title: Embracing complexity, inching closer to reality.
abstract: Drugs designed against targets in presumably simple linear signaling pathways found to be associated with disease are often less effective than predicted. One reason for this is the overly simplistic view of the molecular mechanisms underlying common human diseases. This viewpoint is a consequence of biological reductionism, brought about by the need to form a basic understanding of the fundamental attributes of biological systems and by limitations in the set of tools available for analysis of biological systems. However, complex biological systems are best modeled as highly modular, fluid systems exhibiting a plasticity that allows them to adapt to a vast array of conditions. Historically, this viewpoint has long represented the ideal, but the tools needed to examine and describe this complexity were often lacking. Here we argue that the tools of biological science now allow for a more network-oriented view of biological systems and for explaining the underlying causes of disease, as well as the best ways to target disease. Ultimately, this will help to ensure that the right drug is administered to the right patient at the right time. Focusing on well-studied signaling pathways, refining the definition of disease, and identifying disease subtypes, we demonstrate a more holistic approach to elucidating common human diseases, with the potential to revolutionize treatment of these diseases.
authors.affiliation: Rosetta Inpharmatics, 401 Terry Avenue North, Seattle, WA 98109, USA. eric_schadt@merck.com
authors.forename: Eric E
authors.initials: EE
authors.lastname: Schadt
authors.forename: Alan
authors.initials: A
authors.lastname: Sachs
authors.forename: Stephen
authors.initials: S
authors.lastname: Friend
mesh_terms: D000818:Animals; D003433:Crosses, Genetic; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000187:drug effects / Q000502:physiology; D005838:Genotype; D006801:Humans; D008099:Liver / Q000378:metabolism; D051379:Mice; D008815:Mice, Inbred Strains; D008954:Models, Biological; D009765:Obesity / Q000235:genetics; D017346:Protein Serine-Threonine Kinases; D000077294:Receptor, Transforming Growth Factor-beta Type II; D018125:Receptors, Transforming Growth Factor beta / Q000187:drug effects / Q000502:physiology; D015398:Signal Transduction; D051785:Smad Proteins / Q000502:physiology; D016212:Transforming Growth Factor beta / Q000502:physiology
chemical_list: D018125:Receptors, Transforming Growth Factor beta; D051785:Smad Proteins; D016212:Transforming Growth Factor beta; D017346:Protein Serine-Threonine Kinases; D000077294:Receptor, Transforming Growth Factor-beta Type II