The era of meta-data in health and during critical illness.

A new personalized approach to critical illness is necessary. Evidence base medicine compares heterogeneous populations and so far has brought few (if any) available treatments fro critically ill patients. This approach lacks individualization of treatment. This kind of "signature medicine" could only come from the analysis of genomic, proteomic and metabolomic data from large population-based set of healthy individuals and compare it to specific patterns present during the disease state. During critical illness, identification of specific patterns of activation could increase the chance of therapeutic success by inhibiting or stimulating different parts of the interactome. More over, integration of hemodynamic, respiratory, and/or metabolic data, will allow multiple variables to be analyzed. This requieres a significant challenge for the medical community. From governmental policies to allow massive collection of blood samples from a given population, to researchers, clinical physicians, laboratory, protein data-banks and the general population. After the collection of millions of samples from healthy controls and from every disease state, we could have a population-based profile of homeostasis and track the deviation from this pattern of individual patients. Knowledge of every component involved in the dis-regulation of homeostasis would allow for specific treatments in each case. We could even tailored drug exposure to reduce secondary effects and toxicity according to models done with bio-informatics. Only after identifying if the individual pattern of each patients as a possible responder, then the best "evidence based" therapy should be initiated.
I do not address to the multiple possibilities that could develop from this hypothesis, since interaction and individuality are now at the center of human evolution.


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