Speaker
Amber Smith, PhD
Abstract: Advances in high-throughput technologies have dramatically increased our ability to characterize disease, yet understanding the mechanisms underlying disease progression well enough to predict clinical outcomes remains a major challenge. This seminar will describe how mechanistic mathematical models integrated with multimodal data can infer hidden biological processes, explain why similar biomarker profiles can arise from fundamentally different disease states, and improve predictions of disease outcomes. Using influenza as an example, I will illustrate how this framework reveals mechanisms that are inaccessible to direct measurement and provides a foundation for predictive, mechanism-based precision medicine.
Bio: Amber M. Smith, Ph.D. is a Professor at the University of Tennessee Health Science Center College of Medicine and a member of the Institute for the Study of Host-Pathogen Systems. She leads an interdisciplinary research program that integrates mechanistic mathematical modeling, experimental biology, and clinical data to investigate the immune mechanisms underlying respiratory infections and polymicrobial disease. Her research focuses on influenza and bacterial pneumonia and on developing immune digital twin frameworks to predict disease progression and therapeutic responses. Her work is supported by NIAID, MISM, and ARPA-H and aims to uncover hidden biological mechanisms and advance predictive, mechanism-based approaches to precision medicine.
Event Series
MISM Seminar Series