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A vision and a prescription for big data–enabled medicine

Nature Immunology volume 16, pages 435–439 (2015)Cite this article

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Genetic, environmental and socioeconomic factors render humanity remarkably diverse. '-Omic' and sensor technologies permit the capture of this diversity with unprecedented precision. Leveraging these technologies in clinical decision making will help to bring about the long-heralded personalization of medicine.

Much has been written over the past decade about the potential benefits of a more personalized approach to medicine. Many attempts have been made to define personalized medicine, but here we will simply refer to it as any form of medicine that factors differences specific to individual patients into clinical decision making. This encompasses not only the choice of drugs (personalized therapy) but also the prevention of disease. Indeed, one of personalized medicine's most attractive prospects is that it would enable a less reactive kind of medicine, focused on health maintenance and disease prevention rather than disease management. Concurrently, the past decade has also seen tremendous advances in the ability to measure molecular perturbations on very large scales, up to the systems level. Indeed, '-omics' technologies, genomics in particular, allow the measurement of all constitutive elements of a given system and thus altogether eliminate the need to select a panel of analytes, because everything that can possibly be measured in the system (for example, genome or transcriptome) will be measured. In this Commentary, we will discuss the potential role of systems approaches in enabling the personalization of medicine. First, we will start by sharing a vision for medicine in which clinical decision making is enabled by vast amounts of data generated at the individual level: personal big data. In the second part, we will propose a prescription for big data–enabled medicine: a path toward implementing presymptomatic disease diagnosis by leveraging systems-wide profiling technologies.

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Figure 1: Capturing individual variation with the help of mobile-sensor and molecular-profiling technologies in the era of big data–enabled medicine.
Figure 2: Windows of opportunity afforded by high-resolution proximity testing.

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Authors and Affiliations

  1. Damien Chaussabel is at the Sidra Medical and Research Center, Doha, Qatar.,

    Damien Chaussabel

  2. Bali Pulendran is at the Emory Vaccine Center, Emory University, Atlanta, Georgia, USA.,

    Bali Pulendran

Authors
  1. Damien Chaussabel
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  2. Bali Pulendran
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Correspondence to Damien Chaussabel or Bali Pulendran.

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The authors declare no competing financial interests.

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Chaussabel, D., Pulendran, B. A vision and a prescription for big data–enabled medicine. Nat Immunol 16, 435–439 (2015). https://doi.org/10.1038/ni.3151

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