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Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system

Opioid overdose, dependence, and addiction are a major public health crisis. Patients with chronic kidney disease (CKD) are at high risk of opioid overdose, therefore novel methods that provide accurate prediction of renal clearance (CL(r)) and systemic disposition of opioids in CKD patients can fac...

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Autores principales: Imaoka, Tomoki, Huang, Weize, Shum, Sara, Hailey, Dale W., Chang, Shih-Yu, Chapron, Alenka, Yeung, Catherine K., Himmelfarb, Jonathan, Isoherranen, Nina, Kelly, Edward J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8560754/
https://www.ncbi.nlm.nih.gov/pubmed/34725352
http://dx.doi.org/10.1038/s41598-021-00338-y
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author Imaoka, Tomoki
Huang, Weize
Shum, Sara
Hailey, Dale W.
Chang, Shih-Yu
Chapron, Alenka
Yeung, Catherine K.
Himmelfarb, Jonathan
Isoherranen, Nina
Kelly, Edward J.
author_facet Imaoka, Tomoki
Huang, Weize
Shum, Sara
Hailey, Dale W.
Chang, Shih-Yu
Chapron, Alenka
Yeung, Catherine K.
Himmelfarb, Jonathan
Isoherranen, Nina
Kelly, Edward J.
author_sort Imaoka, Tomoki
collection PubMed
description Opioid overdose, dependence, and addiction are a major public health crisis. Patients with chronic kidney disease (CKD) are at high risk of opioid overdose, therefore novel methods that provide accurate prediction of renal clearance (CL(r)) and systemic disposition of opioids in CKD patients can facilitate the optimization of therapeutic regimens. The present study aimed to predict renal clearance and systemic disposition of morphine and its active metabolite morphine-6-glucuronide (M6G) in CKD patients using a vascularized human proximal tubule microphysiological system (VPT-MPS) coupled with a parent-metabolite full body physiologically-based pharmacokinetic (PBPK) model. The VPT-MPS, populated with a human umbilical vein endothelial cell (HUVEC) channel and an adjacent human primary proximal tubular epithelial cells (PTEC) channel, successfully demonstrated secretory transport of morphine and M6G from the HUVEC channel into the PTEC channel. The in vitro data generated by VPT-MPS were incorporated into a mechanistic kidney model and parent-metabolite full body PBPK model to predict CL(r) and systemic disposition of morphine and M6G, resulting in successful prediction of CL(r) and the plasma concentration–time profiles in both healthy subjects and CKD patients. A microphysiological system together with mathematical modeling successfully predicted renal clearance and systemic disposition of opioids in CKD patients and healthy subjects.
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spelling pubmed-85607542021-11-03 Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system Imaoka, Tomoki Huang, Weize Shum, Sara Hailey, Dale W. Chang, Shih-Yu Chapron, Alenka Yeung, Catherine K. Himmelfarb, Jonathan Isoherranen, Nina Kelly, Edward J. Sci Rep Article Opioid overdose, dependence, and addiction are a major public health crisis. Patients with chronic kidney disease (CKD) are at high risk of opioid overdose, therefore novel methods that provide accurate prediction of renal clearance (CL(r)) and systemic disposition of opioids in CKD patients can facilitate the optimization of therapeutic regimens. The present study aimed to predict renal clearance and systemic disposition of morphine and its active metabolite morphine-6-glucuronide (M6G) in CKD patients using a vascularized human proximal tubule microphysiological system (VPT-MPS) coupled with a parent-metabolite full body physiologically-based pharmacokinetic (PBPK) model. The VPT-MPS, populated with a human umbilical vein endothelial cell (HUVEC) channel and an adjacent human primary proximal tubular epithelial cells (PTEC) channel, successfully demonstrated secretory transport of morphine and M6G from the HUVEC channel into the PTEC channel. The in vitro data generated by VPT-MPS were incorporated into a mechanistic kidney model and parent-metabolite full body PBPK model to predict CL(r) and systemic disposition of morphine and M6G, resulting in successful prediction of CL(r) and the plasma concentration–time profiles in both healthy subjects and CKD patients. A microphysiological system together with mathematical modeling successfully predicted renal clearance and systemic disposition of opioids in CKD patients and healthy subjects. Nature Publishing Group UK 2021-11-01 /pmc/articles/PMC8560754/ /pubmed/34725352 http://dx.doi.org/10.1038/s41598-021-00338-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Imaoka, Tomoki
Huang, Weize
Shum, Sara
Hailey, Dale W.
Chang, Shih-Yu
Chapron, Alenka
Yeung, Catherine K.
Himmelfarb, Jonathan
Isoherranen, Nina
Kelly, Edward J.
Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system
title Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system
title_full Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system
title_fullStr Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system
title_full_unstemmed Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system
title_short Bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system
title_sort bridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8560754/
https://www.ncbi.nlm.nih.gov/pubmed/34725352
http://dx.doi.org/10.1038/s41598-021-00338-y
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