Literature DB >> 31857146

Predicting tubular reabsorption with a human kidney proximal tubule tissue-on-a-chip and physiologically-based modeling.

Courtney Sakolish1, Zunwei Chen2, Chimeddulam Dalaijamts3, Kusumica Mitra4, Yina Liu5, Tracy Fulton6, Terry L Wade7, Edward J Kelly8, Ivan Rusyn9, Weihsueh A Chiu10.   

Abstract

Kidney is a major route of xenobiotic excretion, but the accuracy of preclinical data for predicting in vivo clearance is limited by species differences and non-physiologic 2D culture conditions. Microphysiological systems can potentially increase predictive accuracy due to their more realistic 3D environment and incorporation of dynamic flow. We used a renal proximal tubule microphysiological device to predict renal reabsorption of five compounds: creatinine (negative control), perfluorooctanoic acid (positive control), cisplatin, gentamicin, and cadmium. We perfused compound-containing media to determine renal uptake/reabsorption, adjusted for non-specific binding. A physiologically-based parallel tube model was used to model reabsorption kinetics and make predictions of overall in vivo renal clearance. For all compounds tested, the kidney tubule chip combined with physiologically-based modeling reproduces qualitatively and quantitatively in vivo tubular reabsorption and clearance. However, because the in vitro device lacks filtration and tubular secretion components, additional information on protein binding and the importance of secretory transport is needed in order to make accurate predictions. These and other limitations, such as the presence of non-physiological compounds such as antibiotics and bovine serum albumin in media and the need to better characterize degree of expression of important transporters, highlight some of the challenges with using microphysiological devices to predict in vivo pharmacokinetics.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Kidney; Microphysiological systems; Pharmacokinetics; Renal clearance; Tissue-on-a-chip; Tubular reabsorption

Mesh:

Substances:

Year:  2019        PMID: 31857146      PMCID: PMC7053805          DOI: 10.1016/j.tiv.2019.104752

Source DB:  PubMed          Journal:  Toxicol In Vitro        ISSN: 0887-2333            Impact factor:   3.500


  70 in total

1.  Reporting estimated GFR: a laboratory perspective.

Authors:  W Greg Miller
Journal:  Am J Kidney Dis       Date:  2008-10       Impact factor: 8.860

2.  Tissue engineering of a bioartificial renal tubule.

Authors:  S M MacKay; A J Funke; D A Buffington; H D Humes
Journal:  ASAIO J       Date:  1998 May-Jun       Impact factor: 2.872

Review 3.  Organs-on-a-chip: Current applications and consideration points for in vitro ADME-Tox studies.

Authors:  Seiichi Ishida
Journal:  Drug Metab Pharmacokinet       Date:  2018-01-11       Impact factor: 3.614

Review 4.  Human nephron number: implications for health and disease.

Authors:  John F Bertram; Rebecca N Douglas-Denton; Boucar Diouf; Michael D Hughson; Wendy E Hoy
Journal:  Pediatr Nephrol       Date:  2011-05-22       Impact factor: 3.714

5.  Mechanism of cisplatin proximal tubule toxicity revealed by integrating transcriptomics, proteomics, metabolomics and biokinetics.

Authors:  Anja Wilmes; Chris Bielow; Christina Ranninger; Patricia Bellwon; Lydia Aschauer; Alice Limonciel; Hubert Chassaigne; Theresa Kristl; Stephan Aiche; Christian G Huber; Claude Guillou; Philipp Hewitt; Martin O Leonard; Wolfgang Dekant; Frederic Bois; Paul Jennings
Journal:  Toxicol In Vitro       Date:  2014-10-23       Impact factor: 3.500

Review 6.  Molecular and ionic mimicry and the transport of toxic metals.

Authors:  Christy C Bridges; Rudolfs K Zalups
Journal:  Toxicol Appl Pharmacol       Date:  2005-05-01       Impact factor: 4.219

Review 7.  Renal tubule albumin transport.

Authors:  Michael Gekle
Journal:  Annu Rev Physiol       Date:  2005       Impact factor: 19.318

8.  Nonlinear renal clearance of ultrafilterable platinum in patients treated with cis-dichlorodiammineplatinum (II).

Authors:  P A Reece; I Stafford; J Russell; P G Gill
Journal:  Cancer Chemother Pharmacol       Date:  1985       Impact factor: 3.333

9.  Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements.

Authors:  Dana B Barr; Lynn C Wilder; Samuel P Caudill; Amanda J Gonzalez; Lance L Needham; James L Pirkle
Journal:  Environ Health Perspect       Date:  2005-02       Impact factor: 9.031

10.  Interaction of perfluorooctanoic acid with human serum albumin.

Authors:  Ling-Ling Wu; Hong-Wen Gao; Nai-Yun Gao; Fang-Fang Chen; Ling Chen
Journal:  BMC Struct Biol       Date:  2009-05-14
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  4 in total

1.  Microphysiological Systems Evaluation: Experience of TEX-VAL Tissue Chip Testing Consortium.

Authors:  Ivan Rusyn; Courtney Sakolish; Yuki Kato; Clifford Stephan; Leoncio Vergara; Philip Hewitt; Vasanthi Bhaskaran; Myrtle Davis; Rhiannon N Hardwick; Stephen S Ferguson; Jason P Stanko; Piyush Bajaj; Karissa Adkins; Nisha S Sipes; E Sidney Hunter; Maria T Baltazar; Paul L Carmichael; Kritika Sadh; Richard A Becker
Journal:  Toxicol Sci       Date:  2022-07-28       Impact factor: 4.109

2.  Kidney microphysiological models for nephrotoxicity assessment.

Authors:  Anish Mahadeo; Catherine K Yeung; Jonathan Himmelfarb; Edward J Kelly
Journal:  Curr Opin Toxicol       Date:  2022-03-30

Review 3.  Breakthroughs and Applications of Organ-on-a-Chip Technology.

Authors:  Mufeeda C Koyilot; Priyadarshini Natarajan; Clayton R Hunt; Sonish Sivarajkumar; Romy Roy; Shreeram Joglekar; Shruti Pandita; Carl W Tong; Shamsudheen Marakkar; Lakshminarayanan Subramanian; Shalini S Yadav; Anoop V Cherian; Tej K Pandita; Khader Shameer; Kamlesh K Yadav
Journal:  Cells       Date:  2022-06-02       Impact factor: 7.666

Review 4.  Microphysiological systems: What it takes for community adoption.

Authors:  Passley Hargrove-Grimes; Lucie A Low; Danilo A Tagle
Journal:  Exp Biol Med (Maywood)       Date:  2021-04-25
  4 in total

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