biostudies-literatureImaoka TNational Center for Advancing Translational SciencesNational Institute of Environmental Health SciencesNCATSNCATS NIH HHSNIDA NIH HHSNIEHS NIH HHSNational Institute of General Medical SciencesNational Institute on Drug AbuseNIGMS NIH HHS21356https://www.ebi.ac.uk/biostudies/studies/S-EPMC8560754biostudies-literatureUnknown11(1)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.Scientific reportsBridging the gap between in silico and in vivo by modeling opioid disposition in a kidney proximal tubule microphysiological system.PMC8560754P01DA032507UG3 TR003288R01GM1213545UG3TR003288UG3TR002158TL1TR002318R01 GM121354P30 ES007033P01 DA032507P30ES007033TL1 TR002318Shum SHailey DWHimmelfarb JYeung CKKelly EJHuang WChapron AChang SYImaoka TIsoherranen NfalseBridging 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 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.2021-01-01T00:00:00Z2021 Nov2024-02-15T09:58:45.339Z2022-02-11T12:45:39.261ZS-EPMC85607543472535210.1038/s41598-021-00338-y