Objective: Kidney, as a major excretory organ, is exposed to high levels of drugs and their metabolites. Therefore, kidney toxicity is an important part of drug safety assessment in clinical trials. RENAsymTM is a quantitative systems toxicology (QST) model of drug induced acute kidney injury (AKI) currently under development. In its current form, the model includes representations of proximal tubule cell (PTC) lifecycle, bioenergetics, cellular injury and death pathways. Our objective is to develop a mechanistic mathematical model of mitochondrial dysfunction in proximal tubule cells to predict drug induced AKI.
Methods: We adapted the mitochondrial dysfunction model existing in DILIsym®, a QST model of drug induced liver injury, by modifying the equations to accommodate the physiological differences between kidney and liver. Changes made in order to translate the model to the kidney include (but are not limited to) eliminating de novo lipogenesis and glycogen storage, refining PTC bioenergetics, and changing mitochondrial substrate utilization. For example, glucose oxidation was removed during homeostasis as little glucose oxidation was observed in rat proximal convoluted tubules. We then simulated gentamicin as an exemplar compound to qualitatively validate the model. Gentamicin in vitro mitochondrial toxicity was measured in HepG2 cells and converted to RENAsymTM parameters using MITOsym®. Parameters for oxidative stress and kidney exposure were obtained from literature.
Results: Simulations predicted significant toxicity in rats (100 mg/kg QD dosing) and humans (3mg/kg QD dosing) within 24h. Oxidative stress was predicted to be the major mechanism of toxicity in both species. Mild mitochondrial signals were predicted in rats and none in humans.
Conclusions: A mitochondrial dysfunction model originally constructed for the liver has been adapted to the kidney and reasonably predicts gentamicin-induced AKI. Simulations show that gentamicin induced oxidative stress causes more toxicity than mitochondrial dysfunction.
By Shailendra B. Tallapaka, YeshitilaGebremichael, Scott Q. Siler, Brett A. Howell, Jeffrey L. Woodhead
Tenth Annual American Conference on Pharmacometrics (ACoP) Annual Meeting: October 19-22, 2019, Orlando, FL