# Sepsis modelling: current approaches and organ-on-chip perspectives

## TL;DR

This review explores current methods and future directions in sepsis modeling, emphasizing the potential of organ-on-chip technology to improve translational research.

## Contribution

The paper provides a structured comparison of sepsis models and highlights organ-on-chip systems as a promising approach for capturing human physiology.

## Key findings

- Current sepsis models have limitations in complexity and reproducibility, hindering clinical translation.
- Organ-on-chip systems offer a more accurate representation of human physiology and sepsis features.
- Integrating advanced models could enhance therapeutic discovery and model selection for specific research questions.

## Abstract

Sepsis is a complex life-threatening condition involving immune dysregulation, endothelial dysfunction, and multi-organ failure. To investigate molecular and systemic processes driving disease progression, in vitro, in vivo, and ex vivo experimental methods have been developed. While these systems have advanced understanding of immune activation, cytokine signalling, and organ injury, differences in complexity, reproducibility, and alignment with human pathophysiology have limited the translation of many promising preclinical findings into clinical success. This review examines current literature on sepsis systems, evaluating them in terms of biological complexity, reproducibility, ethical constraints, and clinical applicability. In parallel, it discusses the potential use of microfluidic technology, particularly organ-on-chip, in replicating human physiology and capturing key features of sepsis. By comparing conventional and advanced systems, this review outlines challenges in sepsis research and identifies key directions for a more integrated approach to sepsis modelling, aiming to improve translational outcomes and therapeutic discovery. We aim to provide a structured basis for comparing models when selecting approaches for a given question or candidate therapy.