Please use this identifier to cite or link to this item: https://doi.org/10.1039/c3tx50042j
Title: An <i>in vitro</i> method for the prediction of renal proximal tubular toxicity in humans
Authors: Li, Yao
Oo, Zay Yar
Chang, Shu Yung 
Huang, Peng
Eng, Kim Guan
Zeng, Jia Liu
Kaestli, Alicia J
Gopalan, Began
Kandasamy, Karthikeyan 
Tasnim, Farah
Zink, Daniele
Keywords: Science & Technology
Life Sciences & Biomedicine
Toxicology
EPITHELIAL-CELL LINE
ACUTE KIDNEY INJURY
URINARY BIOMARKER
NEPHROTOXICITY
EXPRESSION
FAILURE
CULTURE
MODEL
DRUGS
ASSAY
Issue Date: 2013
Publisher: ROYAL SOC CHEMISTRY
Citation: Li, Yao, Oo, Zay Yar, Chang, Shu Yung, Huang, Peng, Eng, Kim Guan, Zeng, Jia Liu, Kaestli, Alicia J, Gopalan, Began, Kandasamy, Karthikeyan, Tasnim, Farah, Zink, Daniele (2013). An in vitro method for the prediction of renal proximal tubular toxicity in humans. TOXICOLOGY RESEARCH 2 (5) : 352-365. ScholarBank@NUS Repository. https://doi.org/10.1039/c3tx50042j
Abstract: The kidney is one of the major target organs for drug-induced toxicity. The renal proximal tubule is frequently affected due to its roles in drug transport and in concentrating the glomerular filtrate. Drug-induced kidney injury is associated with increased morbidity and mortality of patients. During drug development, nephrotoxicity is typically detected only late, which leads to high costs for the pharmaceutical industry. A central problem is the lack of pre-clinical models with high predictability. Regulatory accepted or validated in vitro models for the prediction of nephrotoxicity are not available. We developed a novel in vitro model for the prediction of renal proximal tubular toxicity in humans. It employs human primary renal proximal tubular cells and the expression levels of interleukin (IL)-6 and IL-8 were used as the endpoint. The model was evaluated with 41 well-characterized drugs and chemicals. The median values of the major performance metrics (balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value and area under the curve of the receiver operating characteristic curve) ranged between 0.76 and 0.85. This revealed that the predictability of the model is high and it would be expected that in ∼76%-85% of the cases where compounds were predicted as positives or negatives the predictions would be correct. Altogether, the data suggest that the model would allow the prediction of drug-induced proximal tubular toxicity at early pre-clinical stages during drug development. Future work will aim at further validating this model and adapting it to recently developed renal proximal tubular-like cells derived from human pluripotent stem cells. © The Royal Society of Chemistry 2013.
Source Title: TOXICOLOGY RESEARCH
URI: https://scholarbank.nus.edu.sg/handle/10635/245797
ISSN: 2045-452X
2045-4538
DOI: 10.1039/c3tx50042j
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