New and Emerging Research Models for Sepsis

TL;DR

This review discusses new and improved models for studying sepsis, aiming to better reflect human disease and improve treatment development.

Contribution

The paper introduces and evaluates emerging models like human-based systems, AI models, and the FAMOUS framework for sepsis research.

Findings

Animal models have contributed to understanding sepsis but lack translational success.

New models such as AI and human-based systems offer better insights into patient subgroups and outcomes.

The FAMOUS framework ensures therapies are tested against their intended mechanisms.

Abstract

Human sepsis is a complex disease that manifests with a diverse range of phenotypes and inherent variability among individuals, making it hard to develop a comprehensive animal model. Despite this difficulty, numerous animal models have been developed that capture many key aspects of human sepsis. Though the animal models have contributed to the fundamental advances in understanding the pathogenesis of septic patients, the translational value of these models has been constantly questioned because many clinical trials of targeted therapies based on the advances in animal models have failed, highlighting the urgent need for developing new research models or refining previous animal models for sepsis research. In this review, we will summarize recent advances in new and emerging research models for sepsis, including human-based in vitro systems, highly tailored animal models, AI and digital models analyzing vast datasets to define patient subgroups and predict outcomes, and the FAMOUS framework ensuring that therapies are tested against the specific mechanism they are designed to target. We will discuss the strengths and limitations of these models, reflecting the clinical course of sepsis, and discuss the future directions in this subject area.