Quantitative adverse outcome pathway modeling of cisplatin-induced nephrotoxicity: developing in vitro and in vivo models for predictive extrapolation.

Nephrotoxicity is a major concern in the safety assessment of chemicals and drugs. Computational modeling, particularly the use of quantitative adverse outcome pathways (qAOPs), offers a promising strategy to improve the translation from in vitro to in vivo, thereby facilitating reliable predictions of in vivo adverse outcomes and potentially reducing the need for animal testing. Platinum-based drugs are widely used in chemotherapy, yet their clinical application is frequently constrained by nephrotoxic effects. Here, we focus on the development of ordinary differential equation (ODE)-based qAOPs for platinum-induced nephrotoxicity by defining both an in vitro and an in vivo data-driven model. The in vitro model incorporates newly generated, time-course gene expression and propidium iodide (PI) staining data from RPTEC/TERT1 cells exposed to cisplatin. The in vivo model employs published rat data, including dose-response platinum kinetics as well as single-dose time-course platinum kinetics, gene expression, and histopathology data. Our quantitative approach shows that key processes in the AOP related to immune system activity are nonlinear. Specifically, clearance of necrotic kidney cells by immune system activity counters damage accumulation on a timescale of days, yet low-level inflammation still cumulatively affects kidney failure in the long run. Moreover, we perform quantitative in vitro to in vivo extrapolation (QIVIVE) to link the 2 models. With this approach, in vivo adverse outcome predictions can be made in the future not only for platinum-based compounds but also for the safety assessment of other chemicals and drugs, reducing the need for animal testing.