Strategic Initiative Fund (SIF)

Personalized Immune Models to Predict Infectious Disease Outcomes

This "Look to Michigan to Boldly Tackle Infectious Disease" project aims to establish a personalized approach to infectious-disease prediction, treatment, and prevention. Rather than assuming a pathogen affects everyone similarly, the initiative integrates single-cell transcriptomics, state-of-the-art immune profiling, and AI/ML models to predict how individuals respond to viral pathogens, examining how differences in genetics, health history, prior exposures, and immune-cell composition shape each person's response.

The platform will characterize individual immune phenotypes and link them to real-world disease outcomes by leveraging an existing database of COVID-19 patient outcomes and samples to create a scalable, forward disease-prediction model for clinical translation. Its central goal is to create a high-resolution model that predicts patient-specific disease outcomes from immune responses, ultimately helping clinicians identify who is most likely to become severely ill and which interventions may work best.

By connecting molecular measurements, computational predictions, and patient outcomes, the project seeks to make U-M a leader in precision infectious-disease medicine while improving preparedness, reducing severe illness, and supporting more individualized and equitable care.