Literature DB >> 24214317

Towards quantitation of the effects of renal impairment and probenecid inhibition on kidney uptake and efflux transporters, using physiologically based pharmacokinetic modelling and simulations.

Vicky Hsu1, Manuela de L T Vieira1,2, Ping Zhao3, Lei Zhang1, Jenny Huimin Zheng1, Anna Nordmark4, Eva Gil Berglund4, Kathleen M Giacomini5, Shiew-Mei Huang1.   

Abstract

BACKGROUND AND OBJECTIVES: The kidney is a major drug-eliminating organ. Renal impairment or concomitant use of transporter inhibitors may decrease active secretion and increase exposure to a drug that is a substrate of kidney secretory transporters. However, prediction of the effects of patient factors on kidney transporters remains challenging because of the multiplicity of transporters and the lack of understanding of their abundance and specificity. The objective of this study was to use physiologically based pharmacokinetic (PBPK) modelling to evaluate the effects of patient factors on kidney transporters.
METHODS: Models for three renally cleared drugs (oseltamivir carboxylate, cidofovir and cefuroxime) were developed using a general PBPK platform, with the contributions of net basolateral uptake transport (T up,b) and apical efflux transport (T eff,a) being specifically defined. RESULTS AND
CONCLUSION: We demonstrated the practical use of PBPK models to: (1) define transporter-mediated renal secretion, using plasma and urine data; (2) inform a change in the system-dependent parameter (≥10-fold reduction in the functional 'proximal tubule cells per gram kidney') in severe renal impairment that is responsible for the decreased secretory transport activities of test drugs; (3) derive an in vivo, plasma unbound inhibition constant of T up,b by probenecid (≤1 μM), based on observed drug interaction data; and (4) suggest a plausible mechanism of probenecid preferentially inhibiting T up,b in order to alleviate cidofovir-induced nephrotoxicity.

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Year:  2014        PMID: 24214317      PMCID: PMC3927056          DOI: 10.1007/s40262-013-0117-y

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  25 in total

1.  Cefuroxime: human pharmacokinetics..

Authors:  R D Foord
Journal:  Antimicrob Agents Chemother       Date:  1976-05       Impact factor: 5.191

Review 2.  Modeling and predicting drug pharmacokinetics in patients with renal impairment.

Authors:  Karen Rowland Yeo; Mohsen Aarabi; Masoud Jamei; Amin Rostami-Hodjegan
Journal:  Expert Rev Clin Pharmacol       Date:  2011-03       Impact factor: 5.045

3.  The anti-influenza drug oseltamivir exhibits low potential to induce pharmacokinetic drug interactions via renal secretion-correlation of in vivo and in vitro studies.

Authors:  George Hill; Tomas Cihlar; Charles Oo; Edmund S Ho; Ken Prior; Hugh Wiltshire; Jo Barrett; Baulian Liu; Penny Ward
Journal:  Drug Metab Dispos       Date:  2002-01       Impact factor: 3.922

4.  Development of a physiologically based model for oseltamivir and simulation of pharmacokinetics in neonates and infants.

Authors:  Neil Parrott; Brian Davies; Gerhard Hoffmann; Annette Koerner; Thierry Lave; Eric Prinssen; Elizabeth Theogaraj; Thomas Singer
Journal:  Clin Pharmacokinet       Date:  2011-09       Impact factor: 6.447

5.  Characterization of organic anion transport inhibitors using cells stably expressing human organic anion transporters.

Authors:  M Takeda; S Narikawa; M Hosoyamada; S H Cha; T Sekine; H Endou
Journal:  Eur J Pharmacol       Date:  2001-05-11       Impact factor: 4.432

6.  Evaluation of exposure change of nonrenally eliminated drugs in patients with chronic kidney disease using physiologically based pharmacokinetic modeling and simulation.

Authors:  Ping Zhao; Manuela de L T Vieira; Joseph A Grillo; Pengfei Song; Ta-Chen Wu; Jenny H Zheng; Vikram Arya; Eva Gil Berglund; Arthur J Atkinson; Yuichi Sugiyama; K Sandy Pang; Kellie S Reynolds; Darrell R Abernethy; Lei Zhang; Lawrence J Lesko; Shiew-Mei Huang
Journal:  J Clin Pharmacol       Date:  2012-01       Impact factor: 3.126

