Multiscale Mathematical Model of Drug-Induced Proximal Tubule Injury: Linking Urinary Biomarkers to Epithelial Cell Injury and Renal Dysfunction. (6th November 2017)

• Record Type: Journal Article
• Authors: Gebremichael, Yeshitila; Lu, James; Shankaran, Harish; Helmlinger, Gabriel; Mettetal, Jerome; Hallow, K Melissa
• Is Part Of: Toxicological sciences. Volume 162:Number 1(2018)
• Page Start: 200
• Page End: 211
• Publication Date: 2017-11-06
• Subjects: quantitative systems pharmacology -- acute kidney injury -- nephrotoxicity -- biomarker -- proximal tubular injury -- multiscale model; Toxicology -- Periodicals; Toxicology -- Periodicals; Toxicology; Periodicals; 615.9
• DOI: 10.1093/toxsci/kfx239
• Languages: English
• ISSNs: 1096-6080

Abstract

Abstract: Drug-induced nephrotoxicity is a major cause of acute kidney injury, and thus detecting the potential for nephrotoxicity early in the drug development process is critical. Various urinary biomarkers exhibit different patterns following drug-induced injury, which may provide greater information than traditional biomarkers like serum creatinine. In this study, we developed a multiscale quantitative systems pharmacology model relating drug exposure to proximal tubule (PT) epithelial cell injury and subsequently to expression of multiple urinary biomarkers and organ-level functional changes. We utilized urinary kidney injury molecule-1 (Kim-1), alpha glutathione S-transferase, albumin (αGST), glucose, and urine volume time profiles as well as serum creatinine and histopathology data obtained from rats treated with the nephrotoxicant cisplatin to develop the model. Although the model was developed using single-dose response to cisplatin, the model predicted the serum creatinine response to multidose cisplatin regimens. Further, using only the urinary Kim-1 response to gentamicin (a nephrotoxicant with a distinctly different injury time course than cisplatin), the model detected and predicted mild to moderate PT injury, as confirmed with histopathology, even when serum creatinine was unchanged. Thus, the model is generalizable, and can be used to deconvolute the underlying degree and time course of drug-induced PT injury and renal dysfunction from a small number of urinary biomarkers, and may provide a tool to determine optimal dosing regimens that minimize renal injury.