Evaluating Immune Checkpoint Inhibitors for Liver Toxicity in a Biomimetic Liver Microphysiology Model

Conference: SOT
Software: BIOLOGXsym
Division: DILIsym Services

Background & Purpose

  • The prominence of biologic drugs has rapidly gained traction and has delivered life-changing therapies for cancer patients
  • Some biologics are reported to cause hepatoxicity, i.e., biologics-induced liver injury (BILI)
  • Comparison of drug toxicity between biologics and small molecules is an active field of research
  • Two immune checkpoint inhibitor (ICI) biologics, ipilimumab (ipi) and nivolumab (nivo), have demonstrated synergistic effects in cancer immunotherapy at the cost of increased toxicity
  • Although immune-mediated hepatic injury by activated T cells is suspected, mechanisms underlying liver-specific toxicity by ICIs remain unknown
  • In this study, effects of ipi, nivo, and cabozantinib (cabo, a tyrosine kinase inhibitor that has interplay in immunoregulation) mono- and combination treatments on the liver microenvironment were evalated in the Liver Acinus MicroPhysiology System (LAMPS) biomimetic model


  • Compounds were administered at doses based on clinical Cmax ranges for 10 days under continuous perfusion in the 4-cell type LAMPS
  • Toxicity signals from the LAMPS were measured using a combination of flourescence microscopy and immunohistochemistry
  • Statistical comparisons of assay outputs were completed using regression-based and non-parametric tests comparing treated groups to untreated groups
  • Significant findings are reported as mean percentages relative to the untreated group


  • These findings demonstrate the capacity for ipi and nivo to induce intrinsic hepatocyte stress signals in a well-established biomimetic model of the liver, that may contribute to liver-specific adaptive immune responses
  • Mechanisms of cabo-mediated hepatoxicity warrants further investigation
  • The Microphysiology Systems Database will manage, archive, and disseminate the meta, raw, and analytical data including experimental reproducibility analysis and BILI predictive outcomes in our ongoing studies
  • In addition, the results from this study will be used in the novel quantitative systems toxicology platform, BIOLOGXsym™, to predict BILI in populations by combining clinically relevant drug exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic representation of liver responses
  • This integrated approach may set the stage for more efficient development of novel biologics for cancer immunitherapies

By Francisco Huizar, Lawrence A. Vernetti, Lara Clemens, James J. Beaudoin, Scott Q. Siler, Lisl K.M. Shoda, Mark Miedel, Michael Castiglione, Brett A. Howell, Kyunghee Yang, D. Lansing Taylor

2024 SOT Annual Meeting and ToxExpo, March 10–14, 2024, Salt Lake City, Utah