C. Anthony Hunt, PhD

What I do

I am a theoretical systems pharmacologist who develops advanced simulation methods to improve multiscale mechanistic explanations of complex phenomena in the presence and absence of therapeutic interventions.

My research expertise

Computational biology/pharmacology, Bioengineering, Multiscale modeling and simulation, Personalized medicine, Biomedical informatics


BSc, Applied Biology, Georgia Institute of Technology
BSc, Chemistry, Georgia Institute of Technology
PhD, Pharmaceutical Sciences, University of Florida


My research is motivated by this question. What are the causal mechanisms that link induced changes in molecular level events to emergent changes in phenotype at the organism level? We need new ways to explore and challenge plausible answers. So doing will facilitate moving away from empirical approaches to biomedical research and reliance on correlational methods toward new approaches based on improving mechanistic knowledge and insight.
We need ways to build and challenge experimentally (falsify) many alternative, nested, networked mechanistic hypotheses. Doing so using established, bottom-up, computational mathematical models is problematic at best. New methods and new approaches are needed. My search started in earnest circa 1997. We have now developed and demonstrated the scientific power of a novel, fundamentally new class biomedical simulation models along with methods to challenge and iteratively improve plausible, explanatory mechanisms. We adapted concepts and advanced methods from several domains. I call the process the synthetic method of modeling and simulation (SM). I say synthetic because standalone biomimetic components are plugged together in specific ways to form hierarchical, multiscale biomimetic mechanisms in software. I refer to the models as analogues because even though they exist only in silico, their phenotypes can be made to increasingly overlap more of the referent, biological phenotype. They are designed to evolve to become embodiments of most of what we know (or think we know) about aspects of specific organisms and their components.