Context-specific assessment of disease model relevance for post-infection research

Research on post-infection conditions relies on disease models in a setting characterised by heterogeneity and incomplete understanding of disease processes. Different models are often used to address different questions, yet their relevance to specific aspects of the human condition is not always systematically assessed.

We provide a context-specific, quantitative assessment of disease model relevance to human post-infection disease, examining how well individual models capture the biological aspects relevant to a given research question. By analysing models at the molecular and pathway level in relation to human disease within a structured and reproducible framework, we clarify what each model is informative for, where limitations lie, and how different models relate to each other.

This supports consortia in:

• selecting models that are appropriate for specific scientific questions,

• understanding why different models yield different results,

• using complementary models where no single system is sufficient,

• interpreting findings within the actual scope of each model, avoiding over-generalisation.

As an additional benefit, these analyses provide a transparent, evidence-based basis for justifying model selection and can highlight specific biological gaps where models could be refined or complemented to better address the research objectives.

Our contribution helps ensure that conclusions in DISEASE-03 projects are grounded in a clear and quantitative understanding of how disease models relate to the human condition they are intended to represent.