(688a) Predicting Therapeutic Efficacy on Renal Fibrosis in Diabetes: A Mathematical Model

Diabetes is a significant burden on global public health. In the 2015, over 400 million people were diagnosed with diabetes worldwide—a number that is expected to rise to over 600 million in 2040. One-third of these diabetic patients are expected to develop diabetic kidney disease, the leading cause of kidney failure. One of the main reasons for our inability to mitigate the rapidly rising burden of diabetic nephropathy is the lack of non-invasive, accurate markers to track therapeutic efficacy on renal fibrosis. Currently, the gold standard for determining therapeutic efficacy is a biopsy, which is an invasive surgery that cannot be done repeatedly. The other alternative uses biomarkers in the urine to track therapeutic efficacy; however, the currently available biomarkers are not capable of accurately determining therapeutic efficacy. Thus, our objective in this research project is to develop a modeling approach to track therapeutic efficacy that is both non-invasive and accurate.

First, we used experimental studies to create a network structure that represents the process by which hyperglycemia in diabetes stimulates inflammation in the kidney that then results in renal fibrosis. The interactions between key resident and immune cells with the inflammatory and profibrotic molecules is incorporated to be able to accurately model the dynamics that results in fibrosis. The interactions are then formulated as a system of ordinary differential equations (ODEs) where production and degradation kinetics of molecular and cellular species is assumed to follow the mass conservation. Biomolecule-mediated activation and inhibition of processes is modeled using the commonly used approach of Michaelis-Menten kinetics. The resulting system of ODEs are then solved in MATLAB to obtain the population and concentration dynamics of the species considered. To validate our results, we gathered experimental data of renal fibrosis in the type I diabetic mice from the literature. We are currently in the process of modifying and restructuring our model to accurately reflect experimental observations.

Once we have validated our model, we plan to test the ability of our model to predict therapeutic efficacy of different drugs on renal fibrosis. Subsequently, our next step is to adapt the model for type I mice diabetes and then eventually for human diabetes. With increasing validation of our model, we are confident that our model can be used in the future in a clinical setting to non-invasively and accurately determine therapeutic efficacy on renal fibrosis.