"Every patient, disease, tissue, and cell is a complex system. Understand what makes the system tick and you can find a way to treat it. The cutting-edge research and scientific talent at Genentech make it an ideal environment to do just that."
My passion is applying engineering approaches to understand the fascinating complexity of biological systems in order to develop medicines that improve the lives of people suffering from devastating diseases.
I have a background in chemical engineering, with a BSE in from the University of Michigan at Ann Arbor and a PhD from the University of Wisconsin at Madison, after which I did a postdoctoral fellowship at the Steele Lab for Tumor Biology at the Massachusetts General Hospital in Boston. Starting in 2001, I spent 9 years at the systems modeling biotechnology company, Entelos Inc, followed by a few years as an Associate Director at the rheumatology diagnostics company, Crescendo Biosciences.
I joined Genentech in 2012 to implement and lead the Translational and Systems Pharmacology group. Our group focuses on mathematical modeling and computational analysis of complex biological systems to support drug development from basic research through clinical development. We work closely with our collaborators in different departments to support target evaluation, compound design, pharmacokinetic understanding, biomarker and diagnostics strategy, clinical trial planning, and drug safety across different therapeutic areas and molecular formats.
At Genentech, I also get to pursue another passion of mine, K-12 education, by participating in the “Gene Academy” program, which works with local schools to provide mentorship and tutoring.
My group focuses on translational and systems pharmacology, the latter of which has been described as “the quantitative analysis of the dynamic interactions between drug(s) and a biological system that aims to understand the behavior of the system as a whole…” (van der Graaf & Benson, J Pharm Sci 2011). We do this by combining expertise in engineering systems dynamics, pharmaceutical sciences, and biomedical research to develop mechanistic and biology-driven mathematical models of drugs and diseases. These models are essentially mathematical formalizations of the existing knowledge and data in the field. Using the models, we generate entire populations of “virtual” patients in which we conduct in silico research to explore promising drug targets and compounds, evaluate biomarkers, test clinical dosing regimens, and predict clinical efficacy, safety and biomarker responses. Some of our ongoing efforts are in the areas of cancer cell signaling, asthma, cancer immunotherapy, Alzheimer’s disease, and ocular disease. We are also continually developing and sharing novel technical approaches to advance the field of systems pharmacology.