik Pui TsangDepartment of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, USA.
Jonathan HimmelfarbBarbara T. Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn, School of Medicine at Mount Sinai, New York, NY, USA.
Catherine K YeungDepartment of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, USA.
Edward J KellyDepartment of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, USA.

Funding

XENOBIOTIC BIOTRANSFORMATION AND DISPOSITIONP30ES007033 · NIEHS · UNIVERSITY OF WASHINGTON · PI ALI SHOJAIE · 1995 to 2026
$42.5M
Translational center for kidney microphysiological systems to improve drug safety and efficacyU2CTR004867 · NCATS · UNIVERSITY OF WASHINGTON · PI Benjamin Solomon Freedman, Jonathan Himmelfarb · 2024 to 2026
$4.8M
NCATS NIH HHS U2C TR004867NIEHS NIH HHS P30 ES007033
6 · The paper itself

Abstract

introductionPredicting drug - drug interactions (DDIs) is essential for safe, effective medication therapy, yet conventional AREAS COVERED: We outline current DDI workflows, their strengths and limitations, and how single-organ chips can produce quantitative absorption, distribution, metabolism, and excretion (ADME) and toxicity parameters relevant for DDI analysis. We then discuss the need for emerging MOC platforms and the unique advantages that they offer, highlighting case studies that capture more complex DDI scenarios, as well as body-on-a-chip prototypes integrated with mechanistic modeling. EXPERT OPINION: MOC systems are currently poised to complement, not replace, established

Indexed as

Lab-On-A-Chip DevicesModels, BiologicalAnimalsComputer SimulationDrug InteractionsHumansMicrophysiological SystemsPharmaceutical PreparationsPharmacokineticsPharmaceutical PreparationsADMEbody-on-a-chipdrug–drug interactionsIVIVEmicrophysiological systemsmodel-informed drug developmentmulti-organ-on-a-chiporgan-on-a-chipPBPK modelingPK/PD modeling

Identifiers

PMID41701155
PMCPMC13671264

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.