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Organ-on-a-chip (OOC) and organoid technologies are at the forefront of developing sophisticated in vitro systems that replicate complex host–microbiome interactions, including those associated with vaginal health and lung infection. We explore how these technologies provide insights into host–microbiome and host–pathogen interactions and the associated immune responses. Integrating omics data and high-resolution imaging in analyzing these models enhances our understanding of host–microbiome interactions' temporal and spatial aspects, paving the way for new diagnostic and treatment strategies. This review underscores the potential of OOC and organoid technologies in elucidating the complexities of vaginal health and lung disease, which have received less attention than other organ systems in recent organoid and OCC studies. Yet, each system presents notable characteristics, rendering them ideal candidates for these designs. Additionally, this review describes the key factors associated with each organ system and how to choose the technology setup to replicate human physiology. 

Abstract Immune response is critical in septic wound healing. The aberrant and imbalanced signaling dynamics primarily cause a dysfunctional innate immune response, exacerbating pathogen invasion of injured tissue and further stalling the healing process. To design biological controllers that regulate the critical divergence of the immune response during septicemia, we need to understand the intricate differences in immune cell dynamics and coordinated molecular signals of healthy and sepsis injury. Here, we deployed an ordinary differential equation (ODE)-based model to capture the hyper and hypo-inflammatory phases of sepsis wound healing. Our results indicate that impaired macrophage polarization leads to a high abundance of monocytes, M1, and M2 macrophage phenotypes, resulting in immune paralysis. Using a model-based analysis framework, we designed a biological controller which successfully regulates macrophage dysregulation observed in septic wounds. Our model describes a systems biology approach to predict and explore critical parameters as potential therapeutic targets capable of transitioning septic wound inflammation toward a healthy, wound-healing state.