ArticleFrontiers in pharmacology2011
MEGen: A Physiologically Based Pharmacokinetic Model Generator.
Article in Frontiers in pharmacology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Development, testing, parameterisation, and calibration of a human PBPK model for the plasticiser, di-(2-ethylhexyl) terephthalate (DEHTP) usingFrontiers in pharmacology · 2023Article
- Development, testing, parameterisation, and calibration of a human PBK model for the plasticiser, di (2-ethylhexyl) adipate (DEHA) usingFrontiers in pharmacology · 2023Article
- Development, Testing, Parameterisation and Calibration of a Human PBPK Model for the Plasticiser, Di-(2-propylheptyl) Phthalate (DPHP) Using in Silico,Frontiers in pharmacology · 2021Article
- Next generation physiologically based kinetic (NG-PBK) models in support of regulatory decision making.Computational toxicology (Amsterdam, Netherlands) · 2019Review
- Development, Testing, Parameterization, and Calibration of a Human Physiologically Based Pharmacokinetic Model for the Plasticizer, HexamollFrontiers in pharmacology · 2019Article
- In vitro to in vivo extrapolation for high throughput prioritization and decision making.Toxicology in vitro : an international journal published in association with BIBRA · 2018Review
- Evaluation and calibration of high-throughput predictions of chemical distribution to tissues.Journal of pharmacokinetics and pharmacodynamics · 2017Article
- Automated workflows for modelling chemical fate, kinetics and toxicity.Toxicology in vitro : an international journal published in association with BIBRA · 2017Article
- Integrating in vitro data and physiologically based kinetic (PBK) modelling to assess the in vivo potential developmental toxicity of a series of phenols.Archives of toxicology · 2017Article
- Animal-Free Chemical Safety Assessment.Frontiers in pharmacology · 2016Review
- Physiologically based pharmacokinetic modeling framework for quantitative prediction of an herb-drug interaction.CPT: pharmacometrics & systems pharmacology · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Physiologically based pharmacokinetic models are being used in an increasing number of different areas. However, they are perceived as complex, data hungry, resource intensive, and time consuming. In addition, model validation and verification are hindered by the relative complexity of the equations. To begin to address these issues a web application called MEGen for the rapid construction and documentation of bespoke deterministic PBPK model code is under development. MEGen comprises a parameter database and a model code generator that produces code for use in several commercial software packages and one that is freely available. Here we present an overview of the current capabilities of MEGen, and discuss future developments.
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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.