Evidence map›Paper›PMID 31857146›Full record

ArticleToxicology in vitro : an international journal published in association with BIBRA2020

Predicting tubular reabsorption with a human kidney proximal tubule tissue-on-a-chip and physiologically-based modeling.

Courtney Sakolish, Zunwei Chen, Chimeddulam Dalaijamts, Kusumica Mitra, Yina Liu, Tracy Fulton, Terry L Wade, Edward J Kelly, Ivan Rusyn, Weihsueh A Chiu

Open access · greenAbstract read
In one paragraph

Article in Toxicology in vitro : an international journal published in association with BIBRA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

20 citing papers in PubMed, 52 citations in OpenAlex.

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  14. Microphysiological Systems Evaluation: Experience of TEX-VAL Tissue Chip Testing Consortium.Toxicological sciences : an official journal of the Society of Toxicology · 2022
    Article
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  19. Microphysiological systems: What it takes for community adoption.Experimental biology and medicine (Maywood, N.J.) · 2021
    Review
  20. Review
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

10 authors at 2 institutions in 1 country.

Courtney SakolishDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA. Electronic address: csakolish@cvm.tamu.edu.
Zunwei ChenDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA. Electronic address: zchen@cvm.tamu.edu.
Chimeddulam DalaijamtsDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA. Electronic address: cdalaijamts@cvm.tamu.edu.
Kusumica MitraGeochemical and Environmental Research Group, Texas A&M University, College Station, TX 77845, USA. Electronic address: kmitra@tamu.edu.
Yina LiuGeochemical and Environmental Research Group, Texas A&M University, College Station, TX 77845, USA. Electronic address: yinaliu@geos.tamu.edu.
Tracy FultonGeochemical and Environmental Research Group, Texas A&M University, College Station, TX 77845, USA.
Terry L WadeGeochemical and Environmental Research Group, Texas A&M University, College Station, TX 77845, USA. Electronic address: t-wade@geos.tamu.edu.
Edward J KellyDepartment of Pharmaceutics, University of Washington, and Division of Nephrology, University of Washington Kidney Research Institute, Seattle, WA 98195, USA; Division of Nephrology, University of Washington Kidney Research Institute, Seattle, WA 98195, USA. Electronic address: edkelly@uw.edu.
Ivan RusynDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA. Electronic address: irusyn@cvm.tamu.edu.
Weihsueh A ChiuDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA. Electronic address: wchiu@cvm.tamu.edu.
Texas A&M University · USUniversity of Washington · US

Funding

Single cell, multi-parametric high throughput platform to classify endocrine disruptor potential of mixturesP42ES027704 · NIEHS · TEXAS A&M UNIVERSITY · PI Weihsueh A Chiu · 2017 to 2026
$21.2M
Using iPSCs to model patient outcomes in nephrotic syndromeUH3TR000504 · NCATS · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN · 2014 to 2016
$6.1M
TEX-VAL: Texas A&M Tissue Chip Validation CenterU24TR001950 · NCATS · TEXAS A&M UNIVERSITY · PI RUSYN, IVAN · 2016 to 2017
$4.2M
Tissue Chip Data to the Microphysiology Systems Database (MPS-Db) Supplement to A Microphysiological System for Kidney Disease Modeling and Drug Efficacy TestingUH3TR002158 · NCATS · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN · 2019 to 2021
$4.2M
Regulatory Science in Environmental Health and ToxicologyT32ES026568 · NIEHS · TEXAS A&M UNIVERSITY · PI Weihsueh A Chiu, Natalie M Johnson · 2016 to 2026
$3.8M
A Microphysiological System for Kidney Disease Modeling and Drug Efficacy TestingUG3TR002158 · NCATS · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN · 2017 to 2018
$2.9M
A Tissue Engineered Human Kidney Microphysiological SystemUH2TR000504 · NCATS · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN · 2012 to 2013
$2.1M
NCATS NIH HHS U24 TR001950NCATS NIH HHS UG3 TR002158NCATS NIH HHS UH2 TR000504NCATS NIH HHS UH3 TR000504NCATS NIH HHS UH3 TR002158NIEHS NIH HHS P42 ES027704NIEHS NIH HHS T32 ES026568
6 · The paper itself

Abstract

Kidney is a major route of xenobiotic excretion, but the accuracy of preclinical data for predicting in vivo clearance is limited by species differences and non-physiologic 2D culture conditions. Microphysiological systems can potentially increase predictive accuracy due to their more realistic 3D environment and incorporation of dynamic flow. We used a renal proximal tubule microphysiological device to predict renal reabsorption of five compounds: creatinine (negative control), perfluorooctanoic acid (positive control), cisplatin, gentamicin, and cadmium. We perfused compound-containing media to determine renal uptake/reabsorption, adjusted for non-specific binding. A physiologically-based parallel tube model was used to model reabsorption kinetics and make predictions of overall in vivo renal clearance. For all compounds tested, the kidney tubule chip combined with physiologically-based modeling reproduces qualitatively and quantitatively in vivo tubular reabsorption and clearance. However, because the in vitro device lacks filtration and tubular secretion components, additional information on protein binding and the importance of secretory transport is needed in order to make accurate predictions. These and other limitations, such as the presence of non-physiological compounds such as antibiotics and bovine serum albumin in media and the need to better characterize degree of expression of important transporters, highlight some of the challenges with using microphysiological devices to predict in vivo pharmacokinetics.

Indexed as

Models, BiologicalRenal ReabsorptionTissue Culture TechniquesCadmiumCaprylatesCisplatinCreatinineFluorocarbonsGentamicinsHumansKidney Tubules, ProximalCadmiumCaprylatesCisplatinCreatinineFluorocarbonsGentamicinsperfluorooctanoic acidKidneyMicrophysiological systemsPharmacokineticsRenal clearanceTissue-on-a-chipTubular reabsorption

Identifiers

PMID31857146
PMCPMC7053805
OpenAlexW2995121336

What OpenQuestion holds

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LicenceTDM
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.