title: Revolutionizing medicine in the 21st century through systems approaches.
abstract: Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term "personalized medicine", however, fails to reflect the enormous dimensionality of this new medicine that will be predictive, preventive, personalized, and participatory-a vision of medicine we have termed P4 medicine. This reflects a paradigm change in how medicine will be practiced that is revolutionary rather than evolutionary. P4 medicine arises from the confluence of a systems approach to medicine and from the digitalization of medicine that creates the large data sets necessary to deal with the complexities of disease. We predict that systems approaches will empower the transition from conventional reactive medical practice to a more proactive P4 medicine focused on wellness, and will reverse the escalating costs of drug development an will have enormous social and economic benefits. Our vision for P4 medicine in 10 years is that each patient will be associated with a virtual data cloud of billions of data points and that we will have the information technology for healthcare to reduce this enormous data dimensionality to simple hypotheses about health and/or disease for each individual. These data will be multi-scale across all levels of biological organization and extremely heterogeneous in type - this enormous amount of data represents a striking signal-to-noise (S/N) challenge. The key to dealing with this S/N challenge is to take a "holistic systems approach" to disease as we will discuss in this article.
authors: Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA. ihood@systemsbiology.org
authors: Leroy
authors: L
authors: Hood
authors: Rudi
authors: R
authors: Balling
authors: Charles
authors: C
authors: Auffray
mesh_terms: D000818:Animals; D005544:Forecasting; D023281:Genomics / Q000379:methods; D006801:Humans; D057285:Precision Medicine / Q000379:methods* / Q000639:trends; D049490:Systems Biology / Q000379:methods* / Q000639:trends