ArticleLab on a chip2020
Applications of the microphysiology systems database for experimental ADME-Tox and disease models.
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.
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.
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.
Who cites it
29 citing papers in PubMed.
- Reverse bioengineering of the liver: developmental principles for next-generation liver-on-a-chip systems.Communications biology · 2026Review
- Organ-on-chip bridging musculoskeletal disease modeling and precision therapeutic discovery.Trends in biotechnology · 2026Review
- Article
- AI-integrated microfluidics for drug screening: From single cell to organ-on-a-chip.Acta pharmaceutica Sinica. B · 2026Review
- Scaling human liver microphysiological systems: implementing a higher-throughput liver acinus microphysiological system platform.Experimental biology and medicine (Maywood, N.J.) · 2026Article
- Article
- Integrated Patient Digital and Biomimetic Twins for Precision Medicine: A Perspective.Seminars in liver disease · 2025Review
- Comparative Analysis of Chemical Distribution Models for Quantitative In Vitro to In Vivo Extrapolation.Toxics · 2025Article
- Validation of microphysiological systems for interpreting patient heterogeneity requires robust reproducibility analytics and experimental metadata.Cell reports methods · 2025Review
- A metabolic dysfunction-associated steatotic liver acinus biomimetic induces pancreatic islet dysfunction in a coupled microphysiology system.Communications biology · 2024Article
- Normoglycemia and physiological cortisone level maintain glucose homeostasis in a pancreas-liver microphysiological system.Communications biology · 2024Article
- Neuropathogenesis-on-chips for neurodegenerative diseases.Nature communications · 2024Review
- Comparison of wild-type and high-risk PNPLA3 variants in a human biomimetic liver microphysiology system for metabolic dysfunction-associated steatotic liver disease precision therapy.Frontiers in cell and developmental biology · 2024Article
- Reproducibility and Robustness of a Liver Microphysiological System PhysioMimix LC12 under Varying Culture Conditions and Cell Type Combinations.Bioengineering (Basel, Switzerland) · 2023Article
- The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury.International journal of molecular sciences · 2023Article
- OOCDB: A Comprehensive, Systematic, and Real-time Organs-on-a-chip Database.Genomics, proteomics & bioinformatics · 2023Article
- Integrated-gut-liver-on-a-chip platform as an in vitro human model of non-alcoholic fatty liver disease.Communications biology · 2023Article
- Organ-On-A-Chip Database Revealed-Achieving the Human Avatar in Silicon.Bioengineering (Basel, Switzerland) · 2022Review
- Microphysiological Systems Evaluation: Experience of TEX-VAL Tissue Chip Testing Consortium.Toxicological sciences : an official journal of the Society of Toxicology · 2022Article
- A Quantitative Systems Pharmacology Platform Reveals NAFLD Pathophysiological States and Targeting Strategies.Metabolites · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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.
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Registered trials
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.