Evidence map›Paper›PMID 32211684›Full record

ArticleLab on a chip2020

Applications of the microphysiology systems database for experimental ADME-Tox and disease models.

Mark Schurdak, Lawrence Vernetti, Luke Bergenthal, Quinn K Wolter, Tong Ying Shun, Sandra Karcher, D Lansing Taylor, Albert Gough

Abstract read
In one paragraph

Article in Lab on a chip, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

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  19. 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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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

8 authors.

Mark SchurdakDrug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. mes234@pitt.edu and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0002-1146-3268
Lawrence VernettiDrug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. mes234@pitt.edu and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Luke BergenthalDrug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. mes234@pitt.edu.
Quinn K WolterDrug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. mes234@pitt.edu.
Tong Ying ShunDrug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. mes234@pitt.edu.
Sandra KarcherDrug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. mes234@pitt.edu.
D Lansing TaylorDrug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. mes234@pitt.edu and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Albert GoughDrug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. mes234@pitt.edu and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0001-6456-0195

Funding

Harnessing human brain and liver microphysiological systems for testing therapeutics for metastatic melanomaU01TR002383 · NCATS · VANDERBILT UNIVERSITY · PI MURPHY, WILLIAM L., TAYLOR, D. LANSING · 2018 to 2022
$7.6M
Measuring the Temporal-Spatial Responses of Dormancy and Drug Resistance in a Human Breast Cancer Metastatic Niche within a Liver-on-a-Chip Microphysiological PlatformUH3TR000503 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TAYLOR, D. LANSING · 2014 to 2016
$6.2M
University of Pittsburgh Microphysiology Systems Database CenterU24TR002632 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GOUGH, ALBERT H, SCHURDAK, MARK E · 2018 to 2022
$5.1M
University of Pittsburgh Tissue Chip Testing CenterU24TR001935 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SCHURDAK, MARK E · 2016 to 2017
$2.7M
Applying a Human Liver Microphysiology System to Develop Therapeutic Strategies for Non-Alcoholic Fatty Liver Disease (NAFLD)R01DK117881 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TAYLOR, D. LANSING · 2018 to 2021
$2.7M
Collaborations to Extend the Microphysiology Database for Multiple Organ Models,UH2TR000503 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TAYLOR, D. LANSING, YARMUSH, MARTIN L · 2012 to 2013
$2.3M
Human Microphysiology Systems Disease Model of Type 2 Diabetes Starting with Liver and pancreatic IsletsUG3DK119973 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TAYLOR, D. LANSING · 2018 to 2019
$2.3M
InCell 6000 High Content Instrument for Cellular Systems Biology ProgramS10OD012269 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TAYLOR, D. LANSING · 2013 to 2013
$502k
EPA 83573601NCATS NIH HHS U01 TR002383NCATS NIH HHS U24 TR001935NCATS NIH HHS U24 TR001935-02S1NCATS NIH HHS U24 TR002632NCATS NIH HHS UH2 TR000503NCATS NIH HHS UH3 TR000503NIDDK NIH HHS R01 DK117881NIDDK NIH HHS UG3 DK119973NIH HHS S10 OD012269
6 · The paper itself

Abstract

To accelerate the development and application of Microphysiological Systems (MPS) in biomedical research and drug discovery/development, a centralized resource is required to provide the detailed design, application, and performance data that enables industry and research scientists to select, optimize, and/or develop new MPS solutions, as well as to harness data from MPS models. We have previously implemented an open source Microphysiology Systems Database (MPS-Db), with a simple icon driven interface, as a resource for MPS researchers and drug discovery/development scientists (https://mps.csb.pitt.edu). The MPS-Db captures and aggregates data from MPS, ranging from static microplate models to integrated, multi-organ microfluidic models, and associates those data with reference data from chemical, biochemical, pre-clinical, clinical and post-marketing sources to support the design, development, validation, application and interpretation of the models. The MPS-Db enables users to manage their multifactor, multichip studies, then upload, analyze, review, computationally model and share data. Here we discuss how the sharing of MPS study data in the MS-Db is under user control and can be kept private to the individual user, shared with a select group of collaborators, or be made accessible to the general scientific community. We also present a test case using our liver acinus MPS model (LAMPS) as an example and discuss the use of the MPS-Db in managing, designing, and analyzing MPS study data, assessing the reproducibility of MPS models, and evaluating the concordance of MPS model results with clinical findings. We introduce the Disease Portal module with links to resources for the design of MPS disease models and studies and discuss the integration of computational models for the prediction of PK/PD and disease pathways using data generated from MPS models.

Indexed as

LiverMicrofluidicsDatabases, FactualDrug DiscoveryReproducibility of Results

Identifiers

PMID32211684
PMCPMC7497411

What OpenQuestion holds

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LicenceCC BY-NC
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.