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Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population

Elevated serum creatinine (S(Cr)) caused by the inhibition of renal transporter(s) may be misinterpreted as kidney injury. The interpretation is more complicated in patients with chronic kidney disease (CKD) due to altered disposition of creatinine and renal transporter inhibitors. A clinical study...

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Autores principales: Takita, Hiroyuki, Scotcher, Daniel, Chinnadurai, Rajkumar, Kalra, Philip A., Galetin, Aleksandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762809/
https://www.ncbi.nlm.nih.gov/pubmed/33049120
http://dx.doi.org/10.1002/psp4.12566
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author Takita, Hiroyuki
Scotcher, Daniel
Chinnadurai, Rajkumar
Kalra, Philip A.
Galetin, Aleksandra
author_facet Takita, Hiroyuki
Scotcher, Daniel
Chinnadurai, Rajkumar
Kalra, Philip A.
Galetin, Aleksandra
author_sort Takita, Hiroyuki
collection PubMed
description Elevated serum creatinine (S(Cr)) caused by the inhibition of renal transporter(s) may be misinterpreted as kidney injury. The interpretation is more complicated in patients with chronic kidney disease (CKD) due to altered disposition of creatinine and renal transporter inhibitors. A clinical study was conducted in 17 patients with CKD (estimated glomerular filtration rate 15–59 mL/min/1.73 m(2)); changes in S(Cr) were monitored during trimethoprim treatment (100–200 mg/day), administered to prevent recurrent urinary infection, relative to the baseline level. Additional S(Cr)‐interaction data with trimethoprim, cimetidine, and famotidine in patients with CKD were collated from the literature. Our published physiologically‐based creatinine model was extended to predict the effect of the CKD on S(Cr) and creatinine‐drug interaction. The creatinine‐CKD model incorporated age/sex‐related differences in creatinine synthesis, CKD‐related glomerular filtration deterioration; change in transporter activity either proportional or disproportional to glomerular filtration rate (GFR) decline were explored. Optimized models successfully recovered baseline S(Cr) from 64 patients with CKD (geometric mean fold‐error of 1.1). Combined with pharmacokinetic models of inhibitors, the creatinine model was used to simulate transporter‐mediated creatinine‐drug interactions. Use of inhibitor unbound plasma concentrations resulted in 66% of simulated S(Cr) interaction data within the prediction limits, with cimetidine interaction significantly underestimated. Assuming that transporter activity deteriorates disproportional to GFR decline resulted in higher predicted sensitivity to transporter inhibition in patients with CKD relative to healthy patients, consistent with sparse clinical data. For the first time, this novel modelling approach enables quantitative prediction of S(Cr) in CKD and delineation of the effect of disease and renal transporter inhibition in this patient population.
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spelling pubmed-77628092020-12-28 Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population Takita, Hiroyuki Scotcher, Daniel Chinnadurai, Rajkumar Kalra, Philip A. Galetin, Aleksandra CPT Pharmacometrics Syst Pharmacol Research Elevated serum creatinine (S(Cr)) caused by the inhibition of renal transporter(s) may be misinterpreted as kidney injury. The interpretation is more complicated in patients with chronic kidney disease (CKD) due to altered disposition of creatinine and renal transporter inhibitors. A clinical study was conducted in 17 patients with CKD (estimated glomerular filtration rate 15–59 mL/min/1.73 m(2)); changes in S(Cr) were monitored during trimethoprim treatment (100–200 mg/day), administered to prevent recurrent urinary infection, relative to the baseline level. Additional S(Cr)‐interaction data with trimethoprim, cimetidine, and famotidine in patients with CKD were collated from the literature. Our published physiologically‐based creatinine model was extended to predict the effect of the CKD on S(Cr) and creatinine‐drug interaction. The creatinine‐CKD model incorporated age/sex‐related differences in creatinine synthesis, CKD‐related glomerular filtration deterioration; change in transporter activity either proportional or disproportional to glomerular filtration rate (GFR) decline were explored. Optimized models successfully recovered baseline S(Cr) from 64 patients with CKD (geometric mean fold‐error of 1.1). Combined with pharmacokinetic models of inhibitors, the creatinine model was used to simulate transporter‐mediated creatinine‐drug interactions. Use of inhibitor unbound plasma concentrations resulted in 66% of simulated S(Cr) interaction data within the prediction limits, with cimetidine interaction significantly underestimated. Assuming that transporter activity deteriorates disproportional to GFR decline resulted in higher predicted sensitivity to transporter inhibition in patients with CKD relative to healthy patients, consistent with sparse clinical data. For the first time, this novel modelling approach enables quantitative prediction of S(Cr) in CKD and delineation of the effect of disease and renal transporter inhibition in this patient population. John Wiley and Sons Inc. 2020-11-23 2020-12 /pmc/articles/PMC7762809/ /pubmed/33049120 http://dx.doi.org/10.1002/psp4.12566 Text en © 2020 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research
Takita, Hiroyuki
Scotcher, Daniel
Chinnadurai, Rajkumar
Kalra, Philip A.
Galetin, Aleksandra
Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population
title Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population
title_full Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population
title_fullStr Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population
title_full_unstemmed Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population
title_short Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population
title_sort physiologically‐based pharmacokinetic modelling of creatinine‐drug interactions in the chronic kidney disease population
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762809/
https://www.ncbi.nlm.nih.gov/pubmed/33049120
http://dx.doi.org/10.1002/psp4.12566
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