Physicochemical Determinants of Human Renal Clearance

Varma, Manthena V.; Feng, Bo; Obach, R. Scott; Troutman, Matthew D.; Chupka, Jonathan; Miller, Howard L.; El‐Kattan, Ayman

doi:10.1021/jm900403j

Cited by 175 publications

(191 citation statements)

References 43 publications

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“…This is generally consistent with our observations that permeability is inversely related to rat BE, and the compounds with high molecular mass (Ͼ400 Da) and low permeability (Ͻ2.5 ϫ 10 Ϫ6 cm/s) are considerably eliminated in bile. As noted in our previous (Varma et al, 2009) and the current study, low-permeable compounds with low molecular mass are primarily eliminated in urine, whereas larger size compounds are excreted in bile. The apparent molecular mass cutoff noted for BE may indicate that the potential substrate specificity of the transporters involved in hepatobiliary transport is associated with molecular mass.…”

Section: Discussionsupporting

confidence: 81%

“…4; Table 1). Previously, using a dataset of human renal clearance for 391 compounds, we observed that the bases dominate the list of compounds secreted in urine (46%), with acids accounting for only 31% (Varma et al, 2009). A rather predominant presence of acids in the %BE Ն 10 subset (Fig.…”

Section: Discussionmentioning

confidence: 89%

“…The parametric t test (unpaired, two-tailed, unequal variance) was used to determine the significance. However, because the distributions of some properties are skewed away from normality, data were also analyzed by the nonparametric Mann-Whitney test (two-tailed) (Varma et al, 2009(Varma et al, , 2010b.…”

Section: Methodsmentioning

confidence: 99%

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Physicochemical Property Space of Hepatobiliary Transport and Computational Models for Predicting Rat Biliary Excretion

Varma

Chang²,

Lai³

et al. 2012

Drug Metab Dispos

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ABSTRACT:Biliary excretion (BE) is a major elimination pathway, and its prediction is particularly important for optimization of systemic and/or target-site exposure of new molecular entities. The objective is to characterize the physicochemical space associated with hepatobiliary transport and rat BE and to develop in silico models. BE of 123 in-house compounds was obtained using the bile-duct cannulated rat model. Human and rat hepatic uptake transporters (hOATP1B1, hOATP1B3, hOATP2B1, and rOatp1b2) substrates (n ‫؍‬ 183) were identified using transfected cells. Furthermore, the datasets were extended by adding BE of 163 compounds and 97 organic anion transporting polypeptide (OATP) substrates from the literature. Approximately 60% of compounds showing percentage of BE (%BE) > 10 are anions, with mean BE of anions (36%) more than 3-fold higher than that of nonacids (11%). Compounds with %BE > 10 are found to have high molecular mass, large polar surface area, more rotatable bonds, and high H-bond count, whereas the lipophilicity and passive membrane permeability are lower compared with compounds with %BE < 10. According to statistical analysis and principal component analysis, hOATPs and rOatp1b2 substrates showed physicochemical characteristics that were similar to those of the %BE > 10 dataset. We further build categorical in silico models to predict rat BE, and the models (gradient boosting machine and scoring function) developed showed 80% predictability in identifying the rat BE bins (%BE > 10 or < 10). In conclusion, the significant overlap of the property space of OATP substrates and rat BE suggests a predominant role of sinusoidal uptake transporters in biliary elimination. Categorical in silico models to predict rat BE were developed, and successful predictions were achieved.

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Section: Discussionsupporting

confidence: 81%

Section: Discussionmentioning

confidence: 89%

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Physicochemical Property Space of Hepatobiliary Transport and Computational Models for Predicting Rat Biliary Excretion

Varma

Chang²,

Lai³

et al. 2012

Drug Metab Dispos

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“…glomerular filtration, active secretion and tubular reabsorption. Passive renal tubular reabsorption of drugs has been correlated with drug lipophilicity and other physico-chemical properties (23,24). Recently, a quantitative structurepharmacokinetic relationship (QSPKR) model has been developed for prediction of reabsorption clearance, although prior information on the dominant process (reabsorption or secretion) and/or Biopharmaceutical Drug Disposition and Classification System (BDDCS) class is required (25).…”

Section: Measurement Of Renal Passive Tubular Permeability In Vitromentioning

confidence: 99%

Key to Opening Kidney for In Vitro–In Vivo Extrapolation Entrance in Health and Disease: Part I: In Vitro Systems and Physiological Data

Scotcher

Jones²,

Posada

et al. 2016

AAPS J

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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.

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“…a Compounds classified as exhibiting net secretory renal CL based on threshold defined by Varma et al (2009) where CLr Ͼ 1.2 ⅐ f up ⅐ glomerular filtration rate.…”

Section: Analysis Of the øIe-tozer Model Of Drug Distributionmentioning

confidence: 99%

Use of the Øie-Tozer Model in Understanding Mechanisms and Determinants of Drug Distribution

Waters¹,

Lombardo²

2010

Drug Metab Dispos

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Physicochemical Determinants of Human Renal Clearance

Cited by 175 publications

References 43 publications

Physicochemical Property Space of Hepatobiliary Transport and Computational Models for Predicting Rat Biliary Excretion

Physicochemical Property Space of Hepatobiliary Transport and Computational Models for Predicting Rat Biliary Excretion

Key to Opening Kidney for In Vitro–In Vivo Extrapolation Entrance in Health and Disease: Part I: In Vitro Systems and Physiological Data

Use of the Øie-Tozer Model in Understanding Mechanisms and Determinants of Drug Distribution

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