Systems Medicine in Oncology: Signaling Network Modeling and New-Generation Decision-Support Systems

  • Silvio Parodi
  • Giuseppe Riccardi
  • Nicoletta Castagnino
  • Lorenzo Tortolina
  • Massimo Maffei
  • Gabriele Zoppoli
  • Alessio Nencioni
  • Alberto Ballestrero
  • Franco Patrone
Part of the Methods in Molecular Biology book series (MIMB, volume 1386)

Abstract

Two different perspectives are the main focus of this book chapter: (1) A perspective that looks to the future, with the goal of devising rational associations of targeted inhibitors against distinct altered signaling-network pathways. This goal implies a sufficiently in-depth molecular diagnosis of the personal cancer of a given patient. A sufficiently robust and extended dynamic modeling will suggest rational combinations of the abovementioned oncoprotein inhibitors. The work toward new selective drugs, in the field of medicinal chemistry, is very intensive. Rational associations of selective drug inhibitors will become progressively a more realistic goal within the next 3–5 years. Toward the possibility of an implementation in standard oncologic structures of technologically sufficiently advanced countries, new (legal) rules probably will have to be established through a consensus process, at the level of both diagnostic and therapeutic behaviors.

(2) The cancer patient of today is not the patient of 5–10 years from now. How to support the choice of the most convenient (and already clinically allowed) treatment for an individual cancer patient, as of today? We will consider the present level of artificial intelligence (AI) sophistication and the continuous feeding, updating, and integration of cancer-related new data, in AI systems. We will also report briefly about one of the most important projects in this field: IBM Watson US Cancer Centers. Allowing for a temporal shift, in the long term the two perspectives should move in the same direction, with a necessary time lag between them.

Key words

Cancer genomics Signaling-network pathways Individual cancer patient Oncoprotein inhibitors Rational associations of targeted inhibitors New clinical trial designs Systems medicine Decision-support systems Artificial intelligence IBM Watson 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Silvio Parodi
    • 1
  • Giuseppe Riccardi
    • 2
  • Nicoletta Castagnino
    • 1
  • Lorenzo Tortolina
    • 1
  • Massimo Maffei
    • 1
  • Gabriele Zoppoli
    • 1
  • Alessio Nencioni
    • 1
  • Alberto Ballestrero
    • 1
  • Franco Patrone
    • 1
  1. 1.Department of Internal Medicine (DIMI)Genoa UniversityGenoaItaly
  2. 2.Signals and Interactive Systems lab, Department of Engineering and Information ScienceTrento UniversityTrentoItaly

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