ArticleFrontiers in physiology2012
Development of a physiologically based computational kidney model to describe the renal excretion of hydrophilic agents in rats.
Article in Frontiers in physiology, 2012. 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, 14 citations in OpenAlex.
- A comparative computational analysis of IFN-alpha pharmacokinetics and its induced cellular response in mice and humans.PLoS computational biology · 2025Article
- Prediction of higher ceftazidime-avibactam concentrations in the human renal interstitium compared with unbound plasma using a minimal physiologically based pharmacokinetic model developed in rats and pigs through microdialysis.Antimicrobial agents and chemotherapy · 2025Article
- Contrast-induced acute kidney injury and its contemporary prevention.Frontiers in cardiovascular medicine · 2022Review
- An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom.Medical image analysis · 2021Article
- Physiologically-Based Pharmacokinetic Modeling for Drug-Drug Interactions of Procainamide andPharmaceutics · 2019Article
- A Quantitative Systems Pharmacology Kidney Model of Diabetes Associated Renal Hyperfiltration and the Effects of SGLT Inhibitors.CPT: pharmacometrics & systems pharmacology · 2018Article
- Effects of renal impairment on transporter-mediated renal reabsorption of drugs and renal drug-drug interactions: A simulation-based study.Biopharmaceutics & drug disposition · 2018Article
- γ-Hydroxybutyric Acid (GHB) Pharmacokinetics and Pharmacodynamics: Semi-Mechanistic and Physiologically Relevant PK/PD Model.The AAPS journal · 2017Article
- Intraglomerular crosstalk elaborately regulates podocyte injury and repair in diabetic patients: insights from a 3D multiscale modeling study.Oncotarget · 2016Article
- Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model.CPT: pharmacometrics & systems pharmacology · 2016Article
- Semi-mechanistic kidney model incorporating physiologically-relevant fluid reabsorption and transporter-mediated renal reabsorption: pharmacokinetics of γ-hydroxybutyric acid and L-lactate in rats.Journal of pharmacokinetics and pharmacodynamics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A physiologically based kidney model was developed to analyze the renal excretion and kidney exposure of hydrophilic agents, in particular contrast media, in rats. In order to study the influence of osmolality and viscosity changes, the model mechanistically represents urine concentration by water reabsorption in different segments of kidney tubules and viscosity dependent tubular fluid flow. The model was established using experimental data on the physiological steady state without administration of any contrast media or drugs. These data included the sodium and urea concentration gradient along the cortico-medullary axis, water reabsorption, urine flow, and sodium as well as urea urine concentrations for a normal hydration state. The model was evaluated by predicting the effects of mannitol and contrast media administration and comparing to experimental data on cortico-medullary concentration gradients, urine flow, urine viscosity, hydrostatic tubular pressures and single nephron glomerular filtration rate. Finally the model was used to analyze and compare typical examples of ionic and non-ionic monomeric as well as non-ionic dimeric contrast media with respect to their osmolality and viscosity. With the computational kidney model, urine flow depended mainly on osmolality, while osmolality and viscosity were important determinants for tubular hydrostatic pressure and kidney exposure. The low diuretic effect of dimeric contrast media in combination with their high intrinsic viscosity resulted in a high viscosity within the tubular fluid. In comparison to monomeric contrast media, this led to a higher increase in tubular pressure, to a reduction in glomerular filtration rate and tubular flow and to an increase in kidney exposure. The presented kidney model can be implemented into whole body physiologically based pharmacokinetic models and extended in order to simulate the renal excretion of lipophilic drugs which may also undergo active secretion and reabsorption.
Indexed as
Identifiers
What OpenQuestion holds
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.