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I study the dynamics of human pathophysiologic processes by developing mechanistic mathematical descriptions of complex human disease phenotypes and how they change over time. The research combines medical insight, dynamical systems theory, and experiments utilizing clinical specimens, microfluidics, video processing, flow cytometry, simulation, and large-scale analysis of medical databases in pursuit of two goals: (1) advancing fundamental understanding of human pathophysiologic process and their dynamics, and (2) improving patient diagnosis, monitoring, and treatment.

Pathophysiology is described at the molecular, cellular, tissue and organismal levels and may show clinically significant variation over time scales ranging from less than a second to more than a decade. Using clinical laboratory data and experiments with clinical specimens, we can develop detailed descriptions of pathophysiologic states in terms of clinically relevant and measurable quantities. We can then propose mathematical models describing the interrelationships between these state variables and how those relationships change when perturbed by disease. Models must be consistent with mechanisms established by both existing basic research and clinical experience, and once validated will enable the estimation of dynamic parameters. Personalized estimates of parameters often quantify unmeasurable pathophysiologic processes, revealing new insight into pathophysiology and providing opportunities for novel approaches to diagnosis and patient monitoring. Recent work has focused on population dynamics of cell characteristics in anemia and inflammation due to ischemia, infection, autoimmune disease, and more.

Selected Publications

View a complete list of Dr. Higgins' publications on the Center for Systems Biology website.

Di Caprio G, Schonbrun E, Gonçalves BP, Valdez JM, Wood DK, Higgins JM. Highthroughput assessment of hemoglobin polymer in single red blood cells from sickle cell patients under controlled oxygen tension. Proceedings of the National Academy of Sciences of the United States of America. 2019 Dec 10;116(50):25236-25242.

Chaudhury A, Miller GD, Eichner D, Higgins JM. Single-cell modeling of routine clinical blood tests reveals transient dynamics of human response to blood loss. Elife. 2019 Dec 17;8.

Chaudhury A, Noiret L, Higgins JM. White blood cell population dynam-ics for risk stratification of acute coronary syndrome. Proceedings of the National Academy of Sciences USA. 2017; 114(46):12344-12349.

Malka R, Nathan DM, Higgins JM. Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring. Science Translational Medicine. 2016; 8(359):359ra130.