ArticleToxicology2026
An in vitro-in silico workflow for predicting renal clearance of environmental chemicals and drugs.
Article in Toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- New Frontiers of Drug Development Through the Use of New Approach Methodologies.The AAPS journal · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Accurate prediction of human renal clearance is essential for evaluating drug pharmacokinetics and environmental chemical risks, yet current methods often neglect rate-determining active transporter-mediated mechanisms. This study aimed to expand and validate a unified in vitro-in silico workflow for predicting renal clearance of both pharmaceuticals and per- and polyfluoroalkyl substances (PFAS) with varied elimination half-life ranges. We hypothesized that robust predictions of human renal clearance across diverse chemical classes can be achieved by combining human proximal tubule cell-based permeability/uptake assays with computational models of renal physiology. Human RPTEC/TERT1 cells and their OAT1-overexpressing variant were cultured in 96-well plates and Transwells to measure uptake, directional transport, and intracellular accumulation of 36 chemicals (28 PFAS, 7 drugs, 1 cosmetic ingredient). Time-course concentration data were used for either two-compartment (96-well) or three-compartment (Transwell) kinetic models. Permeability parameters were integrated into a physiologically-based kidney model for in vitro-to-in vivo extrapolation (IVIVE). A follow-up validation study with PFAS used independent experiments to derive similar predictions. Transwell-based three-compartment modeling yielded the most accurate absolute renal clearance predictions for rapidly eliminated drugs. For slowly cleared PFAS, simpler 96-well two-compartment modeling provided high correlation with observed human clearance, accurately distinguishing low-, medium- and high-clearance compounds; model predictions were consistently human health-protective. The PFAS validation study confirmed reproducibility of the approach. The proposed workflow is a conservative, scalable, mechanistically-informed and empirically-benchmarked approach for predicting renal clearance in humans. Transwell assays best support drug clearance estimation, whereas high-throughput 96-well formats enable reliable relative clearance ranking for PFAS, supporting both pharmaceutical development and environmental chemical risk assessment.
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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 Socratic graph.