ArticleCPT: pharmacometrics & systems pharmacology2018
Development of a Dynamic Physiologically Based Mechanistic Kidney Model to Predict Renal Clearance.
Article in CPT: pharmacometrics & systems pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Scientific Opinion on waiving of the dog studies in the regulatory process of agrochemicals approval.EFSA journal. European Food Safety Authority · 2026Article
- Rat PermQ: A permeability- and perfusion-based physiologically based pharmacokinetic model for improved prediction of drug concentration-time profiles in rat.Drug metabolism and disposition: the biological fate of chemicals · 2025Article
- Physiologically Based Pharmacokinetic Model of Cefotaxime in Patients with Impaired Renal Function.Clinical pharmacokinetics · 2025Article
- Is the GFR-based scaling approach adequate for predicting pediatric renal clearance of drugs with passive tubular reabsorption? Insights from PBPK modeling.CPT: pharmacometrics & systems pharmacology · 2025Article
- Physiologically based pharmacokinetic modeling of small molecules: How much progress have we made?Drug metabolism and disposition: the biological fate of chemicals · 2025Review
- Maximum likelihood estimation of renal transporter ontogeny profiles for pediatric PBPK modeling.CPT: pharmacometrics & systems pharmacology · 2024Article
- The impact of kidney function on plasma neurofilament light and phospho-tau 181 in a community-based cohort: the Shanghai Aging Study.Alzheimer's research & therapy · 2024Article
- Incorporating Uremic Solute-mediated Inhibition of OAT1/3 Improves PBPK Prediction of Tenofovir Renal and Systemic Disposition in Patients with Severe Kidney Disease.Pharmaceutical research · 2023Article
- Utility of Minimal Physiologically Based Pharmacokinetic Models for Assessing Fractional Distribution, Oral Absorption, and Series-Compartment Models of Hepatic Clearance.Drug metabolism and disposition: the biological fate of chemicals · 2023Article
- The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment.International journal of environmental research and public health · 2023Review
- PBPK Simulation-Based Evaluation of Ganciclovir Crystalluria Risk Factors: Effect of Renal Impairment, Old Age, and Low Fluid Intake.The AAPS journal · 2021Article
- Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system.Scientific reports · 2021Article
- 3D cell culture models: Drug pharmacokinetics, safety assessment, and regulatory consideration.Clinical and translational science · 2021Review
- Novel Mechanistic PBPK Model to Predict Renal Clearance in Varying Stages of CKD by Incorporating Tubular Adaptation and Dynamic Passive Reabsorption.CPT: pharmacometrics & systems pharmacology · 2020Article
- Mechanistic PBPK Modeling of Urine pH Effect on Renal and Systemic Disposition of Methamphetamine and Amphetamine.The Journal of pharmacology and experimental therapeutics · 2020Article
- A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations.CPT: pharmacometrics & systems pharmacology · 2020Article
- Predicting tubular reabsorption with a human kidney proximal tubule tissue-on-a-chip and physiologically-based modeling.Toxicology in vitro : an international journal published in association with BIBRA · 2020Article
- Sampling Site Has a Critical Impact on Physiologically Based Pharmacokinetic Modeling.The Journal of pharmacology and experimental therapeutics · 2020Article
- Development of an in silico prediction system of human renal excretion and clearance from chemical structure information incorporating fraction unbound in plasma as a descriptor.Scientific reports · 2019Article
- Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies.Clinical pharmacokinetics · 2019Review
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
Abstract
Renal clearance is usually predicted via empirical approaches including quantitative structure activity relationship and allometric scaling. Recently, mechanistic prediction approaches using in silico kidney models have been proposed. However, empirical scaling factors are typically used to adjust for either passive diffusion or active secretion, to acceptably predict renal clearances. The goal of this study was to establish a renal clearance simulation tool that allows prediction of renal clearance (filtration and pH-dependent passive reabsorption) from in vitro permeability data. A 35-compartment physiologically based mechanistic kidney model was developed based on human physiology. The model was verified using 46 test compounds, including neutrals, acids, bases, and zwitterions. The feasibility of incorporating active secretion and pH-dependent bidirectional passive diffusion into the model was demonstrated using para-aminohippuric acid (PAH), cimetidine, memantine, and salicylic acid. The developed model enables simulation of renal clearance from in vitro permeability data, with predicted renal clearance within twofold of observed for 87% of the test drugs.
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.