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Publication Detail

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

Authors: Imaoka, Tomoki; Huang, Weize; Shum, Sara; Hailey, Dale W; Chang, Shih-Yu; Chapron, Alenka; Yeung, Catherine K; Himmelfarb, Jonathan; Isoherranen, Nina; Kelly, Edward J

Published In Sci Rep, (2021 11 01)

Abstract: 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 (CLr) 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 CLr and systemic disposition of morphine and M6G, resulting in successful prediction of CLr 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.

PubMed ID: 34725352 Exiting the NIEHS site

MeSH Terms: Analgesics, Opioid/pharmacokinetics*; Biological Transport; Cell Line; Computer Simulation; Human Umbilical Vein Endothelial Cells; Humans; Kidney Tubules, Proximal/metabolism*; Models, Biological; Renal Insufficiency, Chronic/metabolism

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