Quantitative Systems Pharmacology Modeling of Cisplatin-Induced Kidney Injury Following Intravenous and Lymph Node-Targeted Drug Delivery

• Ana Obradovic, Biomedical Engineering, University of Delaware

• Ryan Zurakowski, Biomedical Engineering, University of Delaware

Cisplatin is a widely used chemotherapeutic agent for treating many solid tumors and lymphomas, but its clinical use is often limited by dose-dependent kidney toxicity. A novel lymph node-targeted delivery platform using CSTL carriers has the potential to improve drug localization while reducing systemic exposure, although its effects on kidney injury have not been quantitatively characterized. In this study, we developed a mechanistic quantitative systems pharmacology (QSP) model that integrates cisplatin pharmacokinetics with acute and chronic kidney injury pathways to compare conventional intravenous administration with CSTL-mediated delivery. The pharmacokinetic model was coupled to mechanistic representations of acute proximal tubule brush border loss and chronic periglomerular fibrosis using ordinary differential equations informed by published experimental data. Model simulations predict that CSTL delivery substantially reduces free plasma cisplatin exposure while maintaining high lymph node drug concentrations. Consequently, the model predicts markedly lower acute kidney injury and fibrosis following CSTL administration compared with conventional intravenous dosing. This framework provides a mechanistic approach for linking drug exposure to tissue-level renal injury and enables quantitative comparison of emerging drug delivery strategies. More broadly, this work demonstrates how QSP modeling can support the design and evaluation of targeted therapeutics by predicting both efficacy-related drug distribution and long-term safety outcomes in parallel with ongoing in vivo studies.