{"doi":"10.1101/2020.12.04.412239","title":"Bridging the gap between <i>in silico</i> and <i>in vivo:</i> modeling opioid disposition in a kidney proximal tubule microphysiological system","abstract":"Abstract Background 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 kidney clearance (CL r ) and systemic disposition of opioids in CKD patients can facilitate the optimization of therapeutic regimens. Methods We conducted prediction of kidney 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. Results 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 in a time-dependent manner; transporter inhibitors decreased translocation by 74.3% and 63.6%, respectively. 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. The model successfully predicted CL r within 1.5-fold, and the plasma concentration-time profiles of morphine and M6G in both healthy subjects and CKD patients, with absolute average fold error values &lt;1.5. Conclusions A microphysiological system together with mathematical modeling successfully predicted kidney clearance and systemic disposition of opioids in CKD patients and healthy subjects.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":131925,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9487,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":399926,"name":"Weize Huang","orcid":"0000-0001-5903-721X","position":1,"is_corresponding":false},{"id":381921,"name":"Sara Shum","orcid":null,"position":2,"is_corresponding":false},{"id":117101,"name":"Dale W. Hailey","orcid":null,"position":3,"is_corresponding":false},{"id":587394,"name":"Shih‐Yu Chang","orcid":null,"position":4,"is_corresponding":false},{"id":587395,"name":"Alenka Chapron","orcid":null,"position":5,"is_corresponding":false},{"id":285189,"name":"Catherine K. Yeung","orcid":"0000-0002-6556-6641","position":6,"is_corresponding":false},{"id":54241,"name":"Jonathan Himmelfarb","orcid":"0000-0002-3319-1224","position":7,"is_corresponding":false},{"id":126655,"name":"Nina Isoherranen","orcid":"0000-0002-9548-3126","position":8,"is_corresponding":false},{"id":422499,"name":"Edward J. Kelly","orcid":"0000-0002-6534-9313","position":9,"is_corresponding":false},{"id":587393,"name":"Tomoki Imaoka","orcid":null,"position":0,"is_corresponding":true}],"reference_count":47,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:16:07.542484Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}