Physiologically‐Based Pharmacokinetic Modelling of Creatinine‐Drug Interactions in the Chronic Kidney Disease Population. (23rd November 2020) - Takita, Hiroyuki; Scotcher, Daniel; Chinnadurai, Rajkumar; Kalra, Philip A.; Galetin, Aleksandra
Abstract : Elevated serum creatinine (SCr ) caused by the inhibition of renal transporter(s) may be misinterpreted as kidney injury. The interpretation is more complicated in patients with chronic kidney disease (CKD) due to altered disposition of creatinine and renal transporter inhibitors. A clinical study was conducted in 17 patients with CKD (estimated glomerular filtration rate 15–59 mL/min/1.73 m 2 ); changes in SCr were monitored during trimethoprim treatment (100–200 mg/day), administered to prevent recurrent urinary infection, relative to the baseline level. Additional SCr ‐interaction data with trimethoprim, cimetidine, and famotidine in patients with CKD were collated from the literature. Our published physiologically‐based creatinine model was extended to predict the effect of the CKD on SCr and creatinine‐drug interaction. The creatinine‐CKD model incorporated age/sex‐related differences in creatinine synthesis, CKD‐related glomerular filtration deterioration; change in transporter activity either proportional or disproportional to glomerular filtration rate (GFR) decline were explored. Optimized models successfully recovered baseline SCr from 64 patients with CKD (geometric mean fold‐error of 1.1). Combined with pharmacokinetic models of inhibitors, the creatinine model was used to simulate transporter‐mediated creatinine‐drug interactions. Use of inhibitor unbound plasma concentrations resulted in 66% of simulated SCr interaction data within the prediction limits, with cimetidine interaction significantly underestimated. Assuming that transporter activity deteriorates disproportional to GFR decline resulted in higher predicted sensitivity to transporter inhibition in patients with CKD relative to healthy patients, consistent with sparse clinical data. For the first time, this novel modelling approach enables quantitative prediction of SCr in CKD and delineation of the effect of disease and renal transporter inhibition in this patient population.