Cellular behavior emerges from a complex network of chemical interactions, the details of which remain largely unknown. Developing effective therapies requires a quantitative understanding of these fundamental processes and how they can be safely manipulated to thwart disease. Our lab focuses on constructing mathematical models to assist in diagnosis and treatment of neurodegenerative disease and cancer.
Many complex diseases can only be successfully treated with multi-drug therapeutic strategies. Identifying the proper drugs, doses and scheduling for an effective combination therapy is hindered by the sheer number of permissible combinations. Working with other researchers at the University of Pittsburgh Drug Discovery Institute, our lab is developing a combined experimental and computational methodology for streamlining the discovery of combination therapeutics. We are developing novel chemogenomics approaches to uncover pathways that synergistically modulate cell behavior in Alzheimer's disease, Huntington's disease and traumatic brain injury.
An important part of drug discovery is determining safe dose regimens for a heterogeneous patient population. Increasingly, this means personalizing medications and doses to provide optimal effects in individual patients. Working with industry collaborators, the lab is developing mathematical models of the immune response to cancer treatment. Our goal is to quantitatively predict how individual patients will react to a variety of dosing regimens, in order to optimize the efficacy and minimize the side effects of cancer therapy.