7.  In vitro and in vivo assessment of renal drug transporters in the disposition of mesna and dimesna.

Authors:  M J Cutler; B L Urquhart; T J Velenosi; H E Meyer Zu Schwabedissen; G K Dresser; B F Leake; R G Tirona; R B Kim; D J Freeman
Journal:  J Clin Pharmacol       Date:  2011-04-19       Impact factor: 3.126

8.  Physicochemical determinants of human renal clearance.

Authors:  Manthena V S Varma; Bo Feng; R Scott Obach; Matthew D Troutman; Jonathan Chupka; Howard R Miller; Ayman El-Kattan
Journal:  J Med Chem       Date:  2009-08-13       Impact factor: 7.446

9.  The role of the interstitium of the renal cortex in renal disease.

Authors:  A Bohle; H Christ; K E Grund; S Mackensen
Journal:  Contrib Nephrol       Date:  1979       Impact factor: 1.580

Review 10.  A framework for assessing inter-individual variability in pharmacokinetics using virtual human populations and integrating general knowledge of physical chemistry, biology, anatomy, physiology and genetics: A tale of 'bottom-up' vs 'top-down' recognition of covariates.

Authors:  Masoud Jamei; Gemma L Dickinson; Amin Rostami-Hodjegan
Journal:  Drug Metab Pharmacokinet       Date:  2009       Impact factor: 3.614

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  34 in total

Review 1.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification.

Authors:  Jennifer E Sager; Jingjing Yu; Isabelle Ragueneau-Majlessi; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2015-08-21       Impact factor: 3.922

2.  Prediction of the Effect of Renal Impairment on the Pharmacokinetics of New Drugs.

Authors:  Elisa Borella; Italo Poggesi; Paolo Magni
Journal:  Clin Pharmacokinet       Date:  2018-04       Impact factor: 6.447

3.  Physiologically Based Pharmacokinetic (PBPK) Modeling of Pitavastatin and Atorvastatin to Predict Drug-Drug Interactions (DDIs).

Authors:  Peng Duan; Ping Zhao; Lei Zhang
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2017-08       Impact factor: 2.441

4.  Drug Transporters in Xenobiotic Disposition and Pharmacokinetic Prediction.

Authors:  Qingcheng Mao; Yurong Lai; Joanne Wang
Journal:  Drug Metab Dispos       Date:  2018-05       Impact factor: 3.922

5.  Advancing Predictions of Tissue and Intracellular Drug Concentrations Using In Vitro, Imaging and Physiologically Based Pharmacokinetic Modeling Approaches.

Authors:  Yingying Guo; Xiaoyan Chu; Neil J Parrott; Kim L R Brouwer; Vicky Hsu; Swati Nagar; Pär Matsson; Pradeep Sharma; Jan Snoeys; Yuichi Sugiyama; Daniel Tatosian; Jashvant D Unadkat; Shiew-Mei Huang; Aleksandra Galetin
Journal:  Clin Pharmacol Ther       Date:  2018-09-12       Impact factor: 6.875

6.  Development of a Physiologically Based Pharmacokinetic Model to Predict Disease-Mediated Therapeutic Protein-Drug Interactions: Modulation of Multiple Cytochrome P450 Enzymes by Interleukin-6.

Authors:  Xiling Jiang; Yanli Zhuang; Zhenhua Xu; Weirong Wang; Honghui Zhou
Journal:  AAPS J       Date:  2016-03-09       Impact factor: 4.009

7.  Physiologically based pharmacokinetic modelling and in vivo [I]/K(i) accurately predict P-glycoprotein-mediated drug-drug interactions with dabigatran etexilate.

Authors:  Yuansheng Zhao; Zhe-Yi Hu
Journal:  Br J Pharmacol       Date:  2014-02       Impact factor: 8.739

Review 8.  Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part II: Mechanistic Models and In Vitro-In Vivo Extrapolation.

Authors:  Daniel Scotcher; Christopher Jones; Maria Posada; Aleksandra Galetin; Amin Rostami-Hodjegan
Journal:  AAPS J       Date:  2016-08-09       Impact factor: 4.009

Review 9.  Prediction of pharmacokinetics and drug-drug interactions when hepatic transporters are involved.

Authors:  Rui Li; Hugh A Barton; Manthena V Varma
Journal:  Clin Pharmacokinet       Date:  2014-08       Impact factor: 6.447

10.  Physiologically based pharmacokinetic modeling of impaired carboxylesterase-1 activity: effects on oseltamivir disposition.

Authors:  Zhe-Yi Hu; Andrea N Edginton; S Casey Laizure; Robert B Parker
Journal:  Clin Pharmacokinet       Date:  2014-09       Impact factor: 6.447

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