Evidence map›Paper›PMID 22815171›Full record

ArticleBiotechnology journal2012

Revolutionizing medicine in the 21st century through systems approaches.

Leroy Hood, Rudi Balling, Charles Auffray

Abstract read
In one paragraph

Article in Biotechnology journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. P4 medicine and osteoporosis: a systematic review.Wiener klinische Wochenschrift · 2016
    Pooled it
  2. Sorting out and navigating uncertainty in precision medicine.History and philosophy of the life sciences · 2026
    Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Implementing genomic medicine in New Zealand.Journal of the Royal Society of New Zealand · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Precision diagnostics in children.Cambridge prisms. Precision medicine · 2023
    Review
  14. Article
  15. Article
  16. Engineering complexity in human tissue models of cancer.Advanced drug delivery reviews · 2022
    Review
  17. Article
  18. Article
  19. Article
  20. Review

20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Leroy HoodInstitute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA. ihood@systemsbiology.org
Rudi Balling
Charles Auffray

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2006 to 2016
$30.6M
NIGMS NIH HHS GM076547NIGMS NIH HHS P50 GM076547
6 · The paper itself

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.

Indexed as

AnimalsForecastingGenomicsHumansPrecision MedicineSystems Biology

Identifiers

PMID22815171
PMCPMC3962497

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.