Drug-induced kidney injury accounts for 20% of community-and hospitalacquired cases of acute kidney injury (AKI). The incidence is higher among older individuals, who often have co-existing morbidities and are exposed to more diagnostic procedures and therapies. While demographic and clinical components have been identified as risk factors, the proposed cellular mechanisms of drug-induced kidney injury are numerous and complicated. There are also limitations recognized in the use of traditional biomarkers, such as serum creatinine and blood urea nitrogen, to provide high sensitivity, specificity, and timeliness to identification of drug-induced kidney injury. Therefore, novel biomarkers are currently being investigated, identified, developed, and validated for their performance over the traditional biomarkers. This review will provide an overview of drug-induced kidney injury and will discuss what is known regarding "omic" (proteomic, genomic, transcriptomic, and metabolomic) biomarker strategies for drugs known to induce nephrotoxicity.

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The aim of this study was to investigate the impact of suboptimal 25‐hydroxyvitamin D (25‐VitD) and cholecalciferol (VitD3) supplementation on the pharmacokinetics of oral midazolam (MDZ) in control subjects and subjects with chronic kidney disease (CKD). Subjects with CKD (n = 14) and controls (n = 5) with suboptimal 25‐VitD levels (<30 ng/mL) were enrolled in a 2‐phase study. In phase 1 (suboptimal), subjects were administered a single oral dose of VitD3 (5000 IU) and MDZ (2 mg). In phase 2 (replete) subjects who achieved 25‐VitD repletion after receiving up to 16 weeks of daily cholecalciferol were given the identical single oral doses of VitD3 and MDZ as in phase 1. Concentrations of MDZ and metabolites, 1′‐hydroxymidazolam (1′‐OHMDZ), and 1′‐OHMDZ glucuronide (1′‐OHMDZ‐G) were measured by liquid chromatography–tandem mass spectrometry and pharmacokinetic analysis was performed. Under suboptimal 25‐VitD, reductions in MDZ clearance and renal clearance of 47% and 87%, respectively, and a 72% reduction in renal clearance of 1′‐OHMDZ‐G were observed in CKD vs controls. In phase 1 versus phase 2, MDZ clearance increased in all control subjects, with a median (interquartile range) increase of 10.5 (0.62‐16.7) L/h. No changes in MDZ pharmacokinetics were observed in subjects with CKD between phases 1 and 2. The effects of 25‐VitD repletion on MDZ disposition was largely observed in subjects without kidney disease. Impaired MDZ metabolism and/or excretion alterations due to CKD in a suboptimal 25‐VitD state may not be reversed by cholecalciferol therapy. Suboptimal 25‐VitD may augment the reductions in MDZ and 1′‐OHMDZ‐G clearance values observed in patients with CKD.

A physiologically based pharmacokinetic (PBPK) model of vitamin D 3 and metabolites [25(OH)D 3 , 1,25(OH) 2 D 3 , and 24,25(OH) 2 D 3 ] is presented. In this study, patients with 25(OH)D 3 plasma concentrations below 30 ng/ml were studied after a single dose of 5,000 I.U. (125 µg) cholecalciferol, provided with 5,000 I.U. daily cholecalciferol supplementation until vitamin D replete (25(OH)D 3 plasma concentrations above 30 ng/ml), and had serial plasma samples were collected at each phase for 14 days. Total concentrations of vitamin D 3 and metabolites were measured by ultra-high performance liquid chromatography tandem mass spectrometry. A ninecompartment PBPK model was built using MATLAB to represent the triphasic study nature (insufficient, replenishing, sufficient). Stimulatory and inhibitory effect of 1,25(OH) 2 D 3 were incorporated by fold-changes in the primary metabolic enzymes CYP27B1 and CYP24A1, respectively. Incorporation of dynamic adipose partition coefficients for vitamin D 3 and 25(OH)D 3 and variable enzymatic reactions aided in model fitting.Measures of model predictions agreed well with data from metabolites, with 97%, 88%, and 98% of the data for 25(OH)D 3 , 24,25(OH) 2 D 3 , and 1,25(OH) 2 D 3 , respectively, within 2-fold of unity (fold error values between 0.5 and 2.0). Bootstrapping was performed and optimized parameters were reported with 95% confidence intervals.This PBPK model could be a useful tool for understanding the connections between vitamin D and its metabolites under a variety of clinical situations.