disease by creating a dynamic and comprehensive, yet practical and widely-used, Knowledge Network:

  1. Design of appropriate strategies to collect and integrate disease-relevant information. The Information Commons would be developed by linking molecular data to patient information on a massive scale. Creating a system for establishing this linkage for increasing numbers of individuals—and making the resulting data widely available to researchers—is the key step in moving toward a Knowledge Network and New Taxonomy. Such coupled data can be generated in several ways—including the modest-scale, targeted molecular studies on patient materials that dominate current practice. However, the most direct and effective discovery paradigm involves observational studies that seek to relate molecular data to complete patient medical records available as by-products of routine health care. Effective follow-up of the most promising hypotheses generated through such studies will require laboratory-based biological investigations designed to seek explanations at the biochemical or physiological levels.
  2. Implementation of pilot studies to establish a practical framework to discover relationships between and among molecular and other patient-specific data, patient diagnoses, and clinical outcomes. The new discovery model will involve the mining of large sets of patient data acquired during the ordinary course of health care. This is a novel, largely untested discovery approach. Pilot studies designed to identify and overcome obstacles to successful implementation of this approach will be required before a set of “best practices” can emerge.
  3. Gradual elimination of institutional, cultural, and regulatory barriers to widespread sharing of the molecular profiles and health histories of individuals, while still protecting patients’ rights. The sharing of data about individual patients among multiple parties—including patients, physicians, insurance companies, the pharmaceutical industry, and academic research groups—will be essential. Current policies on consent, confidentiality, data protection and ownership, health cost reimbursement, and intellectual-property will need to be modified to ensure the free flow of research data between all stakeholders without compromising patient interests.


The current model for relating molecular data to diagnoses and clinical outcomes typically involves abstracting clinical data for a modest number of patients from a clinical to a research setting, then attempting to draw correlations between the abstracted clinical data and molecular data such as genetic

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