ABSTRACT
This chapter discusses how modeling and systems biology might contribute to the understanding of personalized health, disease, and treatment. Systems biology enters the field with two components. Experimental systems biology offers new and very powerful means of identifying physiological mechanisms and their parameters. Computational systems biology will use averaged disease models, personalize them, based on individualized data, yield personal risk profiles, and suggest possible prevention strategies. The computational aspect of personalized medicine and predictive health requires the personalization of models. Indeed, the potential of systems biology in drug discovery has been recognized for some time. Systems biology is also used increasingly for receptor binding and dosing studies with newly created molecules. Many aspects of systems biology look promising for reducing the cost of drug discovery through effective early screening and hit elimination. Computational systems biology support pharmacokinetic and pharmacodynamic assessments of the levels of therapeutic agents in different tissues and organs of the body.
