ReviewThe AAPS journal2016
Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part I: In Vitro Systems and Physiological Data.
Review in The AAPS journal, 2016. 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.
- Human and rat renal proximal tubule in vitro models for ADME applications.Archives of toxicology · 2025Review
- Physiologically based pharmacokinetic modeling of small molecules: How much progress have we made?Drug metabolism and disposition: the biological fate of chemicals · 2025Review
- An in vitro-in silico workflow for predicting renal clearance of PFAS.Toxicology and applied pharmacology · 2024Article
- Physiologically Based Pharmacokinetic Modelling to Predict Pharmacokinetics of Enavogliflozin, a Sodium-Dependent Glucose Transporter 2 Inhibitor, in Humans.Pharmaceutics · 2023Article
- Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment.Archives of toxicology · 2022Article
- IVIVE: Facilitating the Use ofToxics · 2022Review
- Application of the Adverse Outcome Pathway Concept toFrontiers in toxicology · 2022Article
- 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
- The Combination of Cell Cultured Technology and In Silico Model to Inform the Drug Development.Pharmaceutics · 2021Review
- Article
- In Vivo-to-In Vitro Extrapolation of Transporter-Mediated Renal Clearance: Relative Expression Factor Versus Relative Activity Factor Approach.Drug metabolism and disposition: the biological fate of chemicals · 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
- Prediction of Metabolite-to-Parent Drug Exposure: Derivation and Application of a Mechanistic Static Model.Clinical and translational science · 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
- Translational Assessment of Drug-Induced Proximal Tubule Injury Using a Kidney Microphysiological System.CPT: pharmacometrics & systems pharmacology · 2019Article
- Interpretation of Non-Clinical Data for Prediction of Human Pharmacokinetic Parameters: In Vitro-In Vivo Extrapolation and Allometric Scaling.Pharmaceutics · 2019Review
- A Population WB-PBPK Model of Colistin and its Prodrug CMS in Pigs: Focus on the Renal Distribution and Excretion.Pharmaceutical research · 2018Article
- Microsomal and Cytosolic Scaling Factors in Dog and Human Kidney Cortex and Application for In Vitro-In Vivo Extrapolation of Renal Metabolic Clearance.Drug metabolism and disposition: the biological fate of chemicals · 2017Article
- Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations.The Journal of pharmacology and experimental therapeutics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The programme for the 2015 AAPS Annual Meeting and Exhibition (Orlando, FL; 25-29 October 2015) included a sunrise session presenting an overview of the state-of-the-art tools for in vitro-in vivo extrapolation (IVIVE) and mechanistic prediction of renal drug disposition. These concepts are based on approaches developed for prediction of hepatic clearance, with consideration of scaling factors physiologically relevant to kidney and the unique and complex structural organisation of this organ. Physiologically relevant kidney models require a number of parameters for mechanistic description of processes, supported by quantitative information on renal physiology (system parameters) and in vitro/in silico drug-related data. This review expands upon the themes raised during the session and highlights the importance of high quality in vitro drug data generated in appropriate experimental setup and robust system-related information for successful IVIVE of renal drug disposition. The different in vitro systems available for studying renal drug metabolism and transport are summarised and recent developments involving state-of-the-art technologies highlighted. Current gaps and uncertainties associated with system parameters related to human kidney for the development of physiologically based pharmacokinetic (PBPK) model and quantitative prediction of renal drug disposition, excretion, and/or metabolism are identified.
Indexed as
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27365096What 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